cmput696 Readings - Denilson Barbosa

Overview

E. Hovy, R. Navigli, and S. P. Ponzetto. Collaboratively built semi-structured content and artificial intelligence: the story so far. Artif. Intell., 194:2–27, January 2013. doi:10.1016/j.artint.2012.10.002. [Bibtex]

@article{Hovy_2013_CBS_2405838_2405907,
    author = "Hovy, Eduard and Navigli, Roberto and Ponzetto, Simone Paolo",
    title = "Collaboratively Built Semi-structured Content and Artificial Intelligence: The Story So Far",
    journal = "Artif. Intell.",
    issue_date = "January, 2013",
    volume = "194",
    month = "January",
    year = "2013",
    issn = "0004-3702",
    pages = "2--27",
    numpages = "26",
    doi = "10.1016/j.artint.2012.10.002",
    acmid = "2405907",
    publisher = "Elsevier Science Publishers Ltd.",
    address = "Essex, UK",
    keywords = "Knowledge acquisition, Knowledge-rich methods, Semantic networks"
}

G. Weikum, X. L. Dong, S. Razniewski, and F. M. Suchanek. Machine knowledge: creation and curation of comprehensive knowledge bases. Found. Trends Databases, 10(2-4):108–490, 2021. URL: https://doi.org/10.1561/1900000064, doi:10.1561/1900000064. [Bibtex]

@article{WeikumDRS21,
    author = "Weikum, Gerhard and Dong, Xin Luna and Razniewski, Simon and Suchanek, Fabian M.",
    title = "Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases",
    journal = "Found. Trends Databases",
    volume = "10",
    number = "2-4",
    pages = "108--490",
    year = "2021",
    url = "https://doi.org/10.1561/1900000064",
    doi = "10.1561/1900000064",
    timestamp = "Thu, 05 Aug 2021 17:55:26 +0200",
    biburl = "https://dblp.org/rec/journals/ftdb/WeikumDRS21.bib",
    bibsource = "dblp computer science bibliography, https://dblp.org"
}

J. Sequeda and O. Lassila. Designing and building enterprise knowledge graphs. Synthesis Lectures on Data, Semantics, and Knowledge, 11(1):1–165, 2021. [Bibtex]

@article{sequeda2021designing,
    author = "Sequeda, Juan and Lassila, Ora",
    title = "Designing and Building Enterprise Knowledge Graphs",
    journal = "Synthesis Lectures on Data, Semantics, and Knowledge",
    volume = "11",
    number = "1",
    pages = "1--165",
    year = "2021",
    publisher = "Morgan \& Claypool Publishers"
}

KG Construction

J. Lehmann, R. Isele, M. Jakob, A. Jentzsch, D. Kontokostas, P. N. Mendes, S. Hellmann, M. Morsey, P. van Kleef, S. Auer, and C. Bizer. Dbpedia - A large-scale, multilingual knowledge base extracted from wikipedia. Semantic Web, 6(2):167–195, 2015. doi:10.3233/SW-140134. [Bibtex] [PDF]

@article{LehmannIJJKMHMK15,
    author = {Lehmann, Jens and Isele, Robert and Jakob, Max and Jentzsch, Anja and Kontokostas, Dimitris and Mendes, Pablo N. and Hellmann, Sebastian and Morsey, Mohamed and van Kleef, Patrick and Auer, S{\"{o}}ren and Bizer, Christian},
    title = "DBpedia - {A} large-scale, multilingual knowledge base extracted from Wikipedia",
    journal = "Semantic Web",
    volume = "6",
    number = "2",
    pages = "167--195",
    year = "2015",
    doi = "10.3233/SW-140134",
    pdf = "http://svn.aksw.org/papers/2013/SWJ_DBpedia/public.pdf",
    timestamp = "Wed, 11 Mar 2015 14:46:32 +0100",
    biburl = "http://dblp.uni-trier.de/rec/bib/journals/semweb/LehmannIJJKMHMK15",
    bibsource = "dblp computer science bibliography, http://dblp.org"
}

E. Muñoz, A. Hogan, and A. Mileo. Using linked data to mine rdf from wikipedia's tables. In Proceedings of the 7th ACM international conference on Web search and data mining, 533–542. ACM, 2014. [Bibtex] [PDF]

@inproceedings{munoz2014using,
    author = "Mu{\~n}oz, Emir and Hogan, Aidan and Mileo, Alessandra",
    title = "Using linked data to mine RDF from wikipedia's tables",
    booktitle = "Proceedings of the 7th ACM international conference on Web search and data mining",
    pages = "533--542",
    year = "2014",
    organization = "ACM",
    PDF = "https://dl.acm.org/citation.cfm?doid=2556195.2556266"
}

