@misc{yang2025languagemodelsontologyencoders,
      title={Language Models as Ontology Encoders}, 
      author={Hui Yang and Jiaoyan Chen and Yuan He and Yongsheng Gao and Ian Horrocks},
      year={2025},
      eprint={2507.14334},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2507.14334}, 
}

@misc{fey2019fastgraphrepresentationlearning,
      title={Fast Graph Representation Learning with PyTorch Geometric}, 
      author={Matthias Fey and Jan Eric Lenssen},
      year={2019},
      eprint={1903.02428},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1903.02428}, 
}

@misc{manchester_pizza_ontology,
  title = {The Pizza Ontology},
  author = {Horridge, Matthew},
  year = {2011},
  note = {From the Protege OWL Tutorial, University of Manchester},
  url = {https://protege.stanford.edu/publications/ontology/pizza.owl}
}

@article{gruber1993ontology,
  title={A translation approach to portable ontology specifications},
  author={Gruber, Thomas R},
  journal={Knowledge acquisition},
  volume={5},
  number={2},
  pages={199--220},
  year={1993},
  publisher={Elsevier}
}

@article{DBLP:journals/corr/abs-2012-13635,
  author       = {Samy Badreddine and
                  Artur S. d'Avila Garcez and
                  Luciano Serafini and
                  Michael Spranger},
  title        = {Logic Tensor Networks},
  journal      = {CoRR},
  volume       = {abs/2012.13635},
  year         = {2020},
  url          = {https://arxiv.org/abs/2012.13635},
  eprinttype    = {arXiv},
  eprint       = {2012.13635},
  timestamp    = {Thu, 10 Nov 2022 17:26:23 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2012-13635.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@misc{lample2019deeplearningsymbolicmathematics,
      title={Deep Learning for Symbolic Mathematics}, 
      author={Guillaume Lample and François Charton},
      year={2019},
      eprint={1912.01412},
      archivePrefix={arXiv},
      primaryClass={cs.SC},
      url={https://arxiv.org/abs/1912.01412}, 
}

@article{DBLP:journals/corr/abs-1904-12584,
  author       = {Jiayuan Mao and
                  Chuang Gan and
                  Pushmeet Kohli and
                  Joshua B. Tenenbaum and
                  Jiajun Wu},
  title        = {The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and
                  Sentences From Natural Supervision},
  journal      = {CoRR},
  volume       = {abs/1904.12584},
  year         = {2019},
  url          = {http://arxiv.org/abs/1904.12584},
  eprinttype    = {arXiv},
  eprint       = {1904.12584},
  timestamp    = {Tue, 05 Aug 2025 17:48:32 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1904-12584.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@proceedings{semrec2023,
booktitle = {22nd International Semantic Web Conference ISWC 2023},
title = {Joint Proceedings of Scholarly QALD 2023 and SemREC 2023},
year = 2023,
editor = {Debayan Banerjee and Ricardo Usbeck and Nandana Mihindukulasooriya and Mohamad Yaser Jaradeh and Sören Auer and Gunjan Singh and Raghava Mutharaju and Pavan Kapanipathi},
number = 3592,
series = {CEUR Workshop Proceedings},
address = {Aachen},
issn = {1613-0073},
url = {http://ceur-ws.org/Vol-3592/},
venue = {Athens, Greece},
eventdate = {2023-11-06/2023-11-10},
}

@proceedings{semrec2022,
booktitle = {21st International Semantic Web Conference (ISWC 2022)},
title = {Joint Proceedings of SemREC 2022 and SMART 2022},
year = 2022,
editor = {Gunjan Singh and Raghava Mutharaju and Pavan Kapanipathi and Nandana Mihindukulasooriya and Mohnish Dubey and Ricardo Usbeck and Debayan Banerjee},
number = 3337,
series = {CEUR Workshop Proceedings},
address = {Aachen},
issn = {1613-0073},
url = {http://ceur-ws.org/Vol-3337/},
venue = {Hangzhou, China},
eventdate = {2022-10-24/2022-10-27},
}

@proceedings{semrec2021,
booktitle = {20th International Semantic Web Conference (ISWC 2021)},
title = {Proceedings of the Semantic Reasoning Evaluation Challenge (SemREC 2021)},
year = 2021,
editor = {Gunjan Singh and Raghava Mutharaju and Pavan Kapanipathi},
number = 3123,
series = {CEUR Workshop Proceedings},
address = {Aachen},
issn = {1613-0073},
url = {http://ceur-ws.org/Vol-3123/},
venue = {Virtual Event},
eventdate = {2021-10-27},
}

@inproceedings{GALEN,
  title={The GALEN High Level Ontology},
  author={Alan L. Rector},
  year={2008},
  url={https://api.semanticscholar.org/CorpusID:73607647}
}

@article{GO,
  added-at = {2012-09-15T11:48:04.000+0200},
  author = {Ashburner, M and Ball, C A and Blake, J A and Botstein, D and Butler, H and Cherry, J M and Davis, A P and Dolinski, K and Dwight, S S and Eppig, J T and Harris, M A and Hill, D P and Issel-Tarver, L and Kasarskis, A and Lewis, S and Matese, J C and Richardson, J E and Ringwald, M and Rubin, G M and Sherlock, G},
  biburl = {https://www.bibsonomy.org/bibtex/2a5639980bc3279f81a2c6d24b55058f7/sbsad},
  description = {Gene ontology: tool for the unification of biology... [Nat Genet. 2000] - PubMed - NCBI},
  doi = {10.1038/75556},
  file = {:/bioinfo/users/bsadacca/Biblio/Genes_DB/GeneOntology.pdf:PDF},
  groups = {public},
  interhash = {402ac4f983bc9e3797406bf9b42ce092},
  intrahash = {a5639980bc3279f81a2c6d24b55058f7},
  journal = {Nat Genet},
  keywords = {DataBase GO Genes},
  month = May,
  number = 1,
  pages = {25-29},
  pmid = {10802651},
  timestamp = {2012-09-18T11:35:37.000+0200},
  title = {Gene ontology: tool for the unification of biology. The Gene Ontology Consortium},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/10802651},
  username = {sbsad},
  volume = 25,
  year = 2000
}

@article{Anatomy,
title = {Uberon, an integrative multi-species anatomy ontology},
author = {Mungall, Christopher J. and Torniai, Carlo and Gkoutos, Georgios V. and Lewis, Suzanna E. and Haendel, Melissa A.},
abstractNote = {We present Uberon, an integrated cross-species ontology consisting of over 6,500 classes representing a variety of anatomical entities, organized according to traditional anatomical classification criteria. The ontology represents structures in a species-neutral way and includes extensive associations to existing species-centric anatomical ontologies, allowing integration of model organism and human data. Uberon provides a necessary bridge between anatomical structures in different taxa for cross-species inference. It uses novel methods for representing taxonomic variation, and has proved to be essential for translational phenotype analyses. Uberon is available at http://uberon.org},
doi = {10.1186/gb-2012-13-1-r5},
journal = {GenomeBiology.com},
number = 1,
volume = 13,
place = {United States},
year = {2012},
month = {1}
}

