Kerala is a state in India and popularly known as "God’s own Country". It is very famous for the BackWaters, HouseBoats, Food, Culture. There are numerous resorts, hotels and homestays in Kerala. This application provides a fun and interactive way to find a Resort of your choice.
This Graph is based on the MST3K TV-series that ran during the 1990s. Awesome TV-serie, my favourite actually. I created this Graph based on the characters of the show and where they live/reside/hunt, and which actors played them. As the Actors usually played several characters, and many characters were played by several actors, the graph get’s a bit interesting :) Enjoy!
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= Models Sports Leagues | |
Aravind R. Yarram <yaravind@gmail.com> | |
v1.0, 08-Sep-2013 | |
== Domain Model | |
Each *League* has multiple *Level*s like playoffs, quarter-finals etc. The levels are ordered: first is playoffs, +NEXT+ is quarter-finals, +NEXT+ is semi-finals and then the next and last one is the finals. The ordering is represented using a http://docs.neo4j.org/chunked/milestone/cookbook-linked-list.html[linked-list]. | |
A *Player* can play for more than one team over multiple leagues but can only play for a single team in a given league. This is captured by the +PLAYED_IN_FOR_LEAGUE+ http://docs.neo4j.org/chunked/milestone/cypher-cookbook-hyperedges.html[hyperedge] between player, team and league using http://docs.neo4j.org/chunked/milestone/cypher-cookbook-hyperedges.html[hypernode] *PlayerTeamLeague* . A team can register in a new league with a different name in which case, we want to know what it was +PREVIOUSLY_KNOWN_AS+.The fact that a player had for a given team (irrespective of which league) is capture |
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= Enterprise Content Management with Neo4j | |
== Introduction | |
There are several challenges in Enterprise Content Management (ECM) that current technologies cannot tackle efficiently. With Neo4j, a whole new world of possibilities opens up. There are few things more "graphy" than ECM, and so the logical next step is the use of graph databases. | |
What follows is a subset of the possibilities with Neo4J in ECM. We tackle recommendations, time-based versioning, ACL, metadata management and user action registration. | |
== The dataset |
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= Why JIRA should use Neo4j | |
== Introduction | |
There are few developers in the world that have never used an issue tracker. But there are even fewer developers who have ever used an issue tracker which uses a graph database. This is a shame because issue tracking really maps much better onto a graph database, than it does onto a relational database. Proof of that is the https://developer.atlassian.com/download/attachments/4227160/JIRA61_db_schema.pdf?api=v2[JIRA database schema]. | |
Now obviously, the example below does not have all of the features that a tool like JIRA provides. But it is only a proof of concept, you could map every feature of JIRA into a Neo4J database. What I've done below, is take out some of the core functionalities and implement those. | |
== The data set |
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= Business Rule / Recommendation gist = | |
In this simple example, we want to highlight the power of graphs to describe, discover, visualise and implement powerful business rule-based recommendations. | |
In the example, we will create a simple graph containing | |
- a +person+ ("Rik") | |
- a +city+ ("London") | |
- an +age+ ("39") | |
- a +child+ ("Toon") | |
and all the required relationships from the person to the city, to his age, and his child. |
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= Last.fm Dataset Gist = | |
Earlier this month, I published http://blog.neo4j.org/2013/07/fun-with-music-neo4j-and-talend.html[a blog post] about my fun with some self-exported http://last.fm[Last.fm] data. With this Gist, I would like to provide a bit more practical detail on the dataset and how you could use it. | |
Let's first create an overview graph of the model. | |
image::http://2.bp.blogspot.com/-uNPggNP9A3c/Ud7HDhwpkbI/AAAAAAAAAK4/AZd25Q0h-j4/s640/Screen+Shot+2013-07-11+at+16.52.59.png[] | |
[source,cypher] | |
---- |
This is the Orienteering Dataset based on the blog.neo4j.org post.
It’s a simple, three-leg training course in an Antwerp park. Setting this up as a graph in neo4j was easy enough:
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= graphGist generated from spock test Neo4jCypherOneLabel.groovy | |
graphGist asciiDoc file for use at http://gist.neo4j.org/ [GitHub Gist] | |
Generated on Sun Jul 28 08:03:43 PDT 2013 | |
//console | |
query to create plato with philosopher label |
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= graphGist generated from spock test Neo4jCypherOneRelationship.groovy | |
graphGist asciiDoc file for use at http://gist.neo4j.org/ [GitHub Gist] | |
Generated on Mon Jul 29 07:11:04 PDT 2013 | |
//console | |
query to create plato with philosopher label |