J. Hoffart, F. M. Suchanek, K. Berberich, and G. Weikum. Yago2: a spatially and temporally enhanced knowledge base from wikipedia. Artif. Intell., 194:28–61, 2013. doi:10.1016/j.artint.2012.06.001. [Bibtex]

@article{Hoffart_etal_JAI2013,
    author = "Hoffart, Johannes and Suchanek, Fabian M. and Berberich, Klaus and Weikum, Gerhard",
    title = "YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia",
    journal = "Artif. Intell.",
    volume = "194",
    pages = "28--61",
    year = "2013",
    doi = "10.1016/j.artint.2012.06.001"
}

T. Mitchell, W. Cohen, E. Hruschka, P. Talukdar, J. Betteridge, A. Carlson, B. Dalvi, M. Gardner, B. Kisiel, J. Krishnamurthy, N. Lao, K. Mazaitis, T. Mohamed, N. Nakashole, E. Platanios, A. Ritter, M. Samadi, B. Settles, R. Wang, D. Wijaya, A. Gupta, X. Chen, A. Saparov, M. Greaves, and J. Welling. Never-ending learning. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15). 2015. [Bibtex] [PDF]

@inproceedings{NELL-aaai15,
    Author = "Mitchell, T. and Cohen, W. and Hruschka, E. and Talukdar, P. and Betteridge, J. and Carlson, A. and Dalvi, B. and Gardner, M. and Kisiel, B. and Krishnamurthy, J. and Lao, N. and Mazaitis, K. and Mohamed, T. and Nakashole, N. and Platanios, E. and Ritter, A. and Samadi, M. and Settles, B. and Wang, R. and Wijaya, D. and Gupta, A. and Chen, X. and Saparov, A. and Greaves, M. and Welling, J.",
    Title = "Never-Ending Learning",
    Booktitle = "Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15)",
    Year = "2015",
    pdf = "https://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/download/10049/9557"
}

R. Navigli and S. P. Ponzetto. Babelnet: the automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artificial Intelligence, 193:217–250, 2012. URL: https://www.sciencedirect.com/science/article/pii/S0004370212000793. [Bibtex] [PDF]

@article{navigli2012babelnet,
    author = "Navigli, Roberto and Ponzetto, Simone Paolo",
    title = "BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network",
    journal = "Artificial Intelligence",
    volume = "193",
    pages = "217--250",
    year = "2012",
    publisher = "Elsevier",
    url = "https://www.sciencedirect.com/science/article/pii/S0004370212000793",
    pdf = "http://wwwusers.di.uniroma1.it/~navigli/pubs/AIJ_2012_Navigli_Ponzetto.pdf"
}

S. Wu, L. Hsiao, X. Cheng, B. Hancock, T. Rekatsinas, P. Levis, and C. Ré. Fonduer: knowledge base construction from richly formatted data. In Proceedings of the 2018 International Conference on Management of Data, 1301–1316. 2018. URL: https://dl.acm.org/doi/abs/10.1145/3183713.3183729. [Bibtex] [PDF]

@inproceedings{wu2018fonduer,
    author = "Wu, Sen and Hsiao, Luke and Cheng, Xiao and Hancock, Braden and Rekatsinas, Theodoros and Levis, Philip and R{\'e}, Christopher",
    title = "Fonduer: Knowledge base construction from richly formatted data",
    booktitle = "Proceedings of the 2018 International Conference on Management of Data",
    pages = "1301--1316",
    year = "2018",
    pdf = "https://dawn.cs.stanford.edu/pubs/fonduer-sigmod2018.pdf",
    url = "https://dl.acm.org/doi/abs/10.1145/3183713.3183729"
}

X. Dong, E. Gabrilovich, G. Heitz, W. Horn, N. Lao, K. Murphy, T. Strohmann, S. Sun, and W. Zhang. Knowledge vault: a web-scale approach to probabilistic knowledge fusion. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '14, 601–610. New York, NY, USA, 2014. ACM. doi:10.1145/2623330.2623623. [Bibtex]