@article{FoodOn,
  abstract = {The construction of high capacity data sharing networks to support increasing government and commercial data exchange has highlighted a key roadblock: the content of existing Internet-connected information remains siloed due to a multiplicity of local languages and data dictionaries. This lack of a digital lingua franca is obvious in the domain of human food as materials travel from their wild or farm origin, through processing and distribution chains, to consumers. Well defined, hierarchical vocabulary, connected with logical relationships—in other words, an ontology—is urgently needed to help tackle data harmonization problems that span the domains of food security, safety, quality, production, distribution, and consumer health and convenience. FoodOn (http://foodon.org) is a consortium-driven project to build a comprehensive and easily accessible global farm-to-fork ontology about food, that accurately and consistently describes foods commonly known in cultures from around the world. FoodOn addresses food product terminology gaps and supports food traceability. Focusing on human and domesticated animal food description, FoodOn contains animal and plant food sources, food categories and products, and other facets like preservation processes, contact surfaces, and packaging. Much of FoodOn’s vocabulary comes from transforming LanguaL, a mature and popular food indexing thesaurus, into a World Wide Web Consortium (W3C) OWL Web Ontology Language-formatted vocabulary that provides system interoperability, quality control, and software-driven intelligence. FoodOn compliments other technologies facilitating food traceability, which is becoming critical in this age of increasing globalization of food networks.},
  added-at = {2019-12-18T15:27:41.000+0100},
  author = {Dooley, Damion M. and Griffiths, Emma J. and Gosal, Gurinder S. and Buttigieg, Pier L. and Hoehndorf, Robert and Lange, Matthew C. and Schriml, Lynn M. and Brinkman, Fiona S. L. and Hsiao, William W. L.},
  biburl = {https://www.bibsonomy.org/bibtex/26f23d09dc44d2e3269ecbb64f1a3cc08/lysander07},
  description = {FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration | npj Science of Food},
  doi = {10.1038/s41538-018-0032-6},
  interhash = {eb2077b25eb1b4598a7af1307d264f81},
  intrahash = {6f23d09dc44d2e3269ecbb64f1a3cc08},
  issn = {23968370},
  journal = {npj Science of Food},
  keywords = {ontology},
  number = 1,
  pages = {23--},
  refid = {Dooley2018},
  timestamp = {2019-12-18T15:29:58.000+0100},
  title = {FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration},
  url = {https://doi.org/10.1038/s41538-018-0032-6},
  volume = 2,
  year = 2018
}

@InProceedings{HeLis,
author="Dragoni, Mauro
and Bailoni, Tania
and Maimone, Rosa
and Eccher, Claudio",
editor="Vrande{\v{c}}i{\'{c}}, Denny
and Bontcheva, Kalina
and Su{\'a}rez-Figueroa, Mari Carmen
and Presutti, Valentina
and Celino, Irene
and Sabou, Marta
and Kaffee, Lucie-Aim{\'e}e
and Simperl, Elena",
title="HeLiS: An Ontology for Supporting Healthy Lifestyles",
booktitle="The Semantic Web -- ISWC 2018",
year="2018",
publisher="Springer International Publishing",
address="Cham",
pages="53--69",
abstract="The use of knowledge resources in the digital health domain is a trending activity significantly grown in the last decade. In this paper, we present HeLiS: an ontology aiming to provide in tandem a representation of both the food and physical activity domains and the definition of concepts enabling the monitoring of users' actions and of their unhealthy behaviors. We describe the construction process, the plan for its maintenance, and how this ontology has been used into a real-world system with a focus on ``Key to Health'': a project for promoting healthy lifestyles on workplaces.",
isbn="978-3-030-00668-6"
}

@inproceedings{semrec_hoehndorf,
  title={Evaluating Different Methods for Semantic Reasoning
Over Ontologies},
  author={Zhapa-Camacho, Fernando and Hoehndorf, Robert},
  booktitle={QALD/SemREC@ ISWC},
  year={2023}
}

@ARTICLE{10148662,
  author={Sheth, Amit and Roy, Kaushik and Gaur, Manas},
  journal={IEEE Intelligent Systems}, 
  title={Neurosymbolic Artificial Intelligence (Why, What, and How)}, 
  year={2023},
  volume={38},
  number={3},
  pages={56-62},
  keywords={Neural networks;Symbols;Self-supervised learning;Medical services;Cognition;Human factors;Safety},
  doi={10.1109/MIS.2023.3268724}}

@inproceedings{Stevens2008AFH,
  title={A Family History Knowledge Base Using OWL 2},
  author={Robert Stevens and Margaret Stevens},
  booktitle={OWL: Experiences and Directions},
  year={2008},
  url={https://api.semanticscholar.org/CorpusID:10478581}
}

@article{SIRIN200751,
title = {Pellet: A practical OWL-DL reasoner},
journal = {Journal of Web Semantics},
volume = {5},
number = {2},
pages = {51-53},
year = {2007},
note = {Software Engineering and the Semantic Web},
issn = {1570-8268},
doi = {https://doi.org/10.1016/j.websem.2007.03.004},
url = {https://www.sciencedirect.com/science/article/pii/S1570826807000169},
author = {Evren Sirin and Bijan Parsia and Bernardo Cuenca Grau and Aditya Kalyanpur and Yarden Katz},
keywords = {Web Ontology Language, Description logics, Tableau Theorem Proving},
abstract = {In this paper, we present a brief overview of Pellet: a complete OWL-DL reasoner with acceptable to very good performance, extensive middleware, and a number of unique features. Pellet is the first sound and complete OWL-DL reasoner with extensive support for reasoning with individuals (including nominal support and conjunctive query), user-defined datatypes, and debugging support for ontologies. It implements several extensions to OWL-DL including a combination formalism for OWL-DL ontologies, a non-monotonic operator, and preliminary support for OWL/Rule hybrid reasoning. Pellet is written in Java and is open source.}
}

@inproceedings{jena_reasoner,
author = {Carroll, Jeremy J. and Dickinson, Ian and Dollin, Chris and Reynolds, Dave and Seaborne, Andy and Wilkinson, Kevin},
title = {Jena: implementing the semantic web recommendations},
year = {2004},
isbn = {1581139128},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1013367.1013381},
doi = {10.1145/1013367.1013381},
abstract = {The new Semantic Web recommendations for RDF, RDFS and OWL have, at their heart, the RDF graph. Jena2, a second-generation RDF toolkit, is similarly centered on the RDF graph. RDFS and OWL reasoning are seen as graph-to-graph transforms, producing graphs of virtual triples. Rich APIs are provided. The Model API includes support for other aspects of the RDF recommendations, such as containers and reification. The Ontology API includes support for RDFS and OWL, including advanced OWL Full support. Jena includes the de facto reference RDF/XML parser, and provides RDF/XML output using the full range of the rich RDF/XML grammar. N3 I/O is supported. RDF graphs can be stored in-memory or in databases. Jena's query language, RDQL, and the Web API are both offered for the next round of standardization.},
booktitle = {Proceedings of the 13th International World Wide Web Conference on Alternate Track Papers \& Posters},
pages = {74–83},
numpages = {10},
keywords = {semantic web, RDQL, RDF, OWL, Jena},
location = {New York, NY, USA},
series = {WWW Alt. '04}
}

@article{hermit,
author = {Glimm, Birte and Horrocks, Ian and Motik, Boris and Stoilos, Giorgos and Wang, Zhe},
title = {HermiT: An OWL 2 Reasoner},
year = {2014},
issue_date = {October   2014},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
volume = {53},
number = {3},
issn = {0168-7433},
url = {https://doi.org/10.1007/s10817-014-9305-1},
doi = {10.1007/s10817-014-9305-1},
abstract = {This system description paper introduces the OWL 2 reasoner HermiT. The reasoner is fully compliant with the OWL 2 Direct Semantics as standardised by the World Wide Web Consortium (W3C). HermiT is based on the hypertableau calculus, and it supports a wide range of standard and novel optimisations that improve the performance of reasoning on real-world ontologies. Apart from the standard OWL 2 reasoning task of entailment checking, HermiT supports several specialised reasoning services such as class and property classification, as well as a range of features outside the OWL 2 standard such as DL-safe rules, SPARQL queries, and description graphs. We discuss the system's architecture, and we present an overview of the techniques used to support the mentioned reasoning tasks. We further compare the performance of reasoning in HermiT with that of FaCT++ and Pellet--two other popular and widely used OWL 2 reasoners.},
journal = {J. Autom. Reason.},
month = {oct},
pages = {245–269},
numpages = {25},
keywords = {Property classification, Optimisations, Ontologies, OWL, Class classification}
}

