From k00ni/owl-reasoner-list

references.md

• Argyridis, Argyros and Argialas, Demetre P (2015). A fuzzy spatial reasoner for multi-scale GEOBIA ontologies.
• Armas Romero, Ana and Cuenca Grau, Bernardo and Horrocks, Ian (2012). MORe: Modular combination of OWL reasoners for ontology classification.
• Bak, Jaroslaw and Nowak, Maciej and Jedrzejek, Czeslaw (2014). RuQAR: Reasoning framework for OWL 2 RL ontologies.
• Balhoff, James P and Good, Benjamin M and Carbon, Seth and Mungall, Chris (2018). Arachne: an OWL RL Reasoner Applied to Gene Ontology Causal Activity Models (and Beyond)..
• Bate, Andrew and Motik, Boris and Grau, Bernardo Cuenca and Simanc (2016). Extending consequence-based reasoning to SRIQ.
• Bento, Alexandre and M'e (2022). Do Arduinos dream of efficient reasoners?.
• Bishop, Barry and Bojanov, Spas (2011). Implementing OWL 2 RL and OWL 2 QL Rule-Sets for OWLIM..
• Bobillo, Fernando and Straccia, Umberto (2016). The fuzzy ontology reasoner fuzzyDL.
• Bourguet, Jean-R'e (2014). TROvE: a Graphical Tool to Evaluate OWL Reasoners..
• Carroll, Jeremy J and Dickinson, Ian and Dollin, Chris and Reynolds, Dave and Seaborne, Andy and Wilkinson, Kevin (2004). Jena: implementing the semantic web recommendations.
• Carral, David and Dragoste, Irina and Gonz'a (2019). Vlog: A rule engine for knowledge graphs.
• Ceylan, (2015). The Bayesian ontology reasoner is born!.
• Todirascu, Amalia and de Beuvron, Fran (2003). Using Semantics for Efficient Information.
• Cucala, David Tena and Grau, Bernardo Cuenca and Horrocks, Ian (2019). Sequoia: A Consequence Based Reasoner for SROIQ..
• David, J'e (2011). The alignment API 4.0.
• del Mar Roldan-Garcia, Maria and Aldana-Montes, Jose F (2012). Evaluating DBOWL: A Nonmaterializing OWL Reasoner based on Relational Database Technology.
• De Meester, Ben and Arndt, D"o (2015). Event-Driven Rule-Based Reasoning using EYE..
• Mutharaju, Raghava and Mateti, Prabhaker and Hitzler, Pascal (2014). Developing a distributed reasoner for the Semantic Web..
• Dolby, Julian and Fokoue, Achille and Kalyanpur, Aditya and Schonberg, Edith and Srinivas, Kavitha (2009). Scalable highly expressive reasoner (SHER).
• Doorenbos, Robert B (1995). Production Matching for Large Learning Systems..
• Elenius, Daniel (2012). SWRL-IQ: A Prolog-based Query Tool for OWL and SWRL..
• Fernandes, Diogo and Bernardino, Jorge (2018). Graph Databases Comparison: AllegroGraph, ArangoDB, InfiniteGraph, Neo4J, and OrientDB..
• Gennari, John H and Musen, Mark A and Fergerson, Ray W and Grosso, William E and Crub'e (2003). The evolution of Prot'e.
• Glimm, Birte and Horrocks, Ian and Motik, Boris and Stoilos, Giorgos and Wang, Zhe (2014). HermiT: an OWL 2 reasoner.
• Grigorev, Andrey V and Ivashko, Alexander G (2013). TReasoner: System Description..
• Giordano, Laura and Gliozzi, Valentina and Pozzato, Gian Luca and Renzulli, Riccardo and others (2017). An efficient reasoner for description logics of typicality and rational closure.
• Haarslev, Volker and M"o (2001). RACER system description.
• Haarslev, Volker and Hidde, Kay and M"o (2012). The RacerPro knowledge representation and reasoning system.
• Hitzler, Pascal and Vrandecic, Denny (2005). The screech owl reasoner-scalable approximate abox reasoning with owl.
• Horridge, Matthew and Bechhofer, Sean (2011). The owl api: A java api for owl ontologies.
• Jang, Minsu and Sohn, Joo-Chan (2004). Bossam: An extended rule engine for OWL inferencing.