@inproceedings{Dong_2014_KVW_2623330_2623623,
    author = "Dong, Xin and Gabrilovich, Evgeniy and Heitz, Geremy and Horn, Wilko and Lao, Ni and Murphy, Kevin and Strohmann, Thomas and Sun, Shaohua and Zhang, Wei",
    title = "Knowledge Vault: A Web-scale Approach to Probabilistic Knowledge Fusion",
    booktitle = "Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
    series = "KDD '14",
    year = "2014",
    isbn = "978-1-4503-2956-9",
    location = "New York, New York, USA",
    pages = "601--610",
    numpages = "10",
    doi = "10.1145/2623330.2623623",
    acmid = "2623623",
    publisher = "ACM",
    address = "New York, NY, USA",
    keywords = "information extraction, knowledge bases, machine learning, probabilistic models"
}

H. Paulheim. Knowledge graph refinement: a survey of approaches and evaluation methods. Semantic web, 8(3):489–508, 2017. [Bibtex] [PDF]

@article{paulheim2017knowledge,
    author = "Paulheim, Heiko",
    title = "Knowledge graph refinement: A survey of approaches and evaluation methods",
    journal = "Semantic web",
    volume = "8",
    number = "3",
    pages = "489--508",
    year = "2017",
    publisher = "IOS Press",
    PDF = "http://semantic-web-journal.net/system/files/swj1167.pdf"
}

R. Xie, Z. Liu, J. Jia, H. Luan, and M. Sun. Representation learning of knowledge graphs with entity descriptions. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, AAAI'16, 2659–2665. AAAI Press, 2016. URL: http://dl.acm.org/citation.cfm?id=3016100.3016273. [Bibtex] [PDF]

@inproceedings{Xie_et_al_2016_AAAI,
    author = "Xie, Ruobing and Liu, Zhiyuan and Jia, Jia and Luan, Huanbo and Sun, Maosong",
    title = "Representation Learning of Knowledge Graphs with Entity Descriptions",
    booktitle = "Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence",
    series = "AAAI'16",
    year = "2016",
    location = "Phoenix, Arizona",
    pages = "2659--2665",
    numpages = "7",
    url = "http://dl.acm.org/citation.cfm?id=3016100.3016273",
    acmid = "3016273",
    publisher = "AAAI Press",
    PDF = "http://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/download/12216/12004"
}

M. Cannaviccio, D. Barbosa, and P. Merialdo. Accurate fact harvesting from natural language text in wikipedia with lector. In Proceedings of the 19th International Workshop on Web and Databases, San Francisco, CA, USA, June 26, 2016, 9. ACM, 2016. doi:10.1145/2932194.2932203. [Bibtex]

@inproceedings{CannaviccioBM_WebDB2016,
    author = "Cannaviccio, Matteo and Barbosa, Denilson and Merialdo, Paolo",
    title = "Accurate fact harvesting from natural language text in wikipedia with Lector",
    booktitle = "Proceedings of the 19th International Workshop on Web and Databases, San Francisco, CA, USA, June 26, 2016",
    pages = "9",
    publisher = "{ACM}",
    year = "2016",
    doi = "10.1145/2932194.2932203",
    timestamp = "Mon, 20 Jun 2016 08:34:57 +0200",
    biburl = "http://dblp.uni-trier.de/rec/bib/conf/webdb/CannaviccioBM16",
    bibsource = "dblp computer science bibliography, http://dblp.org"
}

R. Socher, D. Chen, C. D. Manning, and A. Ng. Reasoning with neural tensor networks for knowledge base completion. In C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K. Q. Weinberger, editors, Advances in Neural Information Processing Systems 26, pages 926–934. Curran Associates, Inc., 2013. URL: http://papers.nips.cc/paper/5028-reasoning-with-neural-tensor-networks-for-knowledge-base-completion.pdf. [Bibtex]

@incollection{neuralTensorNetworksNIPS2013,
    author = "Socher, Richard and Chen, Danqi and Manning, Christopher D and Ng, Andrew",
    editor = "Burges, C. J. C. and Bottou, L. and Welling, M. and Ghahramani, Z. and Weinberger, K. Q.",
    title = "Reasoning With Neural Tensor Networks for Knowledge Base Completion",
    booktitle = "Advances in Neural Information Processing Systems 26",
    pages = "926--934",
    year = "2013",
    publisher = "Curran Associates, Inc.",
    url = "http://papers.nips.cc/paper/5028-reasoning-with-neural-tensor-networks-for-knowledge-base-completion.pdf"
}

Neural Methods for KG construction

M. E. Peters, M. Neumann, R. Logan, R. Schwartz, V. Joshi, S. Singh, and N. A. Smith. Knowledge enhanced contextual word representations. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 43–54. Hong Kong, China, November 2019. Association for Computational Linguistics. URL: https://www.aclweb.org/anthology/D19-1005, doi:10.18653/v1/D19-1005. [Bibtex]

