|
CREATE CONSTRAINT constraint_fa8ae23d FOR (node:Track) REQUIRE (node.Track) IS UNIQUE; |
|
CREATE CONSTRAINT constraint_f4498992 FOR (node:Territory) REQUIRE (node.Territory) IS UNIQUE; |
|
CREATE CONSTRAINT constraint_a8638996 FOR (node:Talk) REQUIRE (node.TalkTitle) IS UNIQUE; |
|
CREATE CONSTRAINT constraint_2d88c94a FOR (node:Speaker) REQUIRE (node.SpeakerName) IS UNIQUE; |
|
UNWIND [{Track:"Beginner", properties:{}}, {Track:"Intermediate", properties:{}}, {Track:"Advanced", properties:{}}] AS row |
|
CREATE (n:Track{Track: row.Track}) SET n += row.properties; |
|
UNWIND [{Territory:"Americas", properties:{}}, {Territory:"APAC", properties:{}}, {Territory:"EMEA", properties:{}}] AS row |
|
CREATE (n:Territory{Territory: row.Territory}) SET n += row.properties; |
|
UNWIND [{TalkTitle:"Welcome to NODES 2022 - AMER", properties:{TalkSummary:"Find out what you can expect from the 24 hours of programming, and learn how to use the NODES event platform.", `START-UTC`:datetime('2022-11-16T15:00:00Z'), `END-UTC`:datetime('2022-11-16T15:15:00Z')}}, {TalkTitle:"Keynote: Social Network Interventions ", properties:{TalkSummary:"A deep understanding of social networks can be used to create an artificial tipping point, changing population behavior by fostering behavioral cascades. Here, we experimentally test this proposition. We show that network-based targeting substantially increases population-level adoption of new behaviors. ", `START-UTC`:datetime('2022-11-17T09:15:00Z'), `END-UTC`:datetime('2022-11-17T09:55:00Z')}}, {TalkTitle:"Introducing Neo4j 5 for Administrators ", properties:{TalkSummary:"In this session, we introduce Neo4j 5 to the world with an overview of the new features.", `START-UTC`:datetime('2022-11-16T16:00:00Z'), `END-UTC`:datetime('2022-11-16T16:35:00Z')}}, {TalkTitle:"Bootstrapping Your Graph Project With Neo4j Workspace ", properties:{TalkSummary:"Join this session to learn more about the new Neo4j Workspace which blends Data Modelling and Import, Cypher Querying and Visual Exploration capabilities all in one place. ", `START-UTC`:datetime('2022-11-16T16:40:00Z'), `END-UTC`:datetime('2022-11-16T17:15:00Z')}}, {TalkTitle:"A Space to Relax: Guided Meditation (AMER) ", properties:{TalkSummary:"In the middle of all the interesting graph sessions, you might need some time to let things land a bit, give your mind some well-needed rest, and come back re-charged and energized for the rest of the day.", `START-UTC`:datetime('2022-11-16T17:20:00Z'), `END-UTC`:datetime('2022-11-16T17:35:00Z')}}, {TalkTitle:"Graph Modeling: The Shadow Graph ", properties:{TalkSummary:"One of the best things about working with graphs is the flexibility of the graph model.\n\nAs part of a tennis predictions app that I've been building, I needed to come up with a way to represent the actual result of a match alongside the predictions done by participants. ", `START-UTC`:datetime('2022-11-16T17:40:00Z'), `END-UTC`:datetime('2022-11-16T17:55:00Z')}}, {TalkTitle:"Graph Database Techniques to Reduce Risk and Innovate ", properties:{TalkSummary:"This session will look at a unique case study recently completed by the Software Engineering Institute (SEI) to tackle challenges encountered by our DoD clients in cybersecurity, risk management, and policy. ", `START-UTC`:datetime('2022-11-16T18:00:00Z'), `END-UTC`:datetime('2022-11-16T18:35:00Z')}}, {TalkTitle:"Divide and Conquer: Send Forth the Microservices ", properties:{TalkSummary:"In this session, we will explore how microservices divide functionality and responsibility and multiply their forces to handle load and complexity. ", `START-UTC`:datetime('2022-11-16T18:40:00Z'), `END-UTC`:datetime('2022-11-16T19:15:00Z')}}, {TalkTitle:"Security and Velocity Through Declarative Ingestion ", properties:{TalkSummary:"Learn about Intuit Security's Ingestion System, Munchlax.\nMunchlax is a kubernetes powered system for declaratively specifying what to ingest and how to ingest data into a graph database. ", `START-UTC`:datetime('2022-11-16T19:20:00Z'), `END-UTC`:datetime('2022-11-16T19:55:00Z')}}, {TalkTitle:"Hypertext Super Collaborator ", properties:{TalkSummary:"Systems thinking inspires us to write, share, and aggregate small graphs in order to discover larger ones. We compose these products of our imagination as graph-shaped \"poems\" in the style of Haiku. Wiki's property graph representation joins tables and trees in the space right behind the glass and travels freely within our federation. A thematic sketch, such as \"organizing for action,\" makes purposeful authoring a matter of choosing relations from a menu. Nodes that match are highlighted. Nodes that don't match invite another composition that brings these ideas together.", `START-UTC`:datetime('2022-11-16T20:00:00Z'), `END-UTC`:datetime('2022-11-16T20:15:00Z')}}, {TalkTitle:"Discover Invisible Patterns in Your Data: Connect Google Sheets Tables and Neo4j ", properties:{TalkSummary:"In this session, Kateryna Nesvit will provide guidance and code for connecting a Google Sheets spreadsheet to a graph in Neo4j. She will cover the fundamental transformation from table data to a graph data model. You will also learn Cypher queries and take the first steps in using data to empower your decisions and make your projects and business successful.", `START-UTC`:datetime('2022-11-16T20:20:00Z'), `END-UTC`:datetime('2022-11-16T20:35:00Z')}}, {TalkTitle:"Let's Get Functional! Pull Off a Trifecta With Spring Cloud Function, Azure Functions, and Neo4j ", properties:{TalkSummary:"This session examines what makes a capability an ideal candidate for development and deployment as a function. The presenter will lead attendees in a Live Coding Adventure(TM) to demonstrate how to create candidate functions using the power of Spring Boot and Spring Cloud Function. ", `START-UTC`:datetime('2022-11-16T20:40:00Z'), `END-UTC`:datetime('2022-11-16T21:15:00Z')}}, {TalkTitle:"Graph Databases for Python Developers ", properties:{TalkSummary:"Graph databases are increasingly popular in the data science field but as a Python programmer you might not have worked with one yet. In this session, you'll get an understanding of the current graph database landscape and the technologies available to Python devs and learn how and what it takes to integrate with a graph database.", `START-UTC`:datetime('2022-11-16T21:20:00Z'), `END-UTC`:datetime('2022-11-16T21:55:00Z')}}, {TalkTitle:"Closing Q&A With Emil and Andreas: AMERICAS ", properties:{TalkSummary:"Neo4j CEO and Co-founder Emil Eifrem and Developer Relations Community Manager Andreas Kollegger will answer audience questions to wrap up NODES. Throughout the two-day event, we encourage participants to keep track of any questions that arise to take full advantage of Emil and Andreas' graph technology expertise.", `START-UTC`:datetime('2022-11-17T08:30:00Z'), `END-UTC`:datetime('2022-11-17T08:50:00Z')}}, {TalkTitle:"Modeling NFT Tweets as a Knowledge Graph Using Neo4j ", properties:{TalkSummary:"In this session, we will try to play with a chunk of NFT data grabbed by my research team recently. I'll show how we can model this data as a Knowledge Graph using CSV importer tool and play around with it", `START-UTC`:datetime('2022-11-16T16:00:00Z'), `END-UTC`:datetime('2022-11-16T16:15:00Z')}}, {TalkTitle:"DeepFace Recognition With Neo4j ", properties:{TalkSummary:"Graph databases are powerful for discovering relationships that are hard to find. In this presentation, we will explore how to use Neo4j graph database for facial recognition analysis using DeepFace.", `START-UTC`:datetime('2022-11-16T16:20:00Z'), `END-UTC`:datetime('2022-11-16T16:35:00Z')}}, {TalkTitle:"IAC: SchemaSmith for Data Governance at JB Hunt ", properties:{TalkSummary:"Do you want to express your graph in easy-to-read YAML and push an easy button to automate scripts to build out your indexes and constraints? This tool will get you at least 67.8% of the way there!", `START-UTC`:datetime('2022-11-16T16:40:00Z'), `END-UTC`:datetime('2022-11-16T17:15:00Z')}}, {TalkTitle:"PHP Devs, Change Your Life ", properties:{TalkSummary:"Talk at conference in 2015 showed me Neo4j for first time and when I created first project with it, my life has changed. Let this talk to raise your desire to change your life today as PHP developer.", `START-UTC`:datetime('2022-11-16T17:20:00Z'), `END-UTC`:datetime('2022-11-16T17:35:00Z')}}, {TalkTitle:"Fashion Retail Recommendations Using Neo4j Graph Data Science and Apache Arrow ", properties:{TalkSummary:"During this presentation, we will show you how to load a dataset on Neo4j Graph Data Science using the new Apache Arrow feature. Then we will use Neo4j graph algorithms to generate the embeddings for recommendations.", `START-UTC`:datetime('2022-11-16T17:40:00Z'), `END-UTC`:datetime('2022-11-16T17:55:00Z')}}, {TalkTitle:"Demystifying Graph Analytics With Visualization ", properties:{TalkSummary:"Graph visualization is a proven method for displaying analytical data to non-experts. It’s effective because it binds analytically derived metrics to instantly recognizable visual properties like color, size, icons, and link widths. This is how developers create powerful graph visualization applications that reveal insights that remain hidden in traditional graph representations.", `START-UTC`:datetime('2022-11-16T18:00:00Z'), `END-UTC`:datetime('2022-11-16T18:35:00Z')}}] AS row |
|
CREATE (n:Talk{TalkTitle: row.TalkTitle}) SET n += row.properties; |
|
UNWIND [{TalkTitle:"Towards Real-time Knowledge Graphs for Non-Player Characters in Games ", properties:{TalkSummary:"This session discusses the development of a Neo4j plugin for Epic Game's Unreal Engine to allow for communications between a game environment's players and non-player characters. ", `START-UTC`:datetime('2022-11-16T18:40:00Z'), `END-UTC`:datetime('2022-11-16T19:15:00Z')}}, {TalkTitle:"GraphQL Quickstart With the Neo4j GraphQL Library ", properties:{TalkSummary:"GraphQL is a great fit for Neo4j, extending the graph model to the API layer of your stack. Getting started is quite easy with the right tools. In this talk, you'll learn how you can go from dataset to application in 15 minutes.", `START-UTC`:datetime('2022-11-16T19:20:00Z'), `END-UTC`:datetime('2022-11-16T19:35:00Z')}}, {TalkTitle:"Quick Deploy GraphQL API With SST ", properties:{TalkSummary:"Learn how to build and deploy a Neo4j GraphQL API using the Serverless Stack Toolkit (SST).", `START-UTC`:datetime('2022-11-16T19:40:00Z'), `END-UTC`:datetime('2022-11-16T19:55:00Z')}}, {TalkTitle:"Exploring Data With Neo4j Bloom ", properties:{TalkSummary:"Learn how the latest updates for Neo4j Bloom make it even easier to visually explore and derive value from graph data, even with little to no coding.", `START-UTC`:datetime('2022-11-16T20:00:00Z'), `END-UTC`:datetime('2022-11-16T20:35:00Z')}}, {TalkTitle:"Graph Data Science for Computer Vision", properties:{TalkSummary:"In this talk, we'll discuss computer vision and the kinds of graph modeling techniques that lend themselves well to this domain. We will utilize a few sample use cases and explore the utilization of a graph-based model and some of its potential alternatives, including some considerations and trade-offs.", `START-UTC`:datetime('2022-11-16T20:40:00Z'), `END-UTC`:datetime('2022-11-16T20:55:00Z')}}, {TalkTitle:"Top 10 Tips for Evaluating “Benchmark” Results ", properties:{TalkSummary:"The LDBC datasets and queries have been used and abused by unscrupulous persons for both fun and profit. This session explores the sub-optimal LDBC data model and queries and how they can be tweaked for significantly better performance.", `START-UTC`:datetime('2022-11-16T21:00:00Z'), `END-UTC`:datetime('2022-11-16T21:15:00Z')}}, {TalkTitle:"Using Sport Data to Build a Graph Model of Inconsistent Hierarchies Over Time ", properties:{TalkSummary:"This session teaches a generalizable graph model for nesting teams within leagues across multiple seasons. Sports league structures are often similar, but there are peculiarities in each, such as promotion and relegation; conferences and divisions; teams changing names and locations; and multiple teams from the same college/club. ", `START-UTC`:datetime('2022-11-16T21:20:00Z'), `END-UTC`:datetime('2022-11-16T21:55:00Z')}}, {TalkTitle:"Graph Pattern Matching ", properties:{TalkSummary:"Graph pattern matching is at the core of all graph query languages. What a user can or cannot do is limited by the expressiveness and performance of graph navigation-oriented capabilities.", `START-UTC`:datetime('2022-11-16T16:00:00Z'), `END-UTC`:datetime('2022-11-16T16:35:00Z')}}, {TalkTitle:"GNNs at Scale With Graph Data Science Sampling and Python Client Integration ", properties:{TalkSummary:"", `START-UTC`:datetime('2022-11-16T16:40:00Z'), `END-UTC`:datetime('2022-11-16T17:15:00Z')}}, {TalkTitle:"Neo4j Ops Manager: Intro and Roadmap ", properties:{TalkSummary:"This session will provide an overview of the recently released Neo4j Ops Manager product for enterprise customers. We'll