• Kang, Yong-Bin and Krishnaswamy, Shonali and Sawangphol, Wudhichart and Gao, Lianli and Li, Yuan-Fang (2020). Understanding and improving ontology reasoning efficiency through learning and ranking.
• Kazakov, Yevgeny and Krötzsch, Markus and Simančík, František (2012). ELK: a reasoner for OWL EL ontologies.
• Kazakov, Yevgeny (2015). Consequence-Driven Reasoning for Horn SHIQ Ontologies.
• Khamparia, Aditya and Pandey, Babita (2017). Comprehensive analysis of semantic web reasoners and tools: a survey.
• Kov'a (2013). First-order theorem proving and Vampire.
• Lam, An Ngoc and Elvese (2023). A Performance Evaluation of OWL 2 DL Reasoners using ORE 2015 and Very Large Bio Ontologies.
• Le Duc, Chan and Lamolle, Myriam and Zimmermann, Antoine and Cur'e (2013). DRAOn: A Distributed Reasoner for Aligned Ontologies..
• Lembo, Domenico and Santarelli, Valerio and Savo, Domenico Fabio (2013). Graph-based ontology classification in OWL 2 QL.
• Li, Yuan-Fang and Kang, Yong-Bin (2020). Towards Meta-reasoning for Ontologies: A Roadmap.
• Liu, Yu and McBrien, Peter (2017). Spowl: Spark-based owl 2 reasoning materialisation.
• Lopes, Carlos and Knorr, Matthias and Leite, Jo (2017). Nohr: Integrating XSB prolog with the OWL 2 profiles and beyond.
• Matentzoglu, Nicolas and Leo, Jared and Hudhra, Valentino and Sattler, Uli and Parsia, Bijan (2015). A Survey of Current, Stand-alone OWL Reasoners..
• Matheus, C and Dionne, B and Parent, D and Baclawski, Kenneth and Kokar, M (2006). Basevisor: A forward-chaining inference engine optimized for rdf/owl triples.
• Meditskos, Georgios and Bassiliades, Nick (2008). A rule-based object-oriented OWL reasoner.
• Meditskos, Georgios and Bassiliades, Nick (2010). DLEJena: A practical forward-chaining OWL 2 RL reasoner combining Jena and Pellet.
• Mendez, Julian and Suntisrivaraporn, Boontawee (2009). Reintroducing CEL as an OWL 2 EL reasoner..
• Metke-Jimenez, Alejandro and Lawley, Michael (2013). Snorocket 2.0: Concrete Domains and Concurrent Classification..
• Mendez, Julian (2012). jcel: A Modular Rule-based Reasoner..
• Michel, Friedrich and Turhan, Anni-Yasmin and Zarrie (2019). Efficient TBox reasoning with value restrictions—introducing the FLower reasoner.
• Mishra, Ravi Bhushan and Kumar, Sandeep (2011). Semantic web reasoners and languages.
• Motik, Boris and Sattler, Ulrike (2006). A comparison of reasoning techniques for querying large description logic aboxes.
• Mrozek, Drahomir and Pukancova, Julia and Homola, Martin (2018). ABox Abduction Solver Exploiting Multiple DL Reasoners..
• Mutharaju, Raghava (2016). Distributed rule-based ontology reasoning.
• Neelam, Sumit and Sharma, Udit and Bhatia, Sumit and Karanam, Hima and Likhyani, Ankita and Abdelaziz, Ibrahim and Fokoue, Achille and Subramaniam, LV (2022). Expressive Reasoning Graph Store: A Unified Framework for Managing RDF and Property Graph Databases.
• Nenov, Yavor and Piro, Robert and Motik, Boris and Horrocks, Ian and Wu, Zhe and Banerjee, Jay (2015). RDFox: A highly-scalable RDF store.
• Niepert, Mathias and Noessner, Jan and Stuckenschmidt, Heiner (2011). Log-linear description logics.
• O'SULLIVAN, DECLAN (2011). COROR: A COmposable Rule-entailment Owl Reasoner for Resource-Constrained Devices, LNCS Rule-Based Reasoning, Programming, and Applications.
• Pan, Jeff Z and Thomas, Edward and Ren, Yuan and Taylor, Stuart (2012). Exploiting tractable fuzzy and crisp reasoning in ontology applications.
• Papadakis, Nikos and Stravoskoufos, Kostas and Baratis, Evdoxios and Petrakis, Euripides GM and Plexousakis, Dimitris (2011). Proton: A prolog reasoner for temporal ontologies in owl.