@article{neurosymbolic_AI,
  author       = {Md. Kamruzzaman Sarker and
                  Lu Zhou and
                  Aaron Eberhart and
                  Pascal Hitzler},
  title        = {Neuro-Symbolic Artificial Intelligence},
  journal      = {AI Communications},
  volume       = {34},
number={3},
 pages        = {197--209},
  year         = {2021},
  
}

@inproceedings{transe,
author = {Bordes, Antoine and Usunier, Nicolas and Garcia-Dur\'{a}n, Alberto and Weston, Jason and Yakhnenko, Oksana},
title = {Translating embeddings for modeling multi-relational data},
year = {2013},
publisher = {Curran Associates Inc.},
address = {Red Hook, NY, USA},
booktitle = {Proceedings of the 26th International Conference on Neural Information Processing Systems - Volume 2},
pages = {2787–2795},
numpages = {9},
location = {Lake Tahoe, Nevada},
series = {NIPS'13}
}

@inproceedings{bert,
    title = "{BERT}: Pre-training of Deep Bidirectional Transformers for Language Understanding",
    author = "Devlin, Jacob  and
      Chang, Ming-Wei  and
      Lee, Kenton  and
      Toutanova, Kristina",
    editor = "Burstein, Jill  and
      Doran, Christy  and
      Solorio, Thamar",
    booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N19-1423",
    doi = "10.18653/v1/N19-1423",
    pages = "4171--4186",
}

@inproceedings{word2vec,
  title={Efficient Estimation of Word Representations in Vector Space},
  author={Tomas Mikolov and Kai Chen and Gregory S. Corrado and Jeffrey Dean},
  booktitle={International Conference on Learning Representations},
  year={2013},
  url={https://api.semanticscholar.org/CorpusID:5959482}
}

@inproceedings{dualboxembeddings,
  edition = {},
  number = {},
  journal = {},
  pages = {},
  publisher = {Association for Computing Machinery},
  school = {},
  title = {Dual box embeddings for the description logic EL++},
  volume = {},
  author = {Jackermeier, M and Chen, J and Horrocks, I},
  editor = {},
  year = {2024},
  organizer = {ACM Web Conference (WWW 2024)},
  series = {}
}

@inproceedings{query_rewriting,
  author       = {Shahla Farzana and
                  Qunzhi Zhou and
                  Petar Ristoski},
  title        = {Knowledge Graph-Enhanced Neural Query Rewriting},
  booktitle    = {Companion Proceedings of the {ACM} Web Conference 2023, {WWW} 2023,
                  Austin, TX, USA, 30 April 2023 - 4 May 2023},
  pages        = {911--919},
  publisher    = {{ACM}},
  year         = {2023},
  url          = {https://doi.org/10.1145/3543873.3587678},
  doi          = {10.1145/3543873.3587678},
  timestamp    = {Wed, 17 May 2023 21:55:44 +0200},
  biburl       = {https://dblp.org/rec/conf/www/FarzanaZR23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{LUBM,
 author = {Guo, Y. and Pan, Z. and Heflin, J.},
 title = {{LUBM}: {A} {B}enchmark for {OWL} {K}nowledge {B}ase {S}ystems},
 journal = {Journal of Web Semantics.},
 issue_date = {October, 2005},
 volume = {\normalfont3},
 number = {2-3},
 year = {2005},
 issn = {1570-8268},
 pages = "158-182",
 numpages = {25},
}

@InProceedings{UOBM,
        author = {Ma, L. and Yang, Y. and  Qiu, Z .and Xie, G. and Pan, Y. and Liu, S.},
        title="{T}owards a {C}omplete {OWL} {O}ntology {B}enchmark",
    booktitle="The Semantic Web: Research and {A}pplications",
    year="2006",
    publisher="Springer Berlin Heidelberg",
    address="Berlin, Heidelberg",
    pages="125--139",
 
}

@inproceedings{wikidata,
author = {Vrande\v{c}i\'{c}, Denny},
title = {Wikidata: A New Platform for Collaborative Data Collection},
year = {2012},
isbn = {9781450312301},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2187980.2188242},
doi = {10.1145/2187980.2188242},
booktitle = {Proceedings of the 21st International Conference on World Wide Web},
pages = {1063–1064},
numpages = {2},
keywords = {wikipedia, semantic web, wikidata, linked data},
location = {Lyon, France},
series = {WWW '12 Companion}
}

@misc{OWL2profile,
	title = {{OWL} 2 {Web} {Ontology} {Language} {Profiles} ({Second} {Edition})},
	author = {Motik, B. and Grau, B. C. and Horrocks, I. and Wu, Zhe. and Fokoue, A. and Lutz, C.},
	url = {https://www.w3.org/TR/owl2-profiles/},
	urldate = {2019-12-09},
	year = {2012}
}