explore its use cases and features, as well as watch a demo and look at a product roadmap.", `START-UTC`:datetime('2022-11-16T17:20:00Z'), `END-UTC`:datetime('2022-11-16T17:55:00Z')}}, {TalkTitle:"Data Management with Knowledge Graphs: Bringing Archives to Life ", properties:{TalkSummary:"Public archives contain incredible amount of knowledge. In this session, we'll cover a real use case of building a knowledge graph for the archive of a major foundation to help empower researchers (or business analysts) to access previously unavailable levels of insights.", `START-UTC`:datetime('2022-11-16T18:00:00Z'), `END-UTC`:datetime('2022-11-16T18:35:00Z')}}, {TalkTitle:"Arcurve Skills and Staffing Recommender ", properties:{TalkSummary:"Challenge: project planning and team building can be difficult when trying to balance skills, experience, and candidates' availability to get the right people on the job. Proposition: leverage data on roles, experience, skills, and capacity to dynamically recommend the best teams using graph technology. ", `START-UTC`:datetime('2022-11-16T18:40:00Z'), `END-UTC`:datetime('2022-11-16T19:15:00Z')}}, {TalkTitle:"Making Sense of Geospatial Data With Knowledge Graphs ", properties:{TalkSummary:"In this presentation, we examine how the open-source Neo4j graph database can be used with QGIS and Python for making sense of geospatial data using graph algorithms and graph data visualization while combining data from OpenStreetMap, cadastral data, and public data portals to find insights that address the use cases mentioned above.", `START-UTC`:datetime('2022-11-16T19:20:00Z'), `END-UTC`:datetime('2022-11-16T19:55:00Z')}}, {TalkTitle:"Neo4j Data Loading (ETL/ELT) Best Practices", properties:{TalkSummary:"What patterns are most appropriate for building ETLs using Neo4j? In this session, we share how we built the Google Cloud DataFlow flex template using the Neo4j Java API. You can then apply the same approach to building read and write operators in any framework, including AWS Lambda and Google Cloud Functions.", `START-UTC`:datetime('2022-11-16T20:00:00Z'), `END-UTC`:datetime('2022-11-16T20:35:00Z')}}, {TalkTitle:"Are Personal Knowledge Graphs the Next Big Thing for Search? ", properties:{TalkSummary:"There are three types of Personal Knowledge Graphs (PKGs) right now, all of which have their own merits, but one, in particular, has \"next big thing\" written all over it.\n\nIn this session, we will walk through the three types of PKGs and explore how one of them may revolutionize the way we personalize the search experience.", `START-UTC`:datetime('2022-11-16T20:40:00Z'), `END-UTC`:datetime('2022-11-16T21:15:00Z')}}, {TalkTitle:"Graph Algorithms and Visualization for Clinical Care Support of Pneumonia ", properties:{TalkSummary:"We will take a deep dive into patient journeys through the Medical Information Mart for Intensive Care (MIMIC)-IV de-identified Electronic Medical Records (EMR) data from 2008-2019, for patients diagnosed with pneumonia.", `START-UTC`:datetime('2022-11-16T21:20:00Z'), `END-UTC`:datetime('2022-11-16T21:55:00Z')}}, {TalkTitle:"Welcome to NODES 2022 - APAC", properties:{TalkSummary:"Find out what you can expect from the 24 hours of programming, and learn how to use the NODES event platform.", `START-UTC`:datetime('2022-11-17T01:30:00Z'), `END-UTC`:datetime('2022-11-17T01:45:00Z')}}, {TalkTitle:"Workspace in AuraDB ", properties:{TalkSummary:"In this session, we'll demonstrate the new-in-v5 workspace that combines practitioner tools into a single unified experience.", `START-UTC`:datetime('2022-11-17T02:30:00Z'), `END-UTC`:datetime('2022-11-17T02:45:00Z')}}, {TalkTitle:"Easy On-Ramp to Using Graphs ", properties:{TalkSummary:"In this session, you'll learn how to create a free Neo4j graph database in the cloud, load your data, and start gaining insights quickly.", `START-UTC`:datetime('2022-11-17T02:50:00Z'), `END-UTC`:datetime('2022-11-17T03:05:00Z')}}, {TalkTitle:"Exploring the Relationships Between People in the Ancient Chinese Novel, \"Three Kingdoms\" ", properties:{TalkSummary:"\"Three Kingdoms\" tells the story of the fateful last reign of the Han dynasty (206 B.C.–A.D. 220) when the Chinese empire was divided into three warring kingdoms. This Ming dynasty masterpiece continues to be widely influential in China, Korea, Japan, and Vietnam and remains a great work of world literature that has become the Chinese national epic. ", `START-UTC`:datetime('2022-11-17T03:10:00Z'), `END-UTC`:datetime('2022-11-17T03:45:00Z')}}] AS row |
|
CREATE (n:Talk{TalkTitle: row.TalkTitle}) SET n += row.properties; |
|
UNWIND [{TalkTitle:"Creating Graphville: A Neo4j Educational Platform ", properties:{TalkSummary:"In this session, Vlad Batushkov will share how he created Graphville, an educational platform for beginners to learn Cypher and Neo4j basics. This indie project has been in development for three years and has become a public product. He will look back to the beginning of the project, summarize the most important aspects of success, and share it with developers.", `START-UTC`:datetime('2022-11-17T03:50:00Z'), `END-UTC`:datetime('2022-11-17T04:05:00Z')}}, {TalkTitle:"Learn Neo4j in Chinese With Neo4j GraphAcademy", properties:{TalkSummary:"Introducing new Chinese courses on GraphAcademy to audiences who love to read in Chinese! We'll walk through one of the \"Neo4j Fundamentals\" courses in this session.", `START-UTC`:datetime('2022-11-17T04:10:00Z'), `END-UTC`:datetime('2022-11-17T04:25:00Z')}}, {TalkTitle:"From Game of Thrones to Information System Cartography ", properties:{TalkSummary:"Come to this session to hear the story of how we built an information system cartography solution on Neo4j that answers complex questions. We can answer questions about operations, single points of failure and critical apps. ", `START-UTC`:datetime('2022-11-17T04:30:00Z'), `END-UTC`:datetime('2022-11-17T05:05:00Z')}}, {TalkTitle:"Coffee Knowledge Graph ", properties:{TalkSummary:"Let's build a coffee knowledge graph. Then, let's drink the coffee that Neo4j recommends!", `START-UTC`:datetime('2022-11-17T05:10:00Z'), `END-UTC`:datetime('2022-11-17T05:45:00Z')}}, {TalkTitle:"Analyzing Spammers in Twitter User Network ", properties:{TalkSummary:"Spammers plague Twitter feeds and often bother users, at least in my country, Thailand. I'll demonstrate how to detect spam and the users who generate them.\nOnce spammers are identified, network algorithms can analyze them to answer a few more questions. ", `START-UTC`:datetime('2022-11-17T05:50:00Z'), `END-UTC`:datetime('2022-11-17T06:05:00Z')}}, {TalkTitle:"Neo4j Lectures of the Stanford CS224W Course ", properties:{TalkSummary:"This Stanford University lecture of the course CS224W (in Chinese language) is \"Machine Learning with Graphs\"", `START-UTC`:datetime('2022-11-17T06:10:00Z'), `END-UTC`:datetime('2022-11-17T06:25:00Z')}}, {TalkTitle:"Track Data Lineage With a Graph Database ", properties:{TalkSummary:"This talk introduces data lineage use cases, shows how data is represented in a graph database, and how we use graph database features for fast and efficient data processing.", `START-UTC`:datetime('2022-11-17T06:30:00Z'), `END-UTC`:datetime('2022-11-17T07:05:00Z')}}, {TalkTitle:"A Space to Relax: Guided Meditation (APAC) ", properties:{TalkSummary:"In the middle of all the interesting graph sessions, you might need some time to let things land a bit, give your mind some well-needed rest, and come back re-charged and energized for the rest of the day.", `START-UTC`:datetime('2022-11-17T07:10:00Z'), `END-UTC`:datetime('2022-11-17T07:25:00Z')}}, {TalkTitle:"Playing With State Machines ", properties:{TalkSummary:"In this talk, we'll play with finite state machines. We'll demonstrate (in a radical Cypher-and-APOC-only way) how Automata can be used in Neo4J to build a compiler, to orchestrate a game or even solve AI classical problems.", `START-UTC`:datetime('2022-11-17T07:30:00Z'), `END-UTC`:datetime('2022-11-17T07:45:00Z')}}, {TalkTitle:"cy2py: Seamless Neo4j Integration in Python Notebooks ", properties:{TalkSummary:"This session will introduce cy2py, a brand new Jupyter extension that allows you to easily integrate Neo4j in Python notebooks. We'll demonstrate how easy it is to visualize the result of Cypher queries as graphs and how you can create Python DataFrames from them, as well as combine them with different plotting libraries.", `START-UTC`:datetime('2022-11-17T07:50:00Z'), `END-UTC`:datetime('2022-11-17T08:05:00Z')}}, {TalkTitle:"ESG Supply Chain Knowledge Graph ", properties:{TalkSummary:"In this session, we will create a knowledge graph to examine how adding different data sources can create new value in terms of environmental, social, and governance (ESG)-related topics. This challenge has particular relevancy because the European Union is currently considering new supply chain legislation. ", `START-UTC`:datetime('2022-11-17T08:10:00Z'), `END-UTC`:datetime('2022-11-17T08:25:00Z')}}, {TalkTitle:"Using Graph Databases for Consumer Products ", properties:{TalkSummary:"Graph databases can provide an excellent alternative to both SQL and other NoSQL databases when building consumer products. Learn how to get started with property graphs, as well as some best practices for modeling data effectively.", `START-UTC`:datetime('2022-11-17T02:30:00Z'), `END-UTC`:datetime('2022-11-17T03:05:00Z')}}, {TalkTitle:"Rapid App Prototyping Using Streamlit and Neo4j ", properties:{TalkSummary:"New analytics and data science projects are challenged with demonstrating value early based on source data. In this presentation, we will demonstrate how to shorten time to value by quickly developing a standalone application using Streamlit. ", `START-UTC`:datetime('2022-11-17T03:10:00Z'), `END-UTC`:datetime('2022-11-17T03:45:00Z')}}, {TalkTitle:"Managing Software-BOM, Security Issues, and Their Knowledge Graphs Is Easy With Neo4j ", properties:{TalkSummary:"Software consists of various libraries. Whenever software is updated, the versions of the libraries also change. Sometimes vulnerabilities are discovered in the libraries.\nWe need to manage the libraries and vulnerabilities at the same time. We also need data science to analyze huge amounts of data, such as what changes were released, how they were handled, and what the results were.\nAll of this is accomplished using Neo4j.", `START-UTC`:datetime('2022-11-17T03:50:00Z'), `END-UTC`:datetime('2022-11-17T04:25:00Z')}}, {TalkTitle:"Connected Data Lakehouse: Neo4j and Databricks Reference Data Architecture ", properties:{TalkSummary:"In this technical session, Neo4j and Databricks will discuss and demonstrate a reference architecture that leverages each other's strengths in connected data and big data to ingest, transform, analyse, and present insights. ", `START-UTC`:datetime('2022-11-17T04:30:00Z'), `END-UTC`:datetime('2022-11-17T05:05:00Z')}}, {TalkTitle:"Construction and Application of Knowledge Graphs: Manufacturing Process for Box Parts ", properties:{TalkSummary:"This session describes how a knowledge graph can capture the structural model for box parts, including the geometric characteristics of the part, the characteristics of the manufacturing process, the processing equipment, tools, and other entities. ", `START-UTC`:datetime('2022-11-17T05:10:00Z'), `END-UTC`:datetime('2022-11-17T05:25:00Z')}}, {TalkTitle:"Knowledge Graphs Powering Active Metadata ", properties:{TalkSummary:"In a world where each organization is now data-heavy, plenty of data is available for decision-making. However, understanding the data and context, i.e. having a human-like intelligence, becomes key to gaining a competitive advantage. The journey begins by knowing your data and building a living, pulsating, intelligent metadata. This session discusses leveraging a knowledge graph for creating active metadata.", `START-UTC`:datetime('2022-11-17T05:30:00Z'), `END-UTC`:datetime('2022-11-17T05:45:00Z')}}, {TalkTitle:"Better Testing With Testcontainers ", properties:{TalkSummary:"In this session, you'll learn how to start new instances of the database along with your tests whenever needed, take control of the lifetime of the container, and expose connection information needed for testing. With this, your testing infrastructure becomes much more portable and there is no need to share credentials of the test server in the future.", `START-UTC`:datetime('2022-11-17T05:50:00Z'), `END-UTC`:datetime('2022-11-17T06:25:00Z')}}, {TalkTitle:"Liquibase & Neo4j: The Migration Sweet Deal ", properties:{TalkSummary:"Bring version control to your database structure! But wait! Does that even make sense for a schema-less database like Neo4j?\n\nLet's see how Liquibase concepts, battle-tested for over 15 years on relational databases, apply to Neo4j today and how we can enjoy high-level refactorings while taming graph complexity. ", `START-UTC`:datetime('2022-11-17T06:30:00Z'), `END-UTC`:datetime('2022-11-17T07:05:00Z')}}, {TalkTitle:"Explore Your Graphs Visually With Jupyter Notebooks ", properties:{TalkSummary:"Learn how to conveniently explore the contents of your Neo4j graph database visually, right inside your Jupyter notebooks. Create powerful notebook scripts that connect to your graph database using Python, execute Cypher queries, and run graph data science algorithms. Finally, create beautiful and helpful visualizations to analyze the results. We'll be using free tools!", `START-UTC`:datetime('2022-11-17T07:10:00Z'), `END-UTC`:datetime('2022-11-17T07:45:00Z')}}] AS row |