• Parsia, Bijan and Sirin, Evren (2004). Pellet: An owl dl reasoner.
• Parsia, Bijan and Matentzoglu, Nicolas and Goncalves, Rafael S and Glimm, Birte and Steigmiller, Andreas (2017). The OWL reasoner evaluation (ORE) 2015 competition report.
• Patel-Schneider, Peter F and Horrocks, Ian (1999). DLP and FaCT.
• P'e (2010). Tractable query answering and rewriting under description logic constraints.
• Riguzzi, Fabrizio and Bellodi, Elena and Lamma, Evelina and Zese, Riccardo (2013). BUNDLE: A reasoner for probabilistic ontologies.
• Rodriguez-Muro, Mariano and Hardi, Josef and Calvanese, Diego (2012). Quest: efficient SPARQL-to-SQL for RDF and OWL.
• Rudolph, Sebastian and Schweizer, Lukas and Tirtarasa, Satyadharma (2017). Wolpertinger: A Fixed-Domain Reasoner..
• Ruta, Michele and Scioscia, Floriano and Gramegna, Filippo and Bilenchi, Ivano and Di Sciascio, Eugenio (2019). Mini-ME Swift: the first mobile OWL reasoner for iOS.
• Scioscia, Floriano and Ruta, Michele and Loseto, Giuseppe and Gramegna, Filippo and Ieva, Saverio and Pinto, Agnese and Di Sciascio, Eugenio (2018). Mini-ME matchmaker and reasoner for the Semantic Web of Things.
• Sertkaya, Bar (2011). In the search of improvements to the EL+ classification algorithm.
• Sertkaya, Baris (2013). The ELepHant Reasoner System Description..
• Shokohinia, Mojtaba and Dideban, Abbas and Yaghmaee, Farzin (2022). A METHOD FOR IMPROVING REASONING AND REALIZATION PROBLEM SOLVING IN DESCRIPTIVE LOGIC-BASED AND ONTOLOGY-BASED REASONERS.
• Sim, Jaemoon and Kim, Jihoon and Kwon, Ohbyung and Lee, Sean S and Kim, Jungho and Jang, HK and Lee, Myungchul (2006). Applying Inference Engine to Context-Aware Computing Services.
• Siorpaes, Katharina and Winkler, Daniel (2010). An elp reasoner.
• Sirin, Evren and Parsia, Bijan and Grau, Bernardo Cuenca and Kalyanpur, Aditya and Katz, Yarden (2007). Pellet: A practical owl-dl reasoner.
• Singh, Gunjan and Bhatia, Sumit and Mutharaju, Raghava (2020). OWL2Bench: a benchmark for OWL 2 reasoners.
• Sinner, Alex and Kleemann, Thomas (2005). Krhyper--in your pocket.
• Sivakumar, R and Arivoli, PV (2011). Ontology visualization PROT'E.
• Slater, Luke and Gkoutos, Georgios V and Schofield, Paul N and Hoehndorf, Robert (2016). Using AberOWL for fast and scalable reasoning over BioPortal ontologies.
• Song, Weihong and Spencer, Bruce and Du, Weichang (2012). WSReasoner: A Prototype Hybrid Reasoner for ALCHOI Ontology Classification using a Weakening and Strengthening Approach..
• Song, Weihong and Spencer, Bruce and Du, Weichang (2013). Technical report of a transformation approach for classifying ALCHI (D) ontologies with a consequence-based ALCH reasoner.
• Steigmiller, Andreas and Liebig, Thorsten and Glimm, Birte (2014). Konclude: system description.
• Stocker, Markus and Smith, Michael (2008). Owlgres: A scalable OWL reasoner..
• Stoilos, Giorgos (2014). Hydrowl: A hybrid query answering system for OWL 2 DL ontologies.
• Straccia, Umberto (2010). Softfacts: A top-k retrieval engine for ontology mediated access to relational databases.
• Terdjimi, Mehdi and M'e (2015). Hylar: Hybrid location-agnostic reasoning.
• Terdjimi, Mehdi and M'e (2016). Hylar+ improving hybrid location-agnostic reasoning with incremental rule-based update.
• Thomas, Edward and Pan, Jeff Z and Ren, Yuan (2010). TrOWL: Tractable OWL 2 Reasoning Infrastructure..
• Tsarkov, Dmitry and Riazanov, Alexandre and Bechhofer, Sean and Horrocks, Ian (2004). Using Vampire to reason with OWL.