@inproceedings{attention,
  author       = {Ashish Vaswani and
                  Noam Shazeer and
                  Niki Parmar and
                  Jakob Uszkoreit and
                  Llion Jones and
                  Aidan N. Gomez and
                  Lukasz Kaiser and
                  Illia Polosukhin},
  editor       = {Isabelle Guyon and
                  Ulrike von Luxburg and
                  Samy Bengio and
                  Hanna M. Wallach and
                  Rob Fergus and
                  S. V. N. Vishwanathan and
                  Roman Garnett},
  title        = {Attention is All you Need},
  booktitle    = {Advances in Neural Information Processing Systems 30: Annual Conference
                  on Neural Information Processing Systems 2017, December 4-9, 2017,
                  Long Beach, CA, {USA}},
  pages        = {5998--6008},
  year         = {2017},
  url          = {https://proceedings.neurips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html},
  timestamp    = {Thu, 21 Jan 2021 15:15:21 +0100},
  biburl       = {https://dblp.org/rec/conf/nips/VaswaniSPUJGKP17.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@book{jimgray,
  editor       = {Jim Gray},
  title        = {The Benchmark Handbook for Database and Transaction Systems (2nd Edition)},
  publisher    = {Morgan Kaufmann},
  year         = {1993},
  isbn         = {1-55860-292-5},
  timestamp    = {Mon, 06 Nov 2017 16:35:10 +0100},
  biburl       = {https://dblp.org/rec/books/mk/Gray93.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{KG,
  author    = {Aidan Hogan and
               Eva Blomqvist and
               Michael Cochez and
               Claudia d'Amato and
               Gerard de Melo and
               Claudio Gutierrez and
               Sabrina Kirrane and
               Jos{\'{e}} Emilio Labra Gayo and
               Roberto Navigli and
               Sebastian Neumaier and
               Axel{-}Cyrille Ngonga Ngomo and
               Axel Polleres and
               Sabbir M. Rashid and
               Anisa Rula and
               Lukas Schmelzeisen and
               Juan F. Sequeda and
               Steffen Staab and
               Antoine Zimmermann},
  title     = {Knowledge {G}raphs},
  journal   = {{ACM} Computing Surveys},
  volume    = {54},
  number    = {4},
  pages     = {71:1--71:37},
  year      = {2022},
  url       = {https://doi.org/10.1145/3447772},
  doi       = {10.1145/3447772},
  timestamp = {Wed, 23 Nov 2022 16:16:44 +0100},
  biburl    = {https://dblp.org/rec/journals/csur/HoganBCdMGKGNNN21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{nesy_bench,
  author       = {Johanna Ott and
                  Arthur Ledaguenel and
                  C{\'{e}}line Hudelot and
                  Mattis Hartwig},
  editor       = {Artur S. d'Avila Garcez and
                  Tarek R. Besold and
                  Marco Gori and
                  Ernesto Jim{\'{e}}nez{-}Ruiz},
  title        = {How to Think About Benchmarking Neurosymbolic AI?},
  booktitle    = {Proceedings of the 17th International Workshop on Neural-Symbolic
                  Learning and Reasoning, La Certosa di Pontignano, Siena, Italy, July
                  3-5, 2023},
  series       = {{CEUR} Workshop Proceedings},
  volume       = {3432},
  pages        = {248--254},
  publisher    = {CEUR-WS.org},
  year         = {2023},
  url          = {https://ceur-ws.org/Vol-3432/paper22.pdf},
  timestamp    = {Tue, 11 Jul 2023 17:14:10 +0200},
  biburl       = {https://dblp.org/rec/conf/nesy/OttLHH23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@book{Sweb_foundation,
  author    = {Pascal Hitzler and
               Markus Kr{\"{o}}tzsch and
               Sebastian Rudolph},
title = {{F}oundations of {S}emantic {W}eb {T}echnologies},
  publisher = {Chapman and Hall/CRC Press},
  year      = {2010},
  url       = {http://www.semantic-web-book.org/},
  isbn      = {9781420090505},
  timestamp = {Fri, 15 Apr 2016 10:34:38 +0200},
  biburl    = {https://dblp.org/rec/books/crc/Hitzler2010.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{patrick,
  author    = {Patrick Hohenecker and
               Thomas Lukasiewicz},
title = {Ontology {R}easoning with {D}eep {N}eural {N}etworks},
  journal   = {Journal of Artificial Intelligence Research},
  volume    = {68},
  pages     = {503--540},
  year      = {2020},
  url       = {https://doi.org/10.1613/jair.1.11661},
  doi       = {10.1613/jair.1.11661},
  timestamp = {Tue, 21 Jul 2020 00:40:32 +0200},
  biburl    = {https://dblp.org/rec/journals/jair/HoheneckerL20.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{symbolicmaths,
  author       = {Guillaume Lample and
                  Fran{\c{c}}ois Charton},
  title        = {Deep Learning For Symbolic Mathematics},
  booktitle    = {8th International Conference on Learning Representations, {ICLR} 2020,
                  Addis Ababa, Ethiopia, April 26-30, 2020},
  publisher    = {OpenReview.net},
  year         = {2020},
  url          = {https://openreview.net/forum?id=S1eZYeHFDS},
  timestamp    = {Thu, 07 May 2020 17:11:48 +0200},
  biburl       = {https://dblp.org/rec/conf/iclr/LampleC20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{concept_learner,
  author       = {Jiayuan Mao and
                  Chuang Gan and
                  Pushmeet Kohli and
                  Joshua B. Tenenbaum and
                  Jiajun Wu},
  title        = {The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and
                  Sentences From Natural Supervision},
  booktitle    = {7th International Conference on Learning Representations, {ICLR} 2019,
                  New Orleans, LA, USA, May 6-9, 2019},
  publisher    = {OpenReview.net},
  year         = {2019},
  url          = {https://openreview.net/forum?id=rJgMlhRctm},
  timestamp    = {Thu, 25 Jul 2019 13:03:16 +0200},
  biburl       = {https://dblp.org/rec/conf/iclr/MaoGKTW19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{alphago,
  author    = {David Silver and
               Aja Huang and
               Chris J. Maddison and
               Arthur Guez and
               Laurent Sifre and
               George van den Driessche and
               Julian Schrittwieser and
               Ioannis Antonoglou and
               Vedavyas Panneershelvam and
               Marc Lanctot and
               Sander Dieleman and
               Dominik Grewe and
               John Nham and
               Nal Kalchbrenner and
               Ilya Sutskever and
               Timothy P. Lillicrap and
               Madeleine Leach and
               Koray Kavukcuoglu and
               Thore Graepel and
               Demis Hassabis},
  title     = {Mastering the game of {G}o with deep neural networks and tree search},
  journal   = {Nat.},
  volume    = {529},
  number    = {7587},
  pages     = {484--489},
  year      = {2016},
  url       = {https://doi.org/10.1038/nature16961},
  doi       = {10.1038/nature16961},
  timestamp = {Mon, 27 Sep 2021 17:38:59 +0200},
  biburl    = {https://dblp.org/rec/journals/nature/SilverHMGSDSAPL16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{henry,
  author       = {Henry A. Kautz},
  title        = {The Third {AI} Summer: {AAAI} Robert S. Engelmore Memorial Lecture},
  journal      = {{AI} Magazine},
  volume       = {43},
  number       = {1},
  pages        = {93--104},
  year         = {2022},
  url          = {https://doi.org/10.1609/aimag.v43i1.19122},
  doi          = {10.1609/aimag.v43i1.19122},
  timestamp    = {Mon, 25 Apr 2022 08:42:12 +0200},
  biburl       = {https://dblp.org/rec/journals/aim/Kautz22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{Ebrahimi2018ReasoningOR,
  author    = {Monireh Ebrahimi and
               Md. Kamruzzaman Sarker and
               Federico Bianchi and
               Ning Xie and
               Derek Doran and
               Pascal Hitzler},
  title={Reasoning over {RDF} {K}nowledge {B}ases using {D}eep {L}earning},
  journal   = {CoRR},
  volume    = {abs/1811.04132},
  year      = {2018},
  url       = {http://arxiv.org/abs/1811.04132},
  eprinttype = {arXiv},
  eprint    = {1811.04132},
  timestamp = {Sat, 23 Jan 2021 01:12:25 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1811-04132.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{noise-tolerant,
  author    = {Bassem Makni and
               James A. Hendler},
  title     = {Deep learning for noise-tolerant {RDFS} reasoning},
  journal   = {Semantic Web},
  volume    = {10},
  number    = {5},
  pages     = {823--862},
  year      = {2019},
  url       = {https://doi.org/10.3233/SW-190363},
  doi       = {10.3233/SW-190363},
  timestamp = {Thu, 09 Jan 2020 18:51:37 +0100},
  biburl    = {https://dblp.org/rec/journals/semweb/MakniH19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Mondal,
  author    = {Sutapa Mondal and
               Sumit Bhatia and
               Raghava Mutharaju},
  editor    = {Andreas Martin and
               Knut Hinkelmann and
               Hans{-}Georg Fill and
               Aurona Gerber and
               Doug Lenat and
               Reinhard Stolle and
               Frank van Harmelen},
  title={{EmEL}$^{++}$: {E}mbeddings for $\mathcal{EL}^{++}$ {D}escription {L}ogic},
  booktitle = {Proceedings of the {AAAI} 2021 Spring Symposium on Combining Machine
               Learning and Knowledge Engineering {(AAAI-MAKE} 2021), Stanford University,
               Palo Alto, California, USA, March 22-24, 2021},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {2846},
  publisher = {CEUR-WS.org},
  year      = {2021},
  url       = {http://ceur-ws.org/Vol-2846/paper19.pdf},
  timestamp = {Thu, 14 Oct 2021 10:05:18 +0200},
  biburl    = {https://dblp.org/rec/conf/aaaiss/MondalBM21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{ELEm,
  author    = {Maxat Kulmanov and
               Wang Liu{-}Wei and
               Yuan Yan and
               Robert Hoehndorf},
  editor    = {Sarit Kraus},
title = {{EL E}mbeddings: {G}eometric Construction of Models for the {D}escription {L}ogic $\mathcal{EL}^{++}$},
  booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on
               Artificial Intelligence, {IJCAI} 2019, Macao, China, August 10-16,
               2019},
  pages     = {6103--6109},
  publisher = {ijcai.org},
  year      = {2019},
  url       = {https://doi.org/10.24963/ijcai.2019/845},
  doi       = {10.24963/ijcai.2019/845},
  timestamp = {Fri, 27 Mar 2020 09:00:53 +0100},
  biburl    = {https://dblp.org/rec/conf/ijcai/KulmanovLYH19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@incollection{sota1,
  author       = {Gunjan Singh and
                  Sumit Bhatia and
                  Raghava Mutharaju},
  title        = {Neuro-Symbolic {RDF} and Description Logic Reasoners: The State-Of-The-Art
                  and Challenges},
  editor       = {Pascal Hitzler and
                  Md. Kamruzzaman Sarker},
  booktitle    = {Compendium of Neurosymbolic Artificial Intelligence},
  series       = {Frontiers in Artificial Intelligence and Applications},
  volume       = {369},
  pages        = {29--63},
  publisher    = {{IOS} Press},
  year         = {2023},
 isbn      = {978-1-64368-407-9},
  url          = {https://doi.org/10.3233/FAIA230134},
  doi          = {10.3233/FAIA230134},
}