|
CREATE (n:Talk{TalkTitle: row.TalkTitle}) SET n += row.properties; |
|
UNWIND [{TalkTitle:"BlueHound: Community-Driven Security Based on Neo4j and NeoDash ", properties:{TalkSummary:"This talk will focus on the technical details of how we use Neo4j with security data to help organizations defend themselves, presenting some of the Cypher queries and the use cases that make up BlueHound. It will also cover using NeoDash and the changes that we’ve made to make it suitable for BlueHound.", `START-UTC`:datetime('2022-11-17T07:50:00Z'), `END-UTC`:datetime('2022-11-17T08:25:00Z')}}, {TalkTitle:"The Heisenbugs - Finding Collusion Among Malicious Entities Through Knowledge Graph ", properties:{TalkSummary:"In this talk, we shall discuss how we can apply the concept of Knowledge Graph as a critical aid to solve a challenging technical scenario often faced by a security researcher. We can consider this scenario equivalent to an Asimovian Robot’s dilemma in taking a decision adhering to the “Laws of Robotics”.", `START-UTC`:datetime('2022-11-17T02:30:00Z'), `END-UTC`:datetime('2022-11-17T03:05:00Z')}}, {TalkTitle:"Doctor.ai: A Graph-Based Medical Chatbot ", properties:{TalkSummary:"Knowledge graphs are prevalent, especially in medicine and healthcare – but so far, only experts can operate them. A natural language chatbot can change that. We have developed a cloud-native medical chatbot called Doctor.ai, backed by a Neo4j graph. We can employ either AWS Lex, GPT-3, or Alan AI as the natural language understanding engine. ", `START-UTC`:datetime('2022-11-17T03:10:00Z'), `END-UTC`:datetime('2022-11-17T03:45:00Z')}}, {TalkTitle:"Running Neo4j in Docker and Deploying Neo4j Application in OpenShift ", properties:{TalkSummary:"In this session, we'll discuss how to deploy Neo4j in Docker and how to deploy the Neo4j application in OpenShift.", `START-UTC`:datetime('2022-11-17T03:50:00Z'), `END-UTC`:datetime('2022-11-17T04:05:00Z')}}, {TalkTitle:"Knowledge Graphs and Machine Learning for Halal Food Product Recommendations ", properties:{TalkSummary:"In this session, we'll compare the products from an online grocery website with the Halal LOD dataset using the Naive Bayes, K Nearest Neighbors, and Random Forest methods. We'll perform feature extraction using several graph algorithms: Common Neighbors, Preferential Attachment, Total Neighbors, Label Propagation, and Louvain.", `START-UTC`:datetime('2022-11-17T04:10:00Z'), `END-UTC`:datetime('2022-11-17T04:25:00Z')}}, {TalkTitle:"Take Data to the Next Level With Graph Machine Learning ", properties:{TalkSummary:"In this session, Joinal Ahmed from Google and Chaitra Ravada from Twitter will discuss why graph machine learning makes more sense than the traditional ML approach and show you how graph ML powers use cases like recommendation systems, fraud detection, and more. ", `START-UTC`:datetime('2022-11-17T04:30:00Z'), `END-UTC`:datetime('2022-11-17T05:05:00Z')}}, {TalkTitle:"CloudScreen: A Graph-Based Drug Repurposing Platform Empowered by Machine Learning ", properties:{TalkSummary:"In this session, we'll present in silico drug repurposing through machine learning analysis of a biochemical knowledge graph. Drug repurposing is the process that identifies the use of an existing drug to a novel protein target. This procedure can save a lot of time and funds during drug discovery and development phases. ", `START-UTC`:datetime('2022-11-17T05:10:00Z'), `END-UTC`:datetime('2022-11-17T05:45:00Z')}}, {TalkTitle:"Generating a Hematopoietic Stem Cell Knowledge Graph for Scientific Knowledge Discovery ", properties:{TalkSummary:"Knowledge graph is widely used in scientific knowledge discovery. This session proposes a framework of generating knowledge using Subject-Predicate-Object (SPO) triples from literatures, which includes five processes: literatures retrieval, SPO extracting, SPO cleanup, SPO ranking, discovery pattern integrating, and graph building – from which a knowledge graph will be generated.", `START-UTC`:datetime('2022-11-17T05:50:00Z'), `END-UTC`:datetime('2022-11-17T06:05:00Z')}}, {TalkTitle:"Taking Application Security Insights to the Next Level With Fabric and NeoSemantics ", properties:{TalkSummary:"First, we build a federated knowledge base of the D3FEND and OdTM knowledge graphs via Neo4J Fabric and NeoSemantics technologies. Then, we build a knowledge graph representation of a cybersecurity finding report composed of flaws detected in application code. Finally, we use a data federation graph query to associate each flaw with information from the knowledge base.", `START-UTC`:datetime('2022-11-17T06:10:00Z'), `END-UTC`:datetime('2022-11-17T06:25:00Z')}}, {TalkTitle:"Graph-Based Features for Recommendation Systems in Drug Discovery ", properties:{TalkSummary:" In this session, we'll cover a practical example of how Neo4J + GDS can be used to create graph-based features to help identify potential gene targets for a given disease. We'll run through using these features in an optimization model that helps scientists go from thousands of target candidates to a manageable number that they can investigate further. ", `START-UTC`:datetime('2022-11-17T06:30:00Z'), `END-UTC`:datetime('2022-11-17T06:45:00Z')}}, {TalkTitle:"Using Graph Embeddings for Suspicious Bitcoin Transactions ", properties:{TalkSummary:"This lightning talk describes how to find features of ransomware Bitcoin transactions from graph embeddings using Neo4j Graph Data Science. ", `START-UTC`:datetime('2022-11-17T06:50:00Z'), `END-UTC`:datetime('2022-11-17T07:05:00Z')}}, {TalkTitle:"Knowledge Graphs in Time-Series Data ", properties:{TalkSummary:"This talk is about the learning of Knowledge Graph Embeddings for time-series decomposition.", `START-UTC`:datetime('2022-11-17T07:10:00Z'), `END-UTC`:datetime('2022-11-17T07:45:00Z')}}, {TalkTitle:"Fundamentals of Neo4j Graph Data Science Series 2.x – Pipelines and More ", properties:{TalkSummary:"This session will show you how to manage and transform your graphs, how to use machine learning pipelines, and how to make the best use of your trained models – all with a focus on the dedicated GDS Python Client, which enables the data scientist to remain in a familiar environment without losing the strength of the Neo4j graph database in the backend.", `START-UTC`:datetime('2022-11-17T07:50:00Z'), `END-UTC`:datetime('2022-11-17T08:25:00Z')}}, {TalkTitle:"Welcome to NODES 2022 - EMEA", properties:{TalkSummary:"Find out what you can expect from the 24 hours of programming, and learn how to use the NODES event platform.", `START-UTC`:datetime('2022-11-17T09:00:00Z'), `END-UTC`:datetime('2022-11-17T09:15:00Z')}}, {TalkTitle:"What's New in Neo4j 5 and Aura 5 for Developers ", properties:{TalkSummary:"In this session, we'll share an overview of new features in Neo4j 5 with a focus on developers. This will include Aura.", `START-UTC`:datetime('2022-11-17T10:00:00Z'), `END-UTC`:datetime('2022-11-17T10:35:00Z')}}, {TalkTitle:"Index Changes in Neo4j 5 ", properties:{TalkSummary:"In this session, we will go over the new index types: RANGE, POINT, and TEXT, when to use them and how upgrade works. FULLTEXT indexes has received an upgrade and does now support indexing of lists/arrays of strings. A new implementation of TEXT index provide much better performance for queries using CONTAINS or ENDS WITH predicates.", `START-UTC`:datetime('2022-11-17T10:40:00Z'), `END-UTC`:datetime('2022-11-17T11:15:00Z')}}, {TalkTitle:"What's New in Graph Data Science Land ", properties:{TalkSummary:"In this session, we'll discuss what's new in graph data science since the release of Neo4j Graph Data Science 2.0.", `START-UTC`:datetime('2022-11-17T11:20:00Z'), `END-UTC`:datetime('2022-11-17T11:35:00Z')}}, {TalkTitle:"Link Prediction With Graph Data Science at Scale ", properties:{TalkSummary:"Predicting links in a graph is a common use, for example, to predict future friends. However, for bigger graphs, it is not computationally feasible to consider every node pair to find the best. In this talk, we will demonstrate how to use Neo4j Graph Data Science to predict links on larger graphs.", `START-UTC`:datetime('2022-11-17T11:40:00Z'), `END-UTC`:datetime('2022-11-17T11:55:00Z')}}, {TalkTitle:"GraphQL Federation and Key Neo4j GraphQL Library Features", properties:{TalkSummary:"Join the Neo4j GraphQL Team as they talk about one of the latest features they are implementing into the Neo4j GraphQL Library - GraphQL Federation. GraphQL Federation enables you to define \"subgraphs\" and stitch them together using a gateway, allowing them to be queried as a single GraphQL schema. ", `START-UTC`:datetime('2022-11-17T12:00:00Z'), `END-UTC`:datetime('2022-11-17T12:35:00Z')}}, {TalkTitle:"Cymple: Cypher Modular Pythonic Language Extension ", properties:{TalkSummary:"In this session, we will introduce the Neo4j community to Cymple, a new open-source Python package.\nCymple creates neat, reusable Cypher queries with auto-completion in Python. We will show you how \"Cymple\" it is to write your queries in Python.", `START-UTC`:datetime('2022-11-17T12:40:00Z'), `END-UTC`:datetime('2022-11-17T12:55:00Z')}}] AS row |
|
CREATE (n:Talk{TalkTitle: row.TalkTitle}) SET n += row.properties; |
|
UNWIND [{TalkTitle:"A Space to Relax: Guided Meditation (EMEA) ", properties:{TalkSummary:"In the middle of all the interesting graph sessions, you might need some time to let things land a bit, give your mind some well-needed rest, and come back re-charged and energized for the rest of the day.", `START-UTC`:datetime('2022-11-17T13:00:00Z'), `END-UTC`:datetime('2022-11-17T13:15:00Z')}}, {TalkTitle:"Tracing Your Data's DNA ", properties:{TalkSummary:"In this talk I will use live demos and coding examples to explore some techniques of how to create the data lineage graph of individual rows or documents using Change Data Capture (CDC) in source systems. We will store the lineage graph within a graph Database to start with, then explore how other types of database could be used instead. This will create a lineage catalogue that can be queried for all manner of use cases, such as incremental data batch operations, blue-green deployments and \"cell-based security\" of data fields.", `START-UTC`:datetime('2022-11-17T13:20:00Z'), `END-UTC`:datetime('2022-11-17T13:55:00Z')}}, {TalkTitle:"Genealogy With Different Graph Technologies for Data Collection and Visualization ", properties:{TalkSummary:"In this presentation, Véronique Gendner shares a project to collect and display genealogy information. She will present the data collection and export/import process from TheBrain to Gramps via Neo4j, discuss graph models and demonstrate how graphs are a very interesting structure to get the best of human thinking combined with automatic processing. ", `START-UTC`:datetime('2022-11-17T14:00:00Z'), `END-UTC`:datetime('2022-11-17T14:35:00Z')}}, {TalkTitle:"RDBMS to Neo4j Real Time Data Sync with Debezium and Kafka ", properties:{TalkSummary:"During this session, we'll introduce the use of Debezium and Kafka to synchronize data from an RDBMS to Neo4j. The pros, cons, and limitations of this approach will be discussed.", `START-UTC`:datetime('2022-11-17T14:40:00Z'), `END-UTC`:datetime('2022-11-17T14:55:00Z')}}, {TalkTitle:"A Developer's Guide to Building a Graph Project Value Case ", properties:{TalkSummary:"This presentation is designed to teach developers how to build a graph project value case. We will discuss why building business cases can be so complicated and explore ways to simplify the process. ", `START-UTC`:datetime('2022-11-17T15:00:00Z'), `END-UTC`:datetime('2022-11-17T15:15:00Z')}}, {TalkTitle:"Temporal Graph Analysis ", properties:{TalkSummary:"In this session, we'll share our experience with horizon scanning over a graph of medical research papers.", `START-UTC`:datetime('2022-11-17T15:20:00Z'), `END-UTC`:datetime('2022-11-17T15:35:00Z')}}, {TalkTitle:"Building Neo4j Ops Manager: Lessons From Dogfooding ", properties:{TalkSummary:"We've recently released a new product: Neo4j Ops Manager. When building it we decided to use quite a few Neo4j frameworks and projects, like Spring Data Neo4j, Neo4j-Migrations, and the Cypher-DSL. From this experience of using our own tools, we learned quite a bit that we would like to share in this session. Tips and tricks included! ", `START-UTC`:datetime('2022-11-17T15:40:00Z'), `END-UTC`:datetime('2022-11-17T15:55:00Z')}}, {TalkTitle:"Closing Q&A With Emil and Andreas: EMEA", properties:{TalkSummary:"Neo4j CEO and Co-founder Emil Eifrem and