@inproceedings{peters-etal-2019-knowledge,
    author = "Peters, Matthew E. and Neumann, Mark and Logan, Robert and Schwartz, Roy and Joshi, Vidur and Singh, Sameer and Smith, Noah A.",
    title = "Knowledge Enhanced Contextual Word Representations",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
    month = "November",
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-1005",
    doi = "10.18653/v1/D19-1005",
    pages = "43--54",
    abstract = "Contextual word representations, typically trained on unstructured, unlabeled text, do not contain any explicit grounding to real world entities and are often unable to remember facts about those entities. We propose a general method to embed multiple knowledge bases (KBs) into large scale models, and thereby enhance their representations with structured, human-curated knowledge. For each KB, we first use an integrated entity linker to retrieve relevant entity embeddings, then update contextual word representations via a form of word-to-entity attention. In contrast to previous approaches, the entity linkers and self-supervised language modeling objective are jointly trained end-to-end in a multitask setting that combines a small amount of entity linking supervision with a large amount of raw text. After integrating WordNet and a subset of Wikipedia into BERT, the knowledge enhanced BERT (KnowBert) demonstrates improved perplexity, ability to recall facts as measured in a probing task and downstream performance on relationship extraction, entity typing, and word sense disambiguation. KnowBert{'}s runtime is comparable to BERT{'}s and it scales to large KBs."
}

B. Ding, Q. Wang, B. Wang, and L. Guo. Improving knowledge graph embedding using simple constraints. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 110–121. Melbourne, Australia, July 2018. Association for Computational Linguistics. URL: https://www.aclweb.org/anthology/P18-1011, doi:10.18653/v1/P18-1011. [Bibtex]

@inproceedings{ding-etal-2018-improving,
author = "Ding, Boyang and Wang, Quan and Wang, Bin and Guo, Li",
title = "Improving Knowledge Graph Embedding Using Simple Constraints",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = "July",
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/P18-1011",
doi = "10.18653/v1/P18-1011",
pages = "110--121",
abstract = "Embedding knowledge graphs (KGs) into continuous vector spaces is a focus of current research. Early works performed this task via simple models developed over KG triples. Recent attempts focused on either designing more complicated triple scoring models, or incorporating extra information beyond triples. This paper, by contrast, investigates the potential of using very simple constraints to improve KG embedding. We examine non-negativity constraints on entity representations and approximate entailment constraints on relation representations. The former help to learn compact and interpretable representations for entities. The latter further encode regularities of logical entailment between relations into their distributed representations. These constraints impose prior beliefs upon the structure of the embedding space, without negative impacts on efficiency or scalability. Evaluation on WordNet, Freebase, and DBpedia shows that our approach is simple yet surprisingly effective, significantly and consistently outperforming competitive baselines. The constraints imposed indeed improve model interpretability, leading to a substantially increased structuring of the embedding space. Code and data are available at \url{https://github.com/iieir-km/ComplEx-NNE_AER}."
}

M. Nickel, K. Murphy, V. Tresp, and E. Gabrilovich. A review of relational machine learning for knowledge graphs. Proceedings of the IEEE, 104(1):11–33, 2016. [Bibtex] [PDF]

@article{nickel2016review,
    author = "Nickel, Maximilian and Murphy, Kevin and Tresp, Volker and Gabrilovich, Evgeniy",
    title = "A review of relational machine learning for knowledge graphs",
    journal = "Proceedings of the IEEE",
    volume = "104",
    number = "1",
    pages = "11--33",
    year = "2016",
    publisher = "IEEE",
    PDF = "https://arxiv.org/pdf/1503.00759.pdf"
}

A. Bordes, N. Usunier, A. Garcia-Duran, J. Weston, and O. Yakhnenko. Translating embeddings for modeling multi-relational data. In Advances in neural information processing systems, 2787–2795. 2013. [Bibtex] [PDF]

@inproceedings{bordes2013translating,
    author = "Bordes, Antoine and Usunier, Nicolas and Garcia-Duran, Alberto and Weston, Jason and Yakhnenko, Oksana",
    title = "Translating embeddings for modeling multi-relational data",
    booktitle = "Advances in neural information processing systems",
    pages = "2787--2795",
    year = "2013",
    PDF = "http://papers.nips.cc/paper/5071-translating-embeddings-for-modeling-multi-relational-data.pdf"
}

M. Nickel, V. Tresp, and H.-P. Kriegel