@inproceedings{zero-shot,
  author       = {Jiaoyan Chen and
                  Freddy L{\'{e}}cu{\'{e}} and
                  Yuxia Geng and
                  Jeff Z. Pan and
                  Huajun Chen},
  editor       = {Diego Calvanese and
                  Esra Erdem and
                  Michael Thielscher},
  title        = {Ontology-guided Semantic Composition for Zero-shot Learning},
  booktitle    = {Proceedings of the 17th International Conference on Principles of
                  Knowledge Representation and Reasoning, {KR} 2020, Rhodes, Greece,
                  September 12-18, 2020},
  pages        = {850--854},
  year         = {2020},
  url          = {https://doi.org/10.24963/kr.2020/87},
  doi          = {10.24963/kr.2020/87},
  timestamp    = {Fri, 29 Jan 2021 19:06:03 +0100},
  biburl       = {https://dblp.org/rec/conf/kr/ChenLGPC20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{ILP,
  author       = {Prithviraj Sen and
                  Breno W. S. R. de Carvalho and
                  Ryan Riegel and
                  Alexander G. Gray},
  title        = {Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks},
  booktitle    = {Thirty-Sixth {AAAI} Conference on Artificial Intelligence, {AAAI}
                  2022, Thirty-Fourth Conference on Innovative Applications of Artificial
                  Intelligence, {IAAI} 2022, The Twelveth Symposium on Educational Advances
                  in Artificial Intelligence, {EAAI} 2022 Virtual Event, February 22
                  - March 1, 2022},
  pages        = {8212--8219},
  publisher    = {{AAAI} Press},
  year         = {2022},
  url          = {https://ojs.aaai.org/index.php/AAAI/article/view/20795},
  timestamp    = {Mon, 11 Jul 2022 16:09:32 +0200},
  biburl       = {https://dblp.org/rec/conf/aaai/SenCRG22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{LTN,
  author       = {Samy Badreddine and
                  Artur S. d'Avila Garcez and
                  Luciano Serafini and
                  Michael Spranger},
  title        = {Logic Tensor Networks},
  journal      = {Artif. Intell.},
  volume       = {303},
  pages        = {103649},
  year         = {2022},
  url          = {https://doi.org/10.1016/j.artint.2021.103649},
  doi          = {10.1016/j.artint.2021.103649},
  timestamp    = {Thu, 10 Nov 2022 17:26:23 +0100},
  biburl       = {https://dblp.org/rec/journals/ai/BadreddineGSS22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{XAI,
  author       = {Feiyu Xu and
                  Hans Uszkoreit and
                  Yangzhou Du and
                  Wei Fan and
                  Dongyan Zhao and
                  Jun Zhu},
  editor       = {Jie Tang and
                  Min{-}Yen Kan and
                  Dongyan Zhao and
                  Sujian Li and
                  Hongying Zan},
  title        = {Explainable {AI:} {A} Brief Survey on History, Research Areas, Approaches
                  and Challenges},
  booktitle    = {Natural Language Processing and Chinese Computing - 8th {CCF} International
                  Conference, {NLPCC} 2019, Dunhuang, China, October 9-14, 2019, Proceedings,
                  Part {II}},
  series       = {Lecture Notes in Computer Science},
  volume       = {11839},
  pages        = {563--574},
  publisher    = {Springer},
  year         = {2019},
  url          = {https://doi.org/10.1007/978-3-030-32236-6\_51},
  doi          = {10.1007/978-3-030-32236-6\_51},
  timestamp    = {Thu, 27 Jul 2023 14:33:41 +0200},
  biburl       = {https://dblp.org/rec/conf/nlpcc/XuUDF0Z19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@ARTICLE{GNN,
  author={Scarselli, Franco and Gori, Marco and Tsoi, Ah Chung and Hagenbuchner, Markus and Monfardini, Gabriele},
  journal={IEEE Transactions on Neural Networks}, 
  title={The Graph Neural Network Model}, 
  year={2009},
  volume={20},
  number={1},
  pages={61-80},
  keywords={Neural networks;Biological system modeling;Data engineering;Computer vision;Chemistry;Biology;Pattern recognition;Data mining;Supervised learning;Parameter estimation;Graphical domains;graph neural networks (GNNs);graph processing;recursive neural networks},
  doi={10.1109/TNN.2008.2005605}}

@incollection{sota2,
  author       = {Bassem Makni and
                  Monireh Ebrahimi and
                  Dagmar Gromann and
                  Aaron Eberhart},
  editor       = {Pascal Hitzler and
                  Md. Kamruzzaman Sarker},
  title        = {Neuro-Symbolic Semantic Reasoning},
  booktitle    = {Neuro-Symbolic Artificial Intelligence: The State of the Art},
  series       = {Frontiers in Artificial Intelligence and Applications},
  volume       = {342},
  pages        = {253--279},
 isbn      = {978-1-64368-244-0},
  publisher    = {{IOS} Press},
  year         = {2021},
  url          = {https://doi.org/10.3233/FAIA210358},
  doi          = {10.3233/FAIA210358},
  timestamp    = {Mon, 26 Jun 2023 08:47:46 +0200},
  biburl       = {https://dblp.org/rec/series/faia/MakniEGE21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{emulation,
  author    = {Aaron Eberhart and
               Monireh Ebrahimi and
               Lu Zhou and
               Cogan Shimizu and
               Pascal Hitzler},
  editor    = {Andreas Martin and
               Knut Hinkelmann and
               Hans{-}Georg Fill and
               Aurona Gerber and
               Doug Lenat and
               Reinhard Stolle and
               Frank van Harmelen},
title = {Completion {R}easoning {E}mulation for the {D}escription {L}ogic $\mathcal{EL}^{+}$},
  booktitle = {Proceedings of the {AAAI} 2020 Spring Symposium on Combining Machine
               Learning and Knowledge Engineering in Practice, {AAAI-MAKE} 2020,
               Palo Alto, CA, USA, March 23-25, 2020, Volume {I}},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {2600},
  publisher = {CEUR-WS.org},
  year      = {2020},
  url       = {http://ceur-ws.org/Vol-2600/paper5.pdf},
  timestamp = {Tue, 22 Mar 2022 08:12:12 +0100},
  biburl    = {https://dblp.org/rec/conf/aaaiss/EberhartEZSH20.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