Developer Relations Community Manager Andreas Kollegger will answer audience questions to wrap up NODES. Throughout the two-day event, we encourage participants to keep track of any questions that arise to take full advantage of Emil and Andreas' graph technology expertise.", `START-UTC`:datetime('2022-11-17T16:00:00Z'), `END-UTC`:datetime('2022-11-17T16:20:00Z')}}, {TalkTitle:"Building Java Applications With Quarkus and Neo4j ", properties:{TalkSummary:"In this live-coding session, you will learn how to build modern Java applications powered by Quarkus, using Neo4j as a graph database to persist domain entities.", `START-UTC`:datetime('2022-11-17T10:00:00Z'), `END-UTC`:datetime('2022-11-17T10:35:00Z')}}, {TalkTitle:"Introducing the PHP and Graph Ecosystem", properties:{TalkSummary:"This session will map out the entire ecosystem to show you how to get started with PHP and Neo4j. Join us to build your application now with one of the most stable and commonly-used web development languages and the world's leading graph database!", `START-UTC`:datetime('2022-11-17T10:40:00Z'), `END-UTC`:datetime('2022-11-17T11:15:00Z')}}, {TalkTitle:"Introduction to Neo4j Plugins ", properties:{TalkSummary:"This talk will give an introduction to Neo4j plugins and how they work. What APIs are available? How can I implement triggers? What are available templates to start from for my own plugin? How do plugins interact with the core database?", `START-UTC`:datetime('2022-11-17T11:20:00Z'), `END-UTC`:datetime('2022-11-17T11:35:00Z')}}, {TalkTitle:"Aura Enterprise is Coming to Azure Cloud - Find Out What We've Been Up To! ", properties:{TalkSummary:"Join our Aura Product Managers and find out about our latest adventure. Neo4j’s enterprise-ready cloud DBaaS offering, Aura, fully managed, in your cloud of choice.", `START-UTC`:datetime('2022-11-17T11:40:00Z'), `END-UTC`:datetime('2022-11-17T11:55:00Z')}}, {TalkTitle:"Hidden in the Clouds: Using Graph Technology to Understand Your Cloud Estate ", properties:{TalkSummary:"The Financial Times turned to graph technologies – Neo4j and GraphQL – to build a user-friendly picture of multiple AWS accounts. This is helping keep their data more secure, saving them money, improving engineering efficiency, and providing instant insights that would previously have taken hours or days of research.", `START-UTC`:datetime('2022-11-17T12:00:00Z'), `END-UTC`:datetime('2022-11-17T12:35:00Z')}}, {TalkTitle:"The HealthECCO Knowledge Graph: Applying Neo4j Technologies in Health Data Research ", properties:{TalkSummary:"The focus of this talk will be on introducing the main code repositories included in the HealthECCO graph, explaining the workflow behind the data loading pipeline, and showcasing the use of Neo4j for health data exploration. Whenever a new data source should be added, the pipeline can be modified to integrate the (fully annotated) dataset.", `START-UTC`:datetime('2022-11-17T12:40:00Z'), `END-UTC`:datetime('2022-11-17T13:15:00Z')}}, {TalkTitle:"Farm Topologies and Time-Series Data ", properties:{TalkSummary:"Monitoring farms and barns is a tedious task. No farm looks like another. Water distribution, next to other elements, has grown generically. A little bit like the good old legacy systems we all love. With the additional complication of keeping track of topology changes, typical building automation systems go out of scope.\nIn this session, you'll learn how clevabit is integrated with Neo4j, PostgreSQL, and TimescaleDB to bring observability to farms and lessons Chris Engelbert learned along the way. And there were a lot of “this time it works” moments.", `START-UTC`:datetime('2022-11-17T13:20:00Z'), `END-UTC`:datetime('2022-11-17T13:55:00Z')}}, {TalkTitle:"What's New in Neo4j Java Driver Version 5.0 ", properties:{TalkSummary:"This session discusses new features in the Neo4j Java Driver version 5.0. We'll cover the upgrade to the JDK 17 baseline, the introduction of Java Module (Jigsaw), and other improvements specific to the driver itself, including a new reactive API and its use of the Flow API.", `START-UTC`:datetime('2022-11-17T14:00:00Z'), `END-UTC`:datetime('2022-11-17T14:15:00Z')}}, {TalkTitle:"Introduction to the Async Python Driver ", properties:{TalkSummary:"In this session, we'll dive into how to turn a sync Python application using the official Neo4j driver into an async one as well as some common pitfalls when writing async Python code and how that relates to the usage of our driver.", `START-UTC`:datetime('2022-11-17T14:20:00Z'), `END-UTC`:datetime('2022-11-17T14:35:00Z')}}, {TalkTitle:"Neo4j Migrations: The Lean Way of Applying Database Refactorings to Neo4j ", properties:{TalkSummary:"Neo4j-Migrations gives you an easy way to apply schema changes to Neo4j. Unlike Liquibase, It is almost dependency free and runs right on the Neo4j Java Driver, with no need to work with JDBC. Neo4j-Migrations integrates Spring Data Neo4j with JHipster and has been in production since summer 2020. Come to this session to learn how you can put Neo4j-Migrations to work for you.", `START-UTC`:datetime('2022-11-17T14:40:00Z'), `END-UTC`:datetime('2022-11-17T15:15:00Z')}}, {TalkTitle:"Building a Visual Rail Planner with NeoDash", properties:{TalkSummary:"NeoDash is an open-source dashboard builder for Neo4j. As part of Neo4j Labs, you can use NeoDash for free in Neo4j Desktop to render force-directed graphs, tables, bar charts, line charts, and more.", `START-UTC`:datetime('2022-11-17T15:20:00Z'), `END-UTC`:datetime('2022-11-17T15:55:00Z')}}, {TalkTitle:"XRP Ledger Blockchain ETL With Neo4j ", properties:{TalkSummary:"This talk showcases how the database, that is kept in sync with the XRP Ledger (+/- 10 seconds), is used in the fight against criminal finances by “following the money,” and how it is used to stay ahead of money laundering when criminals move funds quickly around prior to moving it to legitimate exchanges.", `START-UTC`:datetime('2022-11-17T10:00:00Z'), `END-UTC`:datetime('2022-11-17T10:35:00Z')}}] AS row |
|
CREATE (n:Talk{TalkTitle: row.TalkTitle}) SET n += row.properties; |
|
UNWIND [{TalkTitle:"Neo4j With Docker and Docker Compose Deep Dive ", properties:{TalkSummary:"This session will go over using Neo4j with Docker and Docker compose, presenting tips and tricks on basic usage, an explanation of the Docker image itself, backups and restore and building custom images extending the official Neo4j image.", `START-UTC`:datetime('2022-11-17T10:40:00Z'), `END-UTC`:datetime('2022-11-17T11:15:00Z')}}, {TalkTitle:"User Change Modeling in Graph Applications ", properties:{TalkSummary:"How do you model user changes?\nIn SQL, you'd probably create a new table with a composite primary key to show the changes a user (pk 1) has done to which entity (pk2), and what those changes are. However, in a graph database, you have plenty of options for doing this, all of which have pros and cons in terms of database setup, code complexity, and query performance. In this talk, we'll lay out the problem setup and discuss the advantages and disadvantages of different modeling options.", `START-UTC`:datetime('2022-11-17T11:20:00Z'), `END-UTC`:datetime('2022-11-17T11:55:00Z')}}, {TalkTitle:"Building a Neo4j/Python OGM ", properties:{TalkSummary:"Leverage Cypher map projections and Python dynamic typing to build an Object Graph Mapper for Neo4j. In this step-by-step session, you'll learn how to get started on such a project, from defining the framework API to automatically building Cypher queries.", `START-UTC`:datetime('2022-11-17T12:00:00Z'), `END-UTC`:datetime('2022-11-17T12:35:00Z')}}, {TalkTitle:"Neo4j 5 Foundations for Scale", properties:{TalkSummary:"This session describes two new features in Neo4j 5: Autonomous Clusters and Composite databases.\nTogether, these features can be used to scale several large databases elastically across multiple machines, then create combined aliases where those databases can be queried together.", `START-UTC`:datetime('2022-11-17T12:40:00Z'), `END-UTC`:datetime('2022-11-17T13:15:00Z')}}, {TalkTitle:"Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge Graphs", properties:{TalkSummary:" In this session, we show how the semantic similarity based on transformer embeddings and agglomerative clustering can help in the domain of academic disciplines and research fields and how Neo4j improves the browsing experience of this knowledge graph.", `START-UTC`:datetime('2022-11-17T13:20:00Z'), `END-UTC`:datetime('2022-11-17T13:55:00Z')}}, {TalkTitle:"From Node to Knowledge Graph Embeddings ", properties:{TalkSummary:"", `START-UTC`:datetime('2022-11-17T14:00:00Z'), `END-UTC`:datetime('2022-11-17T14:35:00Z')}}, {TalkTitle:"ML Innovation: More Accuracy in Predictive Models Thanks to Graph Embeddings ", properties:{TalkSummary:"In this session, you'll see a demonstration of this on the CORA dataset of scientific publications, well known in the data science ecosystem; Neo4j and graph embeddings increase several points of accuracy to predict the category of any given research paper.", `START-UTC`:datetime('2022-11-17T14:40:00Z'), `END-UTC`:datetime('2022-11-17T15:15:00Z')}}, {TalkTitle:"Native Graph Algorithms in Rust ", properties:{TalkSummary:"In our talk, we will include demos for how to use the library as a Rust and Python developer, both locally and also via Apache Arrow.", `START-UTC`:datetime('2022-11-17T15:20:00Z'), `END-UTC`:datetime('2022-11-17T15:55:00Z')}}] AS row |
|
CREATE (n:Talk{TalkTitle: row.TalkTitle}) SET n += row.properties; |
|
UNWIND [{SpeakerName:"Michael Hunger", properties:{SpeakerTitle:"NODES Chairman"}}, {SpeakerName:"Nicholas Christakis", properties:{SpeakerTitle:"Social Scientist and Physician at Yale University "}}, {SpeakerName:"Stu Moore", properties:{SpeakerTitle:"Product Manager at Neo4j"}}, {SpeakerName:"Gregory King", properties:{SpeakerTitle:"Product Manager for Developer Tools at Neo4j"}}, {SpeakerName:"Anton Persson", properties:{SpeakerTitle:"Software Engineer on Kernel Team at Neo4j, Mindfulness teacher"}}, {SpeakerName:"Mark Needham", properties:{SpeakerTitle:"Developer Advocate at StarTree"}}, {SpeakerName:"Michael Bandor", properties:{SpeakerTitle:"Senior Software Engineer, Software Engineering Institute (SEI), Carnegie Mellon University"}}, {SpeakerName:"Jennifer Reif", properties:{SpeakerTitle:"Developer Advocate at Neo4j"}}, {SpeakerName:"Zach Probst", properties:{SpeakerTitle:"Senior Software Engineer at Intuit"}}, {SpeakerName:"Ward Cunningham", properties:{SpeakerTitle:"Creator of Wiki and the Federated Implementation"}}, {SpeakerName:"Kateryna Nesvit", properties:{SpeakerTitle:"Visiting Professor in Data Science, College of Business, Innovation, Leadership, and Technology at Marymount University"}}, {SpeakerName:"Mark Heckler", properties:{SpeakerTitle:"Principal Cloud Advocate, Java/JVM Languages at Microsoft"}}, {SpeakerName:"Jason Koo", properties:{SpeakerTitle:"Developer Advocate at Neo4j"}}, {SpeakerName:"Emil Eifrem", properties:{SpeakerTitle:"CEO, Neo4j"}}, {SpeakerName:"Andreas Kollegger", properties:{SpeakerTitle:"Community Ambassador, Neo4j"}}, {SpeakerName:"Siraj Munir", properties:{SpeakerTitle:"Data Scientist, AI Researcher, and Ph.D. Candidate"}}, {SpeakerName:"Sefik Serengil", properties:{SpeakerTitle:"Software Engineer at Vorboss"}}, {SpeakerName:"Donovan Bergin", properties:{SpeakerTitle:"Expert Software Engineer at JB Hunt"}}, {SpeakerName:"Michal Štefaňák", properties:{SpeakerTitle:"Software Developer and Technologies Specialist "}}, {SpeakerName:"Filippo Minutella", properties:{SpeakerTitle:"Chapter Lead of AI at Larus Business Automation"}}] AS row |
|
CREATE (n:Speaker{SpeakerName: row.SpeakerName}) SET n += row.properties; |
|
UNWIND [{SpeakerName:"Valerio Piccioni", properties:{SpeakerTitle:"AI Engineer at Larus Business Automation"}}, {SpeakerName:"Corey Lanum", properties:{SpeakerTitle:"US Country Director, Cambridge Intelligence"}}, {SpeakerName:"Owen Brierley", properties:{SpeakerTitle:"Game Design Researcher and PhD Candidate in Computational Media Design at the University of Calgary"}}, {SpeakerName:"Max Andersson", properties:{SpeakerTitle:"Developer Advocate, Neo4j"}}, {SpeakerName:"Samuel Chalvet", properties:{SpeakerTitle:"Graphable - Senior Consultant"}}, {SpeakerName:"Jeff Gagnon", properties:{SpeakerTitle:"Product Manager at Neo4j"}}, {SpeakerName:"Anuj Agrawal", properties:{SpeakerTitle:"Founder and Engineer at Pointshop"}}, {SpeakerName:"Mark Quinsland", properties:{SpeakerTitle:"Senior Field Engineer, Neo4j"}}, {SpeakerName:"David Tyler", properties:{SpeakerTitle:"Associate Professor, University of Massachusetts Amherst, USA"}}, {SpeakerName:"Joe Cobbs", properties:{SpeakerTitle:"Professor, Northern Kentucky University, USA"}}, {SpeakerName:"Nadja Müller", properties:{SpeakerTitle:"Team Lead of Cypher Surface, Neo4j"}}, {SpeakerName:"Petra Selmer", properties:{SpeakerTitle:"Team Lead of the Query Languages Standards & Research Group, Neo4j"}}, {SpeakerName:"Adam Schill Collberg", properties:{SpeakerTitle:"Senior Software Engineer at Neo4j"}}, {SpeakerName:"Chris Shelmerdine", properties:{SpeakerTitle:"Product Manager at Neo4j"}}, {SpeakerName:"Vlasta Kůs", properties:{SpeakerTitle:"Lead Data Scientist at GraphAware, Dr. Who fan"}}, {SpeakerName:"Mike Morley", properties:{SpeakerTitle:"Director of Machine Learning and Artificial Intelligence Technology, Arcurve Inc."}}, {SpeakerName:"Pete Tunkis", properties:{SpeakerTitle:"Lead Data Scientist at Arcurve Inc."}}, {SpeakerName:"William Lyon", properties:{SpeakerTitle:"Developer Relations Engineer at Neo4j"}}, {SpeakerName:"Anthony Krinsky", properties:{SpeakerTitle:"Developer and Advocate at Neo4j"}}, {SpeakerName:"Ashleigh Faith", properties:{SpeakerTitle:"Founder of the IsA DataThing YouTube Channel"}}] AS row |