• Tsarkov, Dmitry and Horrocks, Ian (2006). FaCT++ description logic reasoner: System description.
• Tsarkov, Dmitry and Palmisano, Ignazio (2012). Chainsaw: a Metareasoner for Large Ontologies..
• Tsatsou, Dorothea and Dasiopoulou, Stamatia and Kompatsiaris, Ioannis and Mezaris, Vasileios (2014). LiFR: A lightweight fuzzy DL reasoner.
• Urbani, Jacopo and Kotoulas, Spyros and Maassen, Jason and Van Harmelen, Frank and Bal, Henri E (2010). OWL Reasoning with WebPIE: Calculating the Closure of 100 Billion Triples..
• Urbani, Jacopo and Van Harmelen, Frank and Schlobach, Stefan and Bal, Henri (2011). QueryPIE: Backward reasoning for OWL Horst over very large knowledge bases.
• Verborgh, Ruben and De Roo, Jos (2015). Drawing conclusions from linked data on the web: The EYE reasoner.
• Wang, Changlong and Feng, Zhiyong and Zhang, Xiaowang and Wang, Xin and Rao, Guozheng and Fu, Daoxun (2019). ComR: a combined OWL reasoner for ontology classification.
• Wu, Zhe and Rieb, Karl and Eadon, George and Khandelwal, Ankesh and Kolovski, Vladimir (2012). Advancing the Enterprise-class OWL Inference Engine in Oracle Database..
• Wu, Kejia and Haarslev, Volker (2012). A Parallel Reasoner for the Description Logic ALC.
• Wu, Wenrui and Feng, Zhiyong and Zhang, Xiaowang and Wang, Xin and Rao, Guozheng (2016). PROSE: A plugin-based paraconsistent OWL reasoner.
• Wullinger, Peter (2018). Supporting format migration with ontology model comparison.
• Xiao, Guohui and Heymans, Stijn and Eiter, Thomas (2010). DReW: a reasoner for datalog-rewritable description logics and dl-programs.
• Zese, Riccardo and Bellodi, Elena and Lamma, Evelina and Riguzzi, Fabrizio (2013). A Description Logics Tableau Reasoner in Prolog..
• Zou, Youyong and Finin, Tim and Chen, Harry (2005). F-owl: An inference engine for semantic web.
• Zhou, Jian and Ma, Li and Liu, Qiaoling and Zhang, Lei and Yu, Yong and Pan, Yue (2006). Minerva: A scalable OWL ontology storage and inference system.
• Zhou, Yujiao and Grau, Bernardo Cuenca and Nenov, Yavor and Kaminski, Mark and Horrocks, Ian (2015). Pagoda: Pay-as-you-go ontology query answering using a datalog reasoner.

https://raw.githubusercontent.com/k00ni/owl-reasoner-list/master/paper.bib

Code generated from github copilot to conver bibtext references to markdown lists

import re

def bibtex_to_md(text):
    # Split the text into separate references
    references = re.split(r'\n(?=@)', text)
    # Format each reference
    md_references = []
    for ref in references:
        # Extract the key information from the reference
        title_match = re.search(r'title={([^}]+)}', ref)
        author_match = re.search(r'author={([^}]+)}', ref)
        year_match = re.search(r'year={([^}]+)}', ref)
        # Format the reference as a markdown list item
        if title_match and author_match and year_match:
            title = title_match.group(1)
            author = author_match.group(1)
            year = year_match.group(1)
            md_references.append(f'- {author} ({year}). {title}.')
    # Join the references back together into a single string
    return '\n'.join(md_references)

def clean_text(text):
    # Remove unicode characters
    text = re.sub(r'\\[^\s]*', '', text)
    # Remove escape sequences
    text = text.replace('{', '').replace('}', '')
    return text

md_text = bibtex_to_md(text)
md_text = clean_text(md_text)

# Write the markdown text to a file
with open('references.md', 'w') as f:
    f.write(md_text)