 @article{pointer_nw,
  author    = {Monireh Ebrahimi and
               Aaron Eberhart and
               Pascal Hitzler},
  title={{O}n the {C}apabilities of {P}ointer {N}etworks for {D}eep {D}eductive {R}easoning},
  journal   = {CoRR},
  volume    = {abs/2106.09225},
  year      = {2021},
  url       = {https://arxiv.org/abs/2106.09225},
  eprinttype = {arXiv},
  eprint    = {2106.09225},
  timestamp = {Tue, 29 Jun 2021 16:55:04 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2106-09225.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{faithful_embeddings,
  author    = {Bo Xiong and
               Nico Potyka and
               Trung{-}Kien Tran and
               Mojtaba Nayyeri and
               Steffen Staab},
  editor    = {Ulrike Sattler and
               Aidan Hogan and
               C. Maria Keet and
               Valentina Presutti and
               Jo{\~{a}}o Paulo A. Almeida and
               Hideaki Takeda and
               Pierre Monnin and
               Giuseppe Pirr{\`{o}} and
               Claudia d'Amato},
  title     = {Faithful {E}mbeddings for $\mathcal{EL}^{++}$
               {K}nowledge {B}ases},
  booktitle = {The Semantic Web - {ISWC} 2022 - 21st International Semantic Web Conference,
               Virtual Event, October 23-27, 2022, Proceedings},
  series    = {Lecture Notes in Computer Science},
  volume    = {13489},
  pages     = {22--38},
  publisher = {Springer},
  year      = {2022},
  url       = {https://doi.org/10.1007/978-3-031-19433-7\_2},
  doi       = {10.1007/978-3-031-19433-7\_2},
  timestamp = {Thu, 20 Oct 2022 15:05:18 +0200},
  biburl    = {https://dblp.org/rec/conf/semweb/XiongPTNS22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{why_settle_for_one,
  author    = {Biswesh Mohapatra and
               Sumit Bhatia and
               Raghava Mutharaju and
               G. Srinivasaraghavan},
  title     = {Why {S}ettle for {J}ust {O}ne? {E}xtending $\mathcal{EL}^{++}$ {O}ntology {E}mbeddings with
               {M}any-to-{M}any {R}elationships},
  journal   = {CoRR},
  volume    = {abs/2110.10555},
  year      = {2021},
  url       = {https://arxiv.org/abs/2110.10555},
  eprinttype = {arXiv},
  eprint    = {2110.10555},
  timestamp = {Fri, 06 May 2022 08:22:59 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2110-10555.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{cone_semantics,
  author    = {{\"{O}}zg{\"{u}}r L{\"{u}}tf{\"{u}} {\"{O}}z{\c{c}}ep and
               Mena Leemhuis and
               Diedrich Wolter},
  editor    = {Christian Bessiere},
 title     = {Cone {S}emantics for {L}ogics with {N}egation},
  booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
               Artificial Intelligence, {IJCAI} 2020},
  pages     = {1820--1826},
  publisher = {ijcai.org},
  year      = {2020},
  url       = {https://doi.org/10.24963/ijcai.2020/252},
  doi       = {10.24963/ijcai.2020/252},
  timestamp = {Sun, 02 Oct 2022 16:08:04 +0200},
  biburl    = {https://dblp.org/rec/conf/ijcai/OzcepLW20.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{dl_sroiq,
  author    = {Ian Horrocks and
               Oliver Kutz and
               Ulrike Sattler},
  editor    = {Patrick Doherty and
               John Mylopoulos and
               Christopher A. Welty},
  title     = {The {E}ven {M}ore {I}rresistible {SROIQ}},
  booktitle = {Proceedings, Tenth International Conference on Principles of Knowledge
               Representation and Reasoning, Lake District of the United Kingdom,
               June 2-5, 2006},
  pages     = {57--67},
  publisher = {{AAAI} Press},
  year      = {2006},
  url       = {http://www.aaai.org/Library/KR/2006/kr06-009.php},
  timestamp = {Tue, 12 Apr 2022 14:46:29 +0200},
  biburl    = {https://dblp.org/rec/conf/kr/HorrocksKS06.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@book{dlbook,
  editor    = {Franz Baader and
               Diego Calvanese and
               Deborah L. McGuinness and
               Daniele Nardi and
               Peter F. Patel{-}Schneider},
title = {The {D}escription {L}ogic {H}andbook: {T}heory, {I}mplementation, and {A}pplications},
  publisher = {Cambridge University Press},
  year      = {2003},
  isbn      = {0-521-78176-0},
  timestamp = {Mon, 20 Nov 2017 13:02:05 +0100},
  biburl    = {https://dblp.org/rec/conf/dlog/2003handbook.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{owl2bench,
  author    = {Gunjan Singh and
               Sumit Bhatia and
               Raghava Mutharaju},
  editor    = {Jeff Z. Pan and
               Valentina A. M. Tamma and
               Claudia d'Amato and
               Krzysztof Janowicz and
               Bo Fu and
               Axel Polleres and
               Oshani Seneviratne and
               Lalana Kagal},
title="{OWL2B}ench: {A} {B}enchmark for {OWL 2 R}easoners",
  booktitle = {The Semantic Web - {ISWC} 2020 - 19th International Semantic Web Conference,
               Athens, Greece, November 2-6, 2020, Proceedings, Part {II}},
  series    = {Lecture Notes in Computer Science},
  volume    = {12507},
  pages     = {81--96},
  publisher = {Springer},
  year      = {2020},
  url       = {https://doi.org/10.1007/978-3-030-62466-8\_6},
  doi       = {10.1007/978-3-030-62466-8\_6},
  timestamp = {Fri, 25 Dec 2020 01:15:04 +0100},
  biburl    = {https://dblp.org/rec/conf/semweb/SinghBM20.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{neuro_symbolic,
  author    = {Artur S. d'Avila Garcez and
               Tarek R. Besold and
               Luc De Raedt and
               Peter F{\"{o}}ldi{\'{a}}k and
               Pascal Hitzler and
               Thomas Icard and
               Kai{-}Uwe K{\"{u}}hnberger and
               Lu{\'{\i}}s C. Lamb and
               Risto Miikkulainen and
               Daniel L. Silver},
title = {Neural-{S}ymbolic {L}earning and {R}easoning: {C}ontributions and {C}hallenges},
  booktitle = {2015 {AAAI} Spring Symposia, Stanford University, Palo Alto, California,
               USA, March 22-25, 2015},
  publisher = {{AAAI} Press},
  year      = {2015},
  url       = {http://www.aaai.org/ocs/index.php/SSS/SSS15/paper/view/10281},
  timestamp = {Wed, 14 Nov 2018 14:18:25 +0100},
  biburl    = {https://dblp.org/rec/conf/aaaiss/GarcezBRFHIKLMS15.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{dl_primer,
  author    = {Markus Kr{\"{o}}tzsch and
               Frantisek Simancik and
               Ian Horrocks},
  title     = {A {D}escription {L}ogic {P}rimer},
  journal   = {CoRR},
  volume    = {abs/1201.4089},
  year      = {2012},
  url       = {http://arxiv.org/abs/1201.4089},
  eprinttype = {arXiv},
  eprint    = {1201.4089},
  timestamp = {Tue, 12 Apr 2022 14:46:29 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1201-4089.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{DL_for_OR,
  author    = {Patrick Hohenecker and
               Thomas Lukasiewicz},
  title     = {Deep {L}earning for {O}ntology {R}easoning},
  journal   = {CoRR},
  volume    = {abs/1705.10342},
  year      = {2017},
  url       = {http://arxiv.org/abs/1705.10342},
  eprinttype = {arXiv},
  eprint    = {1705.10342},
  timestamp = {Mon, 13 Aug 2018 16:46:53 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/HoheneckerL17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{ORE,
  author    = {Bijan Parsia and
               Nicolas Matentzoglu and
               Rafael S. Gon{\c{c}}alves and
               Birte Glimm and
               Andreas Steigmiller},
title = {{T}he {OWL} {R}easoner {E}valuation ({ORE}) 2015 {C}ompetition {R}eport},
  journal   = {Journal of Automated Reasoning},
  volume    = {59},
  number    = {4},
  pages     = {455--482},
  year      = {2017},
  url       = {https://doi.org/10.1007/s10817-017-9406-8},
  doi       = {10.1007/s10817-017-9406-8},
  timestamp = {Tue, 06 Sep 2022 08:18:33 +0200},
  biburl    = {https://dblp.org/rec/journals/jar/ParsiaMGGS17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{Explainable_rdfs_reasoning,
  author    = {Bassem Makni and
               Ibrahim Abdelaziz and
               James A. Hendler},
  title     = {Explainable Deep {RDFS} Reasoner},
  journal   = {CoRR},
volume={abs/2002.03514},
  year      = {2020},
  url       = {https://arxiv.org/abs/2002.03514},
  eprinttype = {arXiv},
  eprint    = {2002.03514},
  timestamp = {Wed, 12 Feb 2020 16:38:55 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2002-03514.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{QuantumEmbedding,
  author    = {Dinesh Garg and
               Shajith Ikbal and
               Santosh K. Srivastava and
               Harit Vishwakarma and
               Hima P. Karanam and
               L. Venkata Subramaniam},
  editor    = {Hanna M. Wallach and
               Hugo Larochelle and
               Alina Beygelzimer and
               Florence d'Alch{\'{e}}{-}Buc and
               Emily B. Fox and
               Roman Garnett},
 title = {Quantum {E}mbedding of {K}nowledge for {R}easoning},
  booktitle = {Advances in Neural Information Processing Systems 32: Annual Conference
               on Neural Information Processing Systems 2019, NeurIPS 2019, December
               8-14, 2019, Vancouver, BC, Canada},
  pages     = {5595--5605},
  year      = {2019},
  url       = {https://proceedings.neurips.cc/paper/2019/hash/cb12d7f933e7d102c52231bf62b8a678-Abstract.html},
  timestamp = {Mon, 16 May 2022 15:41:51 +0200},
  biburl    = {https://dblp.org/rec/conf/nips/GargISVKS19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{yago,
author = {Suchanek, Fabian M. and Kasneci, Gjergji and Weikum, Gerhard},
title = {{YAGO}: {A C}ore of {S}emantic {K}nowledge {U}nifying {W}ord{N}et and {W}ikipedia},
year = {2007},
isbn = {9781595936547},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1242572.1242667},
doi = {10.1145/1242572.1242667},
booktitle = {Proceedings of the 16th International Conference on World Wide Web},
pages = {697–706},
numpages = {10},
keywords = {WordNet, wikipedia},
location = {Banff, Alberta, Canada},
series = {WWW '07}
}