|
CREATE (n:Speaker{SpeakerName: row.SpeakerName}) SET n += row.properties; |
|
UNWIND [{SpeakerName:"Ana Areias", properties:{SpeakerTitle:"Data Scientist at Kineviz"}}, {SpeakerName:"Mengjia Kang", properties:{SpeakerTitle:"Clinical Research Associate, Data Science at Northwestern University"}}, {SpeakerName:"John Stegeman", properties:{SpeakerTitle:"Sr. Manager, Graph Database Product Specialist at Neo4j"}}, {SpeakerName:"Shiny Zhu", properties:{SpeakerTitle:"Developer Advocate at Neo4j"}}, {SpeakerName:"Vlad Batushkov", properties:{SpeakerTitle:"Software Engineering Manager at Agoda"}}, {SpeakerName:"Adrien Sales", properties:{SpeakerTitle:"Chef de Bureau/Division Manager at OPT New Caledonia"}}, {SpeakerName:"Koji Annoura", properties:{SpeakerTitle:"Neo4j Ninja, CTO at UTI, Inc. "}}, {SpeakerName:"Mananai Saengsuwan", properties:{SpeakerTitle:"Software Developer and Data Science Enthusiast"}}, {SpeakerName:"Zihao Zhang", properties:{SpeakerTitle:"Student at Tongji University"}}, {SpeakerName:"Jan Zak", properties:{SpeakerTitle:"Senior Software Engineer at MANTA"}}, {SpeakerName:"David Bucek", properties:{SpeakerTitle:"Team Leader of Architecture"}}, {SpeakerName:"Pierre Halftermeyer", properties:{SpeakerTitle:"PreSales Engineer at Neo4j"}}, {SpeakerName:"Andrea Santurbano", properties:{SpeakerTitle:"CTO at LARUS Business Automation"}}, {SpeakerName:"Dr. Julian Gruemmer", properties:{SpeakerTitle:"Research Associate at Friedrich-Alexander-University"}}, {SpeakerName:"Chris Anthes", properties:{SpeakerTitle:"Founder and CEO/CTO at Hapnyn"}}, {SpeakerName:"David Hughes", properties:{SpeakerTitle:"Principal Graph Consultant - Graphable.ai"}}, {SpeakerName:"Emil Pastor", properties:{SpeakerTitle:"Solution Architect at Neo4j"}}, {SpeakerName:"Ajmal Aziz", properties:{SpeakerTitle:"Senior Solutions Engineer at Databricks"}}, {SpeakerName:"胜海 邱", properties:{SpeakerTitle:"Associate Professor at Nanjing Institute of Technology"}}, {SpeakerName:"Smita Padhy", properties:{SpeakerTitle:"Senior Manager, Cloud Data Architect, and Graph Practice Lead at Accenture "}}] AS row |
|
CREATE (n:Speaker{SpeakerName: row.SpeakerName}) SET n += row.properties; |
|
UNWIND [{SpeakerName:"Gerrit Meier", properties:{SpeakerTitle:"Software Engineer at Neo4j"}}, {SpeakerName:"Florent Biville", properties:{SpeakerTitle:"Developer at Neo4j"}}, {SpeakerName:"Marouane Gazanayi", properties:{SpeakerTitle:"Field engineer @Neo4j"}}, {SpeakerName:"Sebastian Müller", properties:{SpeakerTitle:"CTO of yWorks and Architect of yFiles, the Diagramming Library"}}, {SpeakerName:"Dekel Paz", properties:{SpeakerTitle:"Senior Security Researcher at Zero Networks"}}, {SpeakerName:"Dinesh Venkatesan", properties:{SpeakerTitle:"Principal Security Researcher at Microsoft"}}, {SpeakerName:"Sixing Huang", properties:{SpeakerTitle:"Bioinformatic Research Scientist at BGI Group"}}, {SpeakerName:"Payel Bhunia", properties:{SpeakerTitle:"Senior Software Engineer at ZF Group"}}, {SpeakerName:"Nur Aini Rakhmawati", properties:{SpeakerTitle:"Deputy head of Halal Centre and associate professor of Information systems Department, Institut Teknologi Sepuluh Nopember Surabaya "}}, {SpeakerName:"Joinal Ahmed", properties:{SpeakerTitle:"Data Science Advocacy and Strategy at Google"}}, {SpeakerName:"Chaitra Ravada", properties:{SpeakerTitle:"Machine Learning Engineer at Twitter"}}, {SpeakerName:"Sotiris Ouzounis", properties:{SpeakerTitle:"Ph.D. Candidate at Institute of Chemical Biology, National Hellenic Research Foundation"}}, {SpeakerName:"Alexandros Kanterakis", properties:{SpeakerTitle:"Researcher at Computational BioMedicine Laboratory (CBML) of ICS/FORTH"}}, {SpeakerName:"Vasilis Panagiotopoulos", properties:{SpeakerTitle:"Ph.D. Candidate at University of West Attica and Research Scientist at Cloudpharm PC"}}, {SpeakerName:"Wenjie Chen", properties:{SpeakerTitle:"Documentation and Information Center, Chinese Academy of Chengdu"}}, {SpeakerName:"Gal Engelberg", properties:{SpeakerTitle:"Applied Research Team Lead at Accenture Israel Cyber R&D Lab"}}, {SpeakerName:"Ben Vozza", properties:{SpeakerTitle:"CTO at Crossr"}}, {SpeakerName:"Adam Turner", properties:{SpeakerTitle:"Macquarie University PhD student"}}, {SpeakerName:"Abdul Wahid", properties:{SpeakerTitle:"PhD Researcher, Data Science Institute, National University of Ireland"}}, {SpeakerName:"Mats Rydberg", properties:{SpeakerTitle:"Engineering Team Lead for Graph Data Science"}}] AS row |
|
CREATE (n:Speaker{SpeakerName: row.SpeakerName}) SET n += row.properties; |
|
UNWIND [{SpeakerName:"Luke Gannon", properties:{SpeakerTitle:"Product Manager at Neo4j"}}, {SpeakerName:"Florentin Dörre", properties:{SpeakerTitle:"Graph Data Science Engineer at Neo4j"}}, {SpeakerName:"Darrell Warde", properties:{SpeakerTitle:"Senior Software Engineer and GraphQL Team Lead at Neo4j"}}, {SpeakerName:"Roei Levi", properties:{SpeakerTitle:"Software Engineer at Accenture Cyber R&D Labs"}}, {SpeakerName:"James Bowkett", properties:{SpeakerTitle:"Technical Delivery Director at OpenCredo"}}, {SpeakerName:"Véronique Gendner", properties:{SpeakerTitle:"Information Design and Data Processing"}}, {SpeakerName:"Nicolas Mervaillie", properties:{SpeakerTitle:"Senior Consultant at Neo4j"}}, {SpeakerName:"Alfredo Rubin", properties:{SpeakerTitle:"Consulting Engineer at Neo4j"}}, {SpeakerName:"Rik Van Bruggen", properties:{SpeakerTitle:"Regional Vice President at Neo4j"}}, {SpeakerName:"Fabio Montagna", properties:{SpeakerTitle:"Lead Machine Learning Engineer at GraphAware"}}, {SpeakerName:"Sascha Peukert", properties:{SpeakerTitle:"Software Engineer at Neo4j"}}, {SpeakerName:"Sebastian Daschner", properties:{SpeakerTitle:"Java Champion and Consultant"}}, {SpeakerName:"Ghlen Nagels", properties:{SpeakerTitle:"Web Developer & Graph Database Consultant"}}, {SpeakerName:"Bert Radke", properties:{SpeakerTitle:"Senior Field Engineer at Neo4j"}}, {SpeakerName:"Paul Blewett", properties:{SpeakerTitle:"Enterprise Product Manager, Cloud at Neo4j"}}, {SpeakerName:"Rhys Evans", properties:{SpeakerTitle:"Principal Engineer at the Financial Times"}}, {SpeakerName:"Lea Gütebier", properties:{SpeakerTitle:"Researcher at University Medicine Greifswald"}}, {SpeakerName:"Ron Henkel", properties:{SpeakerTitle:"Researcher at Medical Informatics Department of University Medicine Greifswald"}}, {SpeakerName:"Dagmar Waltemath", properties:{SpeakerTitle:"Professor of Medical Informatics at University Medicine Greifswald"}}, {SpeakerName:"Chris Engelbert", properties:{SpeakerTitle:"Senior Developer Advocate at TimescaleDB"}}] AS row |
|
CREATE (n:Speaker{SpeakerName: row.SpeakerName}) SET n += row.properties; |
|
UNWIND [{SpeakerName:"Dmitriy Tverdiakov", properties:{SpeakerTitle:"Software Engineer"}}, {SpeakerName:"Rouven Bauer", properties:{SpeakerTitle:"Python Driver Author at Neo4j"}}, {SpeakerName:"Michael Simons", properties:{SpeakerTitle:"Software Engineer at Neo4j"}}, {SpeakerName:"Niels De Jong", properties:{SpeakerTitle:"Consulting Engineer at Neo4j"}}, {SpeakerName:"Thomas Silkjaer", properties:{SpeakerTitle:"Head of Analytics and Compliance at XRP Ledger Foundataio"}}, {SpeakerName:"Christophe Willemsen", properties:{SpeakerTitle:"CTO at GraphAware"}}, {SpeakerName:"Elena Kohlwey", properties:{SpeakerTitle:"Specialist Digital Engineering at RLE International"}}, {SpeakerName:"Estelle Scifo", properties:{SpeakerTitle:"Data Scientist & CTO of SmartGrid Communications Inc."}}, {SpeakerName:"Hugo Firth", properties:{SpeakerTitle:"Cluster Wrangler at Neo4j"}}, {SpeakerName:"Tobias Johansson", properties:{SpeakerTitle:"Cypher Engineer at Neo4j"}}, {SpeakerName:"Federica Ventruto", properties:{SpeakerTitle:"Data Scientist at GraphAware"}}, {SpeakerName:"Alessia Melania Lonoce", properties:{SpeakerTitle:"Data Scientist at GraphAware"}}, {SpeakerName:"Tomaz Bratanic", properties:{SpeakerTitle:"Graph Data Analyst"}}, {SpeakerName:"Nicolas Rouyer", properties:{SpeakerTitle:"Senior Pre-Sales Engineer at Neo4j"}}, {SpeakerName:"Martin Junghanns", properties:{SpeakerTitle:"Senior Software Engineer"}}, {SpeakerName:"Paul Horn", properties:{SpeakerTitle:"Software Engineer, Graph Data Science at Neo4j"}}] AS row |
|
CREATE (n:Speaker{SpeakerName: row.SpeakerName}) SET n += row.properties; |
|
UNWIND [{start: {TalkTitle:"Welcome to NODES 2022 - AMER"}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Keynote: Social Network Interventions "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Introducing Neo4j 5 for Administrators "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Bootstrapping Your Graph Project With Neo4j Workspace "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"A Space to Relax: Guided Meditation (AMER) "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Graph Modeling: The Shadow Graph "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Graph Database Techniques to Reduce Risk and Innovate "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Divide and Conquer: Send Forth the Microservices "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Security and Velocity Through Declarative Ingestion "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Hypertext Super Collaborator "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Discover Invisible Patterns in Your Data: Connect Google Sheets Tables and Neo4j "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Let's Get Functional! Pull Off a Trifecta With Spring Cloud Function, Azure Functions, and Neo4j "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Graph Databases for Python Developers "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Closing Q&A With Emil and Andreas: AMERICAS "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Modeling NFT Tweets as a Knowledge Graph Using Neo4j "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"DeepFace Recognition With Neo4j "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"IAC: SchemaSmith for Data Governance at JB Hunt "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"PHP Devs, Change Your Life "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Fashion Retail Recommendations Using Neo4j Graph Data Science and Apache Arrow "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Demystifying Graph Analytics With Visualization "}, end: {Track:"Intermediate"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Track{Track: row.end.Track}) |
|
CREATE (start)-[r:IN_TRACK]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"Towards Real-time Knowledge Graphs for Non-Player Characters in Games "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"GraphQL Quickstart With the Neo4j GraphQL Library "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Quick Deploy GraphQL API With SST "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Exploring Data With Neo4j Bloom "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Graph Data Science for Computer Vision"}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Top 10 Tips for Evaluating “Benchmark” Results "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Using Sport Data to Build a Graph Model of Inconsistent Hierarchies Over Time "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Graph Pattern Matching "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"GNNs at Scale With Graph Data Science Sampling and Python Client Integration "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Neo4j Ops Manager: Intro and Roadmap "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Data Management with Knowledge Graphs: Bringing Archives to Life "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Arcurve Skills and Staffing Recommender "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Making Sense of Geospatial Data With Knowledge Graphs "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Neo4j Data Loading (ETL/ELT) Best Practices"}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Are Personal Knowledge Graphs the Next Big Thing for Search? "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Graph Algorithms and Visualization for Clinical Care Support of Pneumonia "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Welcome to NODES 2022 - APAC"}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Workspace in AuraDB "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Easy On-Ramp to Using Graphs "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Exploring the Relationships Between People in the Ancient Chinese Novel, \"Three Kingdoms\" "}, end: {Track:"Beginner"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Track{Track: row.end.Track}) |
|
CREATE (start)-[r:IN_TRACK]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"Creating Graphville: A Neo4j Educational Platform "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Learn Neo4j in Chinese With Neo4j GraphAcademy"}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"From Game of Thrones to Information System Cartography "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Coffee Knowledge Graph "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Analyzing Spammers in Twitter User Network "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Neo4j Lectures of the Stanford CS224W Course "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Track Data Lineage With a Graph Database "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"A Space to Relax: Guided Meditation (APAC) "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Playing With State Machines "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"cy2py: Seamless Neo4j Integration in Python Notebooks "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"ESG Supply Chain Knowledge Graph "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Using Graph Databases for Consumer Products "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Rapid App Prototyping Using Streamlit and Neo4j "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Managing Software-BOM, Security Issues, and Their Knowledge Graphs Is Easy With Neo4j "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Connected Data Lakehouse: Neo4j and Databricks Reference Data Architecture "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Construction and Application of Knowledge Graphs: Manufacturing Process for Box Parts "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Knowledge Graphs Powering Active Metadata "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Better Testing With Testcontainers "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Liquibase & Neo4j: The Migration Sweet Deal "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Explore Your Graphs Visually With Jupyter Notebooks "}, end: {Track:"Intermediate"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Track{Track: row.end.Track}) |
|
CREATE (start)-[r:IN_TRACK]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"BlueHound: Community-Driven Security Based on Neo4j and NeoDash "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"The Heisenbugs - Finding Collusion Among Malicious Entities Through Knowledge Graph "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Doctor.ai: A Graph-Based Medical Chatbot "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Running Neo4j in Docker and Deploying Neo4j Application in OpenShift "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Knowledge Graphs and Machine Learning for Halal Food Product Recommendations "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Take Data to the Next Level With Graph Machine Learning "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"CloudScreen: A Graph-Based Drug Repurposing Platform Empowered by Machine Learning "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Generating a Hematopoietic Stem Cell Knowledge Graph for Scientific Knowledge Discovery "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Taking Application Security Insights to the Next Level With Fabric and NeoSemantics "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Graph-Based Features for Recommendation Systems in Drug Discovery "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Using Graph Embeddings for Suspicious Bitcoin Transactions "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Knowledge Graphs in Time-Series Data "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Fundamentals of Neo4j Graph Data Science Series 2.x – Pipelines and More "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Welcome to NODES 2022 - EMEA"}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"What's New in Neo4j 5 and Aura 5 for Developers "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Index Changes in Neo4j 5 "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"What's New in Graph Data Science Land "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Link Prediction With Graph Data Science at Scale "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"GraphQL Federation and Key Neo4j GraphQL Library Features"}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Cymple: Cypher Modular Pythonic Language Extension "}, end: {Track:"Beginner"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Track{Track: row.end.Track}) |
|
CREATE (start)-[r:IN_TRACK]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"A Space to Relax: Guided Meditation (EMEA) "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Tracing Your Data's DNA "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Genealogy With Different Graph Technologies for Data Collection and Visualization "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"RDBMS to Neo4j Real Time Data Sync with Debezium and Kafka "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"A Developer's Guide to Building a Graph Project Value Case "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Temporal Graph Analysis "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Building Neo4j Ops Manager: Lessons From Dogfooding "}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Closing Q&A With Emil and Andreas: EMEA"}, end: {Track:"Beginner"}, properties:{}}, {start: {TalkTitle:"Building Java Applications With Quarkus and Neo4j "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Introducing the PHP and Graph Ecosystem"}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Introduction to Neo4j Plugins "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Aura Enterprise is Coming to Azure Cloud - Find Out What We've Been Up To! "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Hidden in the Clouds: Using Graph Technology to Understand Your Cloud Estate "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"The HealthECCO Knowledge Graph: Applying Neo4j Technologies in Health Data Research "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Farm Topologies and Time-Series Data "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"What's New in Neo4j Java Driver Version 5.0 "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Introduction to the Async Python Driver "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Neo4j Migrations: The Lean Way of Applying Database Refactorings to Neo4j "}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"Building a Visual Rail Planner with NeoDash"}, end: {Track:"Intermediate"}, properties:{}}, {start: {TalkTitle:"XRP Ledger Blockchain ETL With Neo4j "}, end: {Track:"Advanced"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Track{Track: row.end.Track}) |
|
CREATE (start)-[r:IN_TRACK]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"Neo4j With Docker and Docker Compose Deep Dive "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"User Change Modeling in Graph Applications "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Building a Neo4j/Python OGM "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Neo4j 5 Foundations for Scale"}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge Graphs"}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"From Node to Knowledge Graph Embeddings "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"ML Innovation: More Accuracy in Predictive Models Thanks to Graph Embeddings "}, end: {Track:"Advanced"}, properties:{}}, {start: {TalkTitle:"Native Graph Algorithms in Rust "}, end: {Track:"Advanced"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Track{Track: row.end.Track}) |
|
CREATE (start)-[r:IN_TRACK]->(end) SET r += row.properties; |
|
UNWIND [{start: {SpeakerName:"Michael Hunger"}, end: {TalkTitle:"Welcome to NODES 2022 - AMER"}, properties:{}}, {start: {SpeakerName:"Nicholas Christakis"}, end: {TalkTitle:"Keynote: Social Network Interventions "}, properties:{}}, {start: {SpeakerName:"Stu Moore"}, end: {TalkTitle:"Introducing Neo4j 5 for Administrators "}, properties:{}}, {start: {SpeakerName:"Gregory King"}, end: {TalkTitle:"Bootstrapping Your Graph Project With Neo4j Workspace "}, properties:{}}, {start: {SpeakerName:"Anton Persson"}, end: {TalkTitle:"A Space to Relax: Guided Meditation (AMER) "}, properties:{}}, {start: {SpeakerName:"Mark Needham"}, end: {TalkTitle:"Graph Modeling: The Shadow Graph "}, properties:{}}, {start: {SpeakerName:"Michael Bandor"}, end: {TalkTitle:"Graph Database Techniques to Reduce Risk and Innovate "}, properties:{}}, {start: {SpeakerName:"Jennifer Reif"}, end: {TalkTitle:"Divide and Conquer: Send Forth the Microservices "}, properties:{}}, {start: {SpeakerName:"Zach Probst"}, end: {TalkTitle:"Security and Velocity Through Declarative Ingestion "}, properties:{}}, {start: {SpeakerName:"Ward Cunningham"}, end: {TalkTitle:"Hypertext Super Collaborator "}, properties:{}}, {start: {SpeakerName:"Kateryna Nesvit"}, end: {TalkTitle:"Discover Invisible Patterns in Your Data: Connect Google Sheets Tables and Neo4j "}, properties:{}}, {start: {SpeakerName:"Mark Heckler"}, end: {TalkTitle:"Let's Get Functional! Pull Off a Trifecta With Spring Cloud Function, Azure Functions, and Neo4j "}, properties:{}}, {start: {SpeakerName:"Jason Koo"}, end: {TalkTitle:"Graph Databases for Python Developers "}, properties:{}}, {start: {SpeakerName:"Emil Eifrem"}, end: {TalkTitle:"Closing Q&A With Emil and Andreas: AMERICAS "}, properties:{}}, {start: {SpeakerName:"Andreas Kollegger"}, end: {TalkTitle:"Closing Q&A With Emil and Andreas: AMERICAS "}, properties:{}}, {start: {SpeakerName:"Siraj Munir"}, end: {TalkTitle:"Modeling NFT Tweets as a Knowledge Graph Using Neo4j "}, properties:{}}, {start: {SpeakerName:"Sefik Serengil"}, end: {TalkTitle:"DeepFace Recognition With Neo4j "}, properties:{}}, {start: {SpeakerName:"Donovan Bergin"}, end: {TalkTitle:"IAC: SchemaSmith for Data Governance at JB Hunt "}, properties:{}}, {start: {SpeakerName:"Michal Štefaňák"}, end: {TalkTitle:"PHP Devs, Change Your Life "}, properties:{}}, {start: {SpeakerName:"Filippo Minutella"}, end: {TalkTitle:"Fashion Retail Recommendations Using Neo4j Graph Data Science and Apache Arrow "}, properties:{}}] AS row |
|
MATCH (start:Speaker{SpeakerName: row.start.SpeakerName}) |
|
MATCH (end:Talk{TalkTitle: row.end.TalkTitle}) |
|
CREATE (start)-[r:DELIVERS_TALK]->(end) SET r += row.properties; |
|
UNWIND [{start: {SpeakerName:"Valerio Piccioni"}, end: {TalkTitle:"Fashion Retail Recommendations Using Neo4j Graph Data Science and Apache Arrow "}, properties:{}}, {start: {SpeakerName:"Corey Lanum"}, end: {TalkTitle:"Demystifying Graph Analytics With Visualization "}, properties:{}}, {start: {SpeakerName:"Owen Brierley"}, end: {TalkTitle:"Towards Real-time Knowledge Graphs for Non-Player Characters in Games "}, properties:{}}, {start: {SpeakerName:"Max Andersson"}, end: {TalkTitle:"GraphQL Quickstart With the Neo4j GraphQL Library "}, properties:{}}, {start: {SpeakerName:"Samuel Chalvet"}, end: {TalkTitle:"Quick Deploy GraphQL API With SST "}, properties:{}}, {start: {SpeakerName:"Jeff Gagnon"}, end: {TalkTitle:"Exploring Data With Neo4j Bloom "}, properties:{}}, {start: {SpeakerName:"Anuj Agrawal"}, end: {TalkTitle:"Graph Data Science for Computer Vision"}, properties:{}}, {start: {SpeakerName:"Mark Quinsland"}, end: {TalkTitle:"Top 10 Tips for Evaluating “Benchmark” Results "}, properties:{}}, {start: {SpeakerName:"David Tyler"}, end: {TalkTitle:"Using Sport Data to Build a Graph Model of Inconsistent Hierarchies Over Time "}, properties:{}}, {start: {SpeakerName:"Joe Cobbs"}, end: {TalkTitle:"Using Sport Data to Build a Graph Model of Inconsistent Hierarchies Over Time "}, properties:{}}, {start: {SpeakerName:"Nadja Müller"}, end: {TalkTitle:"Graph Pattern Matching "}, properties:{}}, {start: {SpeakerName:"Petra Selmer"}, end: {TalkTitle:"Graph Pattern Matching "}, properties:{}}, {start: {SpeakerName:"Adam Schill Collberg"}, end: {TalkTitle:"GNNs at Scale With Graph Data Science Sampling and Python Client Integration "}, properties:{}}, {start: {SpeakerName:"Chris Shelmerdine"}, end: {TalkTitle:"Neo4j Ops Manager: Intro and Roadmap "}, properties:{}}, {start: {SpeakerName:"Vlasta Kůs"}, end: {TalkTitle:"Data Management with Knowledge Graphs: Bringing Archives to Life "}, properties:{}}, {start: {SpeakerName:"Mike Morley"}, end: {TalkTitle:"Arcurve Skills and Staffing Recommender "}, properties:{}}, {start: {SpeakerName:"Pete Tunkis"}, end: {TalkTitle:"Arcurve Skills and Staffing Recommender "}, properties:{}}, {start: {SpeakerName:"William Lyon"}, end: {TalkTitle:"Making Sense of Geospatial Data With Knowledge Graphs "}, properties:{}}, {start: {SpeakerName:"Anthony Krinsky"}, end: {TalkTitle:"Neo4j Data Loading (ETL/ELT) Best Practices"}, properties:{}}, {start: {SpeakerName:"Ashleigh Faith"}, end: {TalkTitle:"Are Personal Knowledge Graphs the Next Big Thing for Search? "}, properties:{}}] AS row |