@article{dbpedia,
author = {Lehmann, Jens and Isele, Robert and Jakob, Max and Jentzsch, Anja and Kontokostas, Dimitris and Mendes, Pablo and Hellmann, Sebastian and Morsey, Mohamed and Van Kleef, Patrick and Auer, Sören and Bizer, Christian},
year = {2014},
month = {01},
title = {DBpedia - {A L}arge-scale, {M}ultilingual {K}nowledge {B}ase {E}xtracted from {W}ikipedia},
volume = {6},
journal = {Semantic Web Journal},
doi = {10.3233/SW-140134}
}

@article{owl2,
  author    = {Bernardo Cuenca Grau and
               Ian Horrocks and
               Boris Motik and
               Bijan Parsia and
               Peter F. Patel{-}Schneider and
               Ulrike Sattler},
  title     = {{OWL} 2: The next step for {OWL}},
  journal   = {Journal of Web Semantics},
  volume    = {6},
  number    = {4},
  pages     = {309--322},
  year      = {2008},
  url       = {https://doi.org/10.1016/j.websem.2008.05.001},
  doi       = {10.1016/j.websem.2008.05.001},
  timestamp = {Tue, 12 Apr 2022 14:46:29 +0200},
  biburl    = {https://dblp.org/rec/journals/ws/GrauHMPPS08.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@misc{RDF,
title = {{Resource} {Description} {Framework} {(RDF)}},
	author = {Klyne, G. and J. Carroll, J. and McBride, B.}, 
	url = {https://www.w3.org/TR/rdf11-concepts/},
	urldate = {2022-11-29},
	year = {2015}
}


@inproceedings{singh_benchmarking_iswc23,
  author       = {Gunjan Singh},
  editor       = {Claudia d'Amato and
                  Jeff Z. Pan},
  title        = {Benchmarking Symbolic and Neuro-Symbolic Description Logic Reasoners},
  booktitle    = {Proceedings of the Doctoral Consortium at {ISWC} 2023 co-located with
                  22nd International Semantic Web Conference {(ISWC} 2023), Athens,
                  Greece, November 7, 2023},
  series       = {{CEUR} Workshop Proceedings},
  volume       = {3678},
  publisher    = {CEUR-WS.org},
  year         = {2023},
  url          = {https://ceur-ws.org/Vol-3678/paper11.pdf},
  timestamp    = {Mon, 13 May 2024 08:44:02 +0200},
  biburl       = {https://dblp.org/rec/conf/semweb/Singh23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
@misc{Singh_Mutharaju_Bhatia_Tommasini, url={https://neurosymbolic-ai-journal.com/system/files/nai-paper-774_0.pdf}, title={Benchmarking Neuro-Symbolic Reasoners: Existing Challenges and A Way Forward}, journal={Neurosymbolic Artificial Intelligence}, author={Singh, Gunjan and Mutharaju, Raghava and Bhatia, Sumit and Tommasini, Ricardo}} 

@article{YU2023105,
title = {A survey on neural-symbolic learning systems},
journal = {Neural Networks},
volume = {166},
pages = {105-126},
year = {2023},
issn = {0893-6080},
doi = {https://doi.org/10.1016/j.neunet.2023.06.028},
url = {https://www.sciencedirect.com/science/article/pii/S0893608023003398},
author = {Dongran Yu and Bo Yang and Dayou Liu and Hui Wang and Shirui Pan},
keywords = {Neural-symbolic learning systems, Neural networks, Symbolic reasoning, Symbols, Logic, Knowledge graphs},
abstract = {In recent years, neural systems have demonstrated highly effective learning ability and superior perception intelligence. However, they have been found to lack effective reasoning and cognitive ability. On the other hand, symbolic systems exhibit exceptional cognitive intelligence but suffer from poor learning capabilities when compared to neural systems. Recognizing the advantages and disadvantages of both methodologies, an ideal solution emerges: combining neural systems and symbolic systems to create neural-symbolic learning systems that possess powerful perception and cognition. The purpose of this paper is to survey the advancements in neural-symbolic learning systems from four distinct perspectives: challenges, methods, applications, and future directions. By doing so, this research aims to propel this emerging field forward, offering researchers a comprehensive and holistic overview. This overview will not only highlight the current state-of-the-art but also identify promising avenues for future research.}
}

@article{10.1007/s10489-020-02165-6,
author = {Ebrahimi, Monireh and Eberhart, Aaron and Bianchi, Federico and Hitzler, Pascal},
title = {Towards bridging the neuro-symbolic gap: deep deductive reasoners},
year = {2021},
issue_date = {Sep 2021},
publisher = {Kluwer Academic Publishers},
address = {USA},
volume = {51},
number = {9},
issn = {0924-669X},
url = {https://doi.org/10.1007/s10489-020-02165-6},
doi = {10.1007/s10489-020-02165-6},
abstract = {Symbolic knowledge representation and reasoning and deep learning are fundamentally different approaches to artificial intelligence with complementary capabilities. The former are transparent and data-efficient, but they are sensitive to noise and cannot be applied to non-symbolic domains where the data is ambiguous. The latter can learn complex tasks from examples, are robust to noise, but are black boxes; require large amounts of –not necessarily easily obtained– data, and are slow to learn and prone to adversarial examples. Either paradigm excels at certain types of problems where the other paradigm performs poorly. In order to develop stronger AI systems, integrated neuro-symbolic systems that combine artificial neural networks and symbolic reasoning are being sought. In this context, one of the fundamental open problems is how to perform logic-based deductive reasoning over knowledge bases by means of trainable artificial neural networks. This paper provides a brief summary of the authors’ recent efforts to bridge the neural and symbolic divide in the context of deep deductive reasoners. Throughout the paper we will discuss strengths and limitations of models in term of accuracy, scalability, transferability, generalizabiliy, speed, and interpretability, and finally, will talk about possible modifications to enhance desirable capabilities. More specifically, in terms of architectures, we are looking at Memory-augmented networks, Logic Tensor Networks, and compositions of LSTM models to explore their capabilities and limitations in conducting deductive reasoning. We are applying these models on Resource Description Framework (RDF), first-order logic, and the description logic EL+ respectively.},
journal = {Applied Intelligence},
month = {sep},
pages = {6326–6348},
numpages = {23},
keywords = {Neuro-symbolic reasoning, Deep deductive reasoners, Memory-augmented networks, Logic tensor networks, LSTM, Logic}
}

@article{STEIGMILLER201478,
title = {Konclude: System description},
journal = {Journal of Web Semantics},
volume = {27-28},
pages = {78-85},
year = {2014},
note = {Semantic Web Challenge 2013},
issn = {1570-8268},
doi = {https://doi.org/10.1016/j.websem.2014.06.003},
url = {https://www.sciencedirect.com/science/article/pii/S157082681400047X},
author = {Andreas Steigmiller and Thorsten Liebig and Birte Glimm},
keywords = {Web ontology language, Description logics, Tableau theorem proving}
}

@article{deng2012mnist,
  title={The mnist database of handwritten digit images for machine learning research},
  author={Deng, Li},
  journal={IEEE Signal Processing Magazine},
  volume={29},
  number={6},
  pages={141--142},
  year={2012},
  publisher={IEEE}
}

@misc{1606.01540,
  Author = {Greg Brockman and Vicki Cheung and Ludwig Pettersson and Jonas Schneider and John Schulman and Jie Tang and Wojciech Zaremba},
  Title = {OpenAI Gym},
  Year = {2016},
  Eprint = {arXiv:1606.01540},
}

@misc{wang2019glue,
      title={GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding}, 
      author={Alex Wang and Amanpreet Singh and Julian Michael and Felix Hill and Omer Levy and Samuel R. Bowman},
      year={2019},
      eprint={1804.07461},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@inproceedings{gunjan,
  author    = {Singh, Gunjan},
  title     = {Benchmarking Symbolic and Neuro-Symbolic
               Description Logic Reasoners},
  year      = {2023},
  organization = {Doctoral Consortium at International Semantic Web Conference}
}

@article{gcn,
  author    = {Thomas N. Kipf and
               Max Welling},
  title     = {Semi-Supervised Classification with Graph Convolutional Networks},
  journal   = {CoRR},
  volume    = {abs/1609.02907},
  year      = {2016},
  url       = {http://arxiv.org/abs/1609.02907},
  eprinttype = {arXiv},
  eprint    = {1609.02907},
  timestamp = {Mon, 13 Aug 2018 16:48:31 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/KipfW16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@misc{rgcn,
      title={Modeling Relational Data with Graph Convolutional Networks}, 
      author={Michael Schlichtkrull and Thomas N. Kipf and Peter Bloem and Rianne van den Berg and Ivan Titov and Max Welling},
      year={2017},
      eprint={1703.06103},
      archivePrefix={arXiv},
      primaryClass={stat.ML}
}

@article{noise_taxonomy,
author = {Anke, Luis Espinosa and Declerck, Thierry and Gromann, Dagmar and Makni, Bassem and Hendler, James and Gromann, Dagmar and Espinosa Anke, Luis and Declerck, Thierry},
title = {Deep learning for noise-tolerant RDFS reasoning},
year = {2019},
issue_date = {2019},
publisher = {IOS Press},
address = {NLD},
volume = {10},
number = {5},
issn = {1570-0844},
url = {https://doi.org/10.3233/SW-190363},
doi = {10.3233/SW-190363},
abstract = {Since the 2001 envisioning of the Semantic Web (SW) (Scientific American 284(5) (2001) 34–43), the main research focus in SW reasoning has been on the soundness and completeness of reasoners. While these reasoners assume the veracity of input data, the reality is that the Web of data is inherently noisy. Although there has been recent work on noise-tolerant reasoning, it has focused on type inference rather than full RDFS reasoning. Even though RDFS closure generation can be seen as a Knowledge Graph (KG) completion problem, the problem setting is different&nbsp;– making KG embedding techniques that were designed for link prediction not suitable for RDFS reasoning. This paper documents a novel approach that extends noise-tolerance in the SW to full RDFS reasoning. Our embedding technique&nbsp;– that is tailored for RDFS reasoning&nbsp;– consists of layering RDF graphs and encoding them in the form of 3D adjacency matrices where each layer layout forms a graph word. Each input graph and its entailments are then represented as sequences of graph words, and RDFS inference can be formulated as translation of these graph words sequences, achieved through neural machine translation. Our evaluation on LUBM1 synthetic dataset shows 97 \% validation accuracy and 87.76 \% on a subset of DBpedia while demonstrating a noise-tolerance unavailable with rule-based reasoners.},
journal = {Semant. Web},
month = {jan},
pages = {823–862},
numpages = {40},
keywords = {graph words, neural machine translation, noise-tolerance, RDFS reasoning, Semantic Web, Deep learning}
}

@misc{owl2vec*,
      title={OWL2Vec*: Embedding of OWL Ontologies}, 
      author={Jiaoyan Chen and Pan Hu and Ernesto Jimenez-Ruiz and Ole Magnus Holter and Denvar Antonyrajah and Ian Horrocks},
      year={2021},
      eprint={2009.14654},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}

@misc{box2el,
      title={Dual Box Embeddings for the Description Logic EL++}, 
      author={Mathias Jackermeier and Jiaoyan Chen and Ian Horrocks},
      year={2024},
      eprint={2301.11118},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}

@article{raji2021ai,
  author       = {Inioluwa Deborah Raji and
                  Emily M. Bender and
                  Amandalynne Paullada and
                  Emily Denton and
                  Alex Hanna},
  title        = {{AI} and the Everything in the Whole Wide World Benchmark},
  journal      = {CoRR},
  volume       = {abs/2111.15366},
  year         = {2021},
  url          = {https://arxiv.org/abs/2111.15366},
  eprinttype    = {arXiv},
  eprint       = {2111.15366},
  timestamp    = {Thu, 02 Dec 2021 10:50:44 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2111-15366.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{mowl,
       author = {Zhapa-Camacho, Fernando and Kulmanov, Maxat and Hoehndorf, Robert},
       title = "{mOWL: Python library for machine learning with biomedical ontologies}",
       journal = {Bioinformatics},
       year = {2022},
       month = {12},
       issn = {1367-4803},
       doi = {10.1093/bioinformatics/btac811},
       url = {https://doi.org/10.1093/bioinformatics/btac811},
       note = {btac811},
       eprint = {https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btac811/48438324/btac811.pdf},
       }

@inproceedings{garcez2015neural,
  title={Neural-symbolic learning and reasoning: contributions and challenges},
  author={Garcez, Artur d'Avila and Besold, Tarek R and De Raedt, Luc and F{\"o}ldiak, Peter and Hitzler, Pascal and Icard, Thomas and K{\"u}hnberger, Kai-Uwe and Lamb, Luis C and Miikkulainen, Risto and Silver, Daniel L},
  booktitle={2015 AAAI Spring Symposium Series},
  year={2015}
}

@inproceedings{liu2024knowledge,
  title={Knowledge graph error detection with contrastive confidence adaption},
  author={Liu, Xiangyu and Liu, Yang and Hu, Wei},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={38},
  number={8},
  pages={8824--8831},
  year={2024}
}