|
MATCH (start:Speaker{SpeakerName: row.start.SpeakerName}) |
|
MATCH (end:Talk{TalkTitle: row.end.TalkTitle}) |
|
CREATE (start)-[r:DELIVERS_TALK]->(end) SET r += row.properties; |
|
UNWIND [{start: {SpeakerName:"Ana Areias"}, end: {TalkTitle:"Graph Algorithms and Visualization for Clinical Care Support of Pneumonia "}, properties:{}}, {start: {SpeakerName:"Mengjia Kang"}, end: {TalkTitle:"Graph Algorithms and Visualization for Clinical Care Support of Pneumonia "}, properties:{}}, {start: {SpeakerName:"Michael Hunger"}, end: {TalkTitle:"Welcome to NODES 2022 - APAC"}, properties:{}}, {start: {SpeakerName:"John Stegeman"}, end: {TalkTitle:"Workspace in AuraDB "}, properties:{}}, {start: {SpeakerName:"John Stegeman"}, end: {TalkTitle:"Easy On-Ramp to Using Graphs "}, properties:{}}, {start: {SpeakerName:"Shiny Zhu"}, end: {TalkTitle:"Exploring the Relationships Between People in the Ancient Chinese Novel, \"Three Kingdoms\" "}, properties:{}}, {start: {SpeakerName:"Vlad Batushkov"}, end: {TalkTitle:"Creating Graphville: A Neo4j Educational Platform "}, properties:{}}, {start: {SpeakerName:"Shiny Zhu"}, end: {TalkTitle:"Learn Neo4j in Chinese With Neo4j GraphAcademy"}, properties:{}}, {start: {SpeakerName:"Adrien Sales"}, end: {TalkTitle:"From Game of Thrones to Information System Cartography "}, properties:{}}, {start: {SpeakerName:"Koji Annoura"}, end: {TalkTitle:"Coffee Knowledge Graph "}, properties:{}}, {start: {SpeakerName:"Mananai Saengsuwan"}, end: {TalkTitle:"Analyzing Spammers in Twitter User Network "}, properties:{}}, {start: {SpeakerName:"Zihao Zhang"}, end: {TalkTitle:"Neo4j Lectures of the Stanford CS224W Course "}, properties:{}}, {start: {SpeakerName:"Jan Zak"}, end: {TalkTitle:"Track Data Lineage With a Graph Database "}, properties:{}}, {start: {SpeakerName:"David Bucek"}, end: {TalkTitle:"Track Data Lineage With a Graph Database "}, properties:{}}, {start: {SpeakerName:"Anton Persson"}, end: {TalkTitle:"A Space to Relax: Guided Meditation (APAC) "}, properties:{}}, {start: {SpeakerName:"Pierre Halftermeyer"}, end: {TalkTitle:"Playing With State Machines "}, properties:{}}, {start: {SpeakerName:"Andrea Santurbano"}, end: {TalkTitle:"cy2py: Seamless Neo4j Integration in Python Notebooks "}, properties:{}}, {start: {SpeakerName:"Dr. Julian Gruemmer"}, end: {TalkTitle:"ESG Supply Chain Knowledge Graph "}, properties:{}}, {start: {SpeakerName:"Chris Anthes"}, end: {TalkTitle:"Using Graph Databases for Consumer Products "}, properties:{}}, {start: {SpeakerName:"David Hughes"}, end: {TalkTitle:"Rapid App Prototyping Using Streamlit and Neo4j "}, properties:{}}] AS row |
|
MATCH (start:Speaker{SpeakerName: row.start.SpeakerName}) |
|
MATCH (end:Talk{TalkTitle: row.end.TalkTitle}) |
|
CREATE (start)-[r:DELIVERS_TALK]->(end) SET r += row.properties; |
|
UNWIND [{start: {SpeakerName:"Koji Annoura"}, end: {TalkTitle:"Managing Software-BOM, Security Issues, and Their Knowledge Graphs Is Easy With Neo4j "}, properties:{}}, {start: {SpeakerName:"Emil Pastor"}, end: {TalkTitle:"Connected Data Lakehouse: Neo4j and Databricks Reference Data Architecture "}, properties:{}}, {start: {SpeakerName:"Ajmal Aziz"}, end: {TalkTitle:"Connected Data Lakehouse: Neo4j and Databricks Reference Data Architecture "}, properties:{}}, {start: {SpeakerName:"胜海 邱"}, end: {TalkTitle:"Construction and Application of Knowledge Graphs: Manufacturing Process for Box Parts "}, properties:{}}, {start: {SpeakerName:"Smita Padhy"}, end: {TalkTitle:"Knowledge Graphs Powering Active Metadata "}, properties:{}}, {start: {SpeakerName:"Gerrit Meier"}, end: {TalkTitle:"Better Testing With Testcontainers "}, properties:{}}, {start: {SpeakerName:"Florent Biville"}, end: {TalkTitle:"Liquibase & Neo4j: The Migration Sweet Deal "}, properties:{}}, {start: {SpeakerName:"Marouane Gazanayi"}, end: {TalkTitle:"Liquibase & Neo4j: The Migration Sweet Deal "}, properties:{}}, {start: {SpeakerName:"Sebastian Müller"}, end: {TalkTitle:"Explore Your Graphs Visually With Jupyter Notebooks "}, properties:{}}, {start: {SpeakerName:"Dekel Paz"}, end: {TalkTitle:"BlueHound: Community-Driven Security Based on Neo4j and NeoDash "}, properties:{}}, {start: {SpeakerName:"Dinesh Venkatesan"}, end: {TalkTitle:"The Heisenbugs - Finding Collusion Among Malicious Entities Through Knowledge Graph "}, properties:{}}, {start: {SpeakerName:"Sixing Huang"}, end: {TalkTitle:"Doctor.ai: A Graph-Based Medical Chatbot "}, properties:{}}, {start: {SpeakerName:"Payel Bhunia"}, end: {TalkTitle:"Running Neo4j in Docker and Deploying Neo4j Application in OpenShift "}, properties:{}}, {start: {SpeakerName:"Nur Aini Rakhmawati"}, end: {TalkTitle:"Knowledge Graphs and Machine Learning for Halal Food Product Recommendations "}, properties:{}}, {start: {SpeakerName:"Joinal Ahmed"}, end: {TalkTitle:"Take Data to the Next Level With Graph Machine Learning "}, properties:{}}, {start: {SpeakerName:"Chaitra Ravada"}, end: {TalkTitle:"Take Data to the Next Level With Graph Machine Learning "}, properties:{}}, {start: {SpeakerName:"Sotiris Ouzounis"}, end: {TalkTitle:"CloudScreen: A Graph-Based Drug Repurposing Platform Empowered by Machine Learning "}, properties:{}}, {start: {SpeakerName:"Alexandros Kanterakis"}, end: {TalkTitle:"CloudScreen: A Graph-Based Drug Repurposing Platform Empowered by Machine Learning "}, properties:{}}, {start: {SpeakerName:"Vasilis Panagiotopoulos"}, end: {TalkTitle:"CloudScreen: A Graph-Based Drug Repurposing Platform Empowered by Machine Learning "}, properties:{}}, {start: {SpeakerName:"Wenjie Chen"}, end: {TalkTitle:"Generating a Hematopoietic Stem Cell Knowledge Graph for Scientific Knowledge Discovery "}, properties:{}}] AS row |
|
MATCH (start:Speaker{SpeakerName: row.start.SpeakerName}) |
|
MATCH (end:Talk{TalkTitle: row.end.TalkTitle}) |
|
CREATE (start)-[r:DELIVERS_TALK]->(end) SET r += row.properties; |
|
UNWIND [{start: {SpeakerName:"Gal Engelberg"}, end: {TalkTitle:"Taking Application Security Insights to the Next Level With Fabric and NeoSemantics "}, properties:{}}, {start: {SpeakerName:"Ben Vozza"}, end: {TalkTitle:"Graph-Based Features for Recommendation Systems in Drug Discovery "}, properties:{}}, {start: {SpeakerName:"Adam Turner"}, end: {TalkTitle:"Using Graph Embeddings for Suspicious Bitcoin Transactions "}, properties:{}}, {start: {SpeakerName:"Abdul Wahid"}, end: {TalkTitle:"Knowledge Graphs in Time-Series Data "}, properties:{}}, {start: {SpeakerName:"Mats Rydberg"}, end: {TalkTitle:"Fundamentals of Neo4j Graph Data Science Series 2.x – Pipelines and More "}, properties:{}}, {start: {SpeakerName:"Michael Hunger"}, end: {TalkTitle:"Welcome to NODES 2022 - EMEA"}, properties:{}}, {start: {SpeakerName:"John Stegeman"}, end: {TalkTitle:"What's New in Neo4j 5 and Aura 5 for Developers "}, properties:{}}, {start: {SpeakerName:"Anton Persson"}, end: {TalkTitle:"Index Changes in Neo4j 5 "}, properties:{}}, {start: {SpeakerName:"Luke Gannon"}, end: {TalkTitle:"What's New in Graph Data Science Land "}, properties:{}}, {start: {SpeakerName:"Florentin Dörre"}, end: {TalkTitle:"Link Prediction With Graph Data Science at Scale "}, properties:{}}, {start: {SpeakerName:"Darrell Warde"}, end: {TalkTitle:"GraphQL Federation and Key Neo4j GraphQL Library Features"}, properties:{}}, {start: {SpeakerName:"Roei Levi"}, end: {TalkTitle:"Cymple: Cypher Modular Pythonic Language Extension "}, properties:{}}, {start: {SpeakerName:"Anton Persson"}, end: {TalkTitle:"A Space to Relax: Guided Meditation (EMEA) "}, properties:{}}, {start: {SpeakerName:"James Bowkett"}, end: {TalkTitle:"Tracing Your Data's DNA "}, properties:{}}, {start: {SpeakerName:"Véronique Gendner"}, end: {TalkTitle:"Genealogy With Different Graph Technologies for Data Collection and Visualization "}, properties:{}}, {start: {SpeakerName:"Nicolas Mervaillie"}, end: {TalkTitle:"RDBMS to Neo4j Real Time Data Sync with Debezium and Kafka "}, properties:{}}, {start: {SpeakerName:"Alfredo Rubin"}, end: {TalkTitle:"RDBMS to Neo4j Real Time Data Sync with Debezium and Kafka "}, properties:{}}, {start: {SpeakerName:"Rik Van Bruggen"}, end: {TalkTitle:"A Developer's Guide to Building a Graph Project Value Case "}, properties:{}}, {start: {SpeakerName:"Fabio Montagna"}, end: {TalkTitle:"Temporal Graph Analysis "}, properties:{}}, {start: {SpeakerName:"Sascha Peukert"}, end: {TalkTitle:"Building Neo4j Ops Manager: Lessons From Dogfooding "}, properties:{}}] AS row |
|
MATCH (start:Speaker{SpeakerName: row.start.SpeakerName}) |
|
MATCH (end:Talk{TalkTitle: row.end.TalkTitle}) |
|
CREATE (start)-[r:DELIVERS_TALK]->(end) SET r += row.properties; |
|
UNWIND [{start: {SpeakerName:"Emil Eifrem"}, end: {TalkTitle:"Closing Q&A With Emil and Andreas: EMEA"}, properties:{}}, {start: {SpeakerName:"Andreas Kollegger"}, end: {TalkTitle:"Closing Q&A With Emil and Andreas: EMEA"}, properties:{}}, {start: {SpeakerName:"Sebastian Daschner"}, end: {TalkTitle:"Building Java Applications With Quarkus and Neo4j "}, properties:{}}, {start: {SpeakerName:"Ghlen Nagels"}, end: {TalkTitle:"Introducing the PHP and Graph Ecosystem"}, properties:{}}, {start: {SpeakerName:"Bert Radke"}, end: {TalkTitle:"Introduction to Neo4j Plugins "}, properties:{}}, {start: {SpeakerName:"Paul Blewett"}, end: {TalkTitle:"Aura Enterprise is Coming to Azure Cloud - Find Out What We've Been Up To! "}, properties:{}}, {start: {SpeakerName:"Rhys Evans"}, end: {TalkTitle:"Hidden in the Clouds: Using Graph Technology to Understand Your Cloud Estate "}, properties:{}}, {start: {SpeakerName:"Lea Gütebier"}, end: {TalkTitle:"The HealthECCO Knowledge Graph: Applying Neo4j Technologies in Health Data Research "}, properties:{}}, {start: {SpeakerName:"Ron Henkel"}, end: {TalkTitle:"The HealthECCO Knowledge Graph: Applying Neo4j Technologies in Health Data Research "}, properties:{}}, {start: {SpeakerName:"Dagmar Waltemath"}, end: {TalkTitle:"The HealthECCO Knowledge Graph: Applying Neo4j Technologies in Health Data Research "}, properties:{}}, {start: {SpeakerName:"Chris Engelbert"}, end: {TalkTitle:"Farm Topologies and Time-Series Data "}, properties:{}}, {start: {SpeakerName:"Dmitriy Tverdiakov"}, end: {TalkTitle:"What's New in Neo4j Java Driver Version 5.0 "}, properties:{}}, {start: {SpeakerName:"Rouven Bauer"}, end: {TalkTitle:"Introduction to the Async Python Driver "}, properties:{}}, {start: {SpeakerName:"Michael Simons"}, end: {TalkTitle:"Neo4j Migrations: The Lean Way of Applying Database Refactorings to Neo4j "}, properties:{}}, {start: {SpeakerName:"Niels De Jong"}, end: {TalkTitle:"Building a Visual Rail Planner with NeoDash"}, properties:{}}, {start: {SpeakerName:"Thomas Silkjaer"}, end: {TalkTitle:"XRP Ledger Blockchain ETL With Neo4j "}, properties:{}}, {start: {SpeakerName:"Christophe Willemsen"}, end: {TalkTitle:"Neo4j With Docker and Docker Compose Deep Dive "}, properties:{}}, {start: {SpeakerName:"Elena Kohlwey"}, end: {TalkTitle:"User Change Modeling in Graph Applications "}, properties:{}}, {start: {SpeakerName:"Estelle Scifo"}, end: {TalkTitle:"Building a Neo4j/Python OGM "}, properties:{}}, {start: {SpeakerName:"Hugo Firth"}, end: {TalkTitle:"Neo4j 5 Foundations for Scale"}, properties:{}}] AS row |
|
MATCH (start:Speaker{SpeakerName: row.start.SpeakerName}) |
|
MATCH (end:Talk{TalkTitle: row.end.TalkTitle}) |
|
CREATE (start)-[r:DELIVERS_TALK]->(end) SET r += row.properties; |
|
UNWIND [{start: {SpeakerName:"Tobias Johansson"}, end: {TalkTitle:"Neo4j 5 Foundations for Scale"}, properties:{}}, {start: {SpeakerName:"Federica Ventruto"}, end: {TalkTitle:"Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge Graphs"}, properties:{}}, {start: {SpeakerName:"Alessia Melania Lonoce"}, end: {TalkTitle:"Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge Graphs"}, properties:{}}, {start: {SpeakerName:"Tomaz Bratanic"}, end: {TalkTitle:"From Node to Knowledge Graph Embeddings "}, properties:{}}, {start: {SpeakerName:"Nicolas Rouyer"}, end: {TalkTitle:"ML Innovation: More Accuracy in Predictive Models Thanks to Graph Embeddings "}, properties:{}}, {start: {SpeakerName:"Martin Junghanns"}, end: {TalkTitle:"Native Graph Algorithms in Rust "}, properties:{}}, {start: {SpeakerName:"Paul Horn"}, end: {TalkTitle:"Native Graph Algorithms in Rust "}, properties:{}}] AS row |
|
MATCH (start:Speaker{SpeakerName: row.start.SpeakerName}) |
|
MATCH (end:Talk{TalkTitle: row.end.TalkTitle}) |
|
CREATE (start)-[r:DELIVERS_TALK]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"Welcome to NODES 2022 - AMER"}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Keynote: Social Network Interventions "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Introducing Neo4j 5 for Administrators "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Bootstrapping Your Graph Project With Neo4j Workspace "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"A Space to Relax: Guided Meditation (AMER) "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Graph Modeling: The Shadow Graph "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Graph Database Techniques to Reduce Risk and Innovate "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Divide and Conquer: Send Forth the Microservices "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Security and Velocity Through Declarative Ingestion "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Hypertext Super Collaborator "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Discover Invisible Patterns in Your Data: Connect Google Sheets Tables and Neo4j "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Let's Get Functional! Pull Off a Trifecta With Spring Cloud Function, Azure Functions, and Neo4j "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Graph Databases for Python Developers "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Closing Q&A With Emil and Andreas: AMERICAS "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Modeling NFT Tweets as a Knowledge Graph Using Neo4j "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"DeepFace Recognition With Neo4j "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"IAC: SchemaSmith for Data Governance at JB Hunt "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"PHP Devs, Change Your Life "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Fashion Retail Recommendations Using Neo4j Graph Data Science and Apache Arrow "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Demystifying Graph Analytics With Visualization "}, end: {Territory:"Americas"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Territory{Territory: row.end.Territory}) |
|
CREATE (start)-[r:AIMED_AT]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"Towards Real-time Knowledge Graphs for Non-Player Characters in Games "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"GraphQL Quickstart With the Neo4j GraphQL Library "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Quick Deploy GraphQL API With SST "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Exploring Data With Neo4j Bloom "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Graph Data Science for Computer Vision"}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Top 10 Tips for Evaluating “Benchmark” Results "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Using Sport Data to Build a Graph Model of Inconsistent Hierarchies Over Time "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Graph Pattern Matching "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"GNNs at Scale With Graph Data Science Sampling and Python Client Integration "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Neo4j Ops Manager: Intro and Roadmap "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Data Management with Knowledge Graphs: Bringing Archives to Life "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Arcurve Skills and Staffing Recommender "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Making Sense of Geospatial Data With Knowledge Graphs "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Neo4j Data Loading (ETL/ELT) Best Practices"}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Are Personal Knowledge Graphs the Next Big Thing for Search? "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Graph Algorithms and Visualization for Clinical Care Support of Pneumonia "}, end: {Territory:"Americas"}, properties:{}}, {start: {TalkTitle:"Welcome to NODES 2022 - APAC"}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Keynote: Social Network Interventions "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Workspace in AuraDB "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Easy On-Ramp to Using Graphs "}, end: {Territory:"APAC"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Territory{Territory: row.end.Territory}) |
|
CREATE (start)-[r:AIMED_AT]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"Exploring the Relationships Between People in the Ancient Chinese Novel, \"Three Kingdoms\" "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Creating Graphville: A Neo4j Educational Platform "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Learn Neo4j in Chinese With Neo4j GraphAcademy"}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"From Game of Thrones to Information System Cartography "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Coffee Knowledge Graph "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Analyzing Spammers in Twitter User Network "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Neo4j Lectures of the Stanford CS224W Course "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Track Data Lineage With a Graph Database "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"A Space to Relax: Guided Meditation (APAC) "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Playing With State Machines "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"cy2py: Seamless Neo4j Integration in Python Notebooks "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"ESG Supply Chain Knowledge Graph "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Closing Q&A With Emil and Andreas: AMERICAS "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Using Graph Databases for Consumer Products "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Rapid App Prototyping Using Streamlit and Neo4j "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Managing Software-BOM, Security Issues, and Their Knowledge Graphs Is Easy With Neo4j "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Connected Data Lakehouse: Neo4j and Databricks Reference Data Architecture "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Construction and Application of Knowledge Graphs: Manufacturing Process for Box Parts "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Knowledge Graphs Powering Active Metadata "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Better Testing With Testcontainers "}, end: {Territory:"APAC"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Territory{Territory: row.end.Territory}) |
|
CREATE (start)-[r:AIMED_AT]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"Liquibase & Neo4j: The Migration Sweet Deal "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Explore Your Graphs Visually With Jupyter Notebooks "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"BlueHound: Community-Driven Security Based on Neo4j and NeoDash "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"The Heisenbugs - Finding Collusion Among Malicious Entities Through Knowledge Graph "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Doctor.ai: A Graph-Based Medical Chatbot "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Running Neo4j in Docker and Deploying Neo4j Application in OpenShift "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Knowledge Graphs and Machine Learning for Halal Food Product Recommendations "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Take Data to the Next Level With Graph Machine Learning "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"CloudScreen: A Graph-Based Drug Repurposing Platform Empowered by Machine Learning "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Generating a Hematopoietic Stem Cell Knowledge Graph for Scientific Knowledge Discovery "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Taking Application Security Insights to the Next Level With Fabric and NeoSemantics "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Graph-Based Features for Recommendation Systems in Drug Discovery "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Using Graph Embeddings for Suspicious Bitcoin Transactions "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Knowledge Graphs in Time-Series Data "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Fundamentals of Neo4j Graph Data Science Series 2.x – Pipelines and More "}, end: {Territory:"APAC"}, properties:{}}, {start: {TalkTitle:"Welcome to NODES 2022 - EMEA"}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Keynote: Social Network Interventions "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"What's New in Neo4j 5 and Aura 5 for Developers "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Index Changes in Neo4j 5 "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"What's New in Graph Data Science Land "}, end: {Territory:"EMEA"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Territory{Territory: row.end.Territory}) |
|
CREATE (start)-[r:AIMED_AT]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"Link Prediction With Graph Data Science at Scale "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"GraphQL Federation and Key Neo4j GraphQL Library Features"}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Cymple: Cypher Modular Pythonic Language Extension "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"A Space to Relax: Guided Meditation (EMEA) "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Tracing Your Data's DNA "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Genealogy With Different Graph Technologies for Data Collection and Visualization "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"RDBMS to Neo4j Real Time Data Sync with Debezium and Kafka "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"A Developer's Guide to Building a Graph Project Value Case "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Temporal Graph Analysis "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Building Neo4j Ops Manager: Lessons From Dogfooding "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Closing Q&A With Emil and Andreas: EMEA"}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Building Java Applications With Quarkus and Neo4j "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Introducing the PHP and Graph Ecosystem"}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Introduction to Neo4j Plugins "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Aura Enterprise is Coming to Azure Cloud - Find Out What We've Been Up To! "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Hidden in the Clouds: Using Graph Technology to Understand Your Cloud Estate "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"The HealthECCO Knowledge Graph: Applying Neo4j Technologies in Health Data Research "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Farm Topologies and Time-Series Data "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"What's New in Neo4j Java Driver Version 5.0 "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Introduction to the Async Python Driver "}, end: {Territory:"EMEA"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Territory{Territory: row.end.Territory}) |
|
CREATE (start)-[r:AIMED_AT]->(end) SET r += row.properties; |
|
UNWIND [{start: {TalkTitle:"Neo4j Migrations: The Lean Way of Applying Database Refactorings to Neo4j "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Building a Visual Rail Planner with NeoDash"}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"XRP Ledger Blockchain ETL With Neo4j "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Neo4j With Docker and Docker Compose Deep Dive "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"User Change Modeling in Graph Applications "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Building a Neo4j/Python OGM "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Neo4j 5 Foundations for Scale"}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge Graphs"}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"From Node to Knowledge Graph Embeddings "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"ML Innovation: More Accuracy in Predictive Models Thanks to Graph Embeddings "}, end: {Territory:"EMEA"}, properties:{}}, {start: {TalkTitle:"Native Graph Algorithms in Rust "}, end: {Territory:"EMEA"}, properties:{}}] AS row |
|
MATCH (start:Talk{TalkTitle: row.start.TalkTitle}) |
|
MATCH (end:Territory{Territory: row.end.Territory}) |
|
CREATE (start)-[r:AIMED_AT]->(end) SET r += row.properties; |
|
UNWIND [{start: {Track:"Beginner"}, end: {Territory:"Americas"}, properties:{}}, {start: {Track:"Intermediate"}, end: {Territory:"Americas"}, properties:{}}, {start: {Track:"Advanced"}, end: {Territory:"Americas"}, properties:{}}, {start: {Track:"Beginner"}, end: {Territory:"APAC"}, properties:{}}, {start: {Track:"Intermediate"}, end: {Territory:"APAC"}, properties:{}}, {start: {Track:"Advanced"}, end: {Territory:"APAC"}, properties:{}}, {start: {Track:"Beginner"}, end: {Territory:"EMEA"}, properties:{}}, {start: {Track:"Intermediate"}, end: {Territory:"EMEA"}, properties:{}}, {start: {Track:"Advanced"}, end: {Territory:"EMEA"}, properties:{}}] AS row |
|
MATCH (start:Track{Track: row.start.Track}) |
|
MATCH (end:Territory{Territory: row.end.Territory}) |
|
CREATE (start)-[r:RELATED_TO]->(end) SET r += row.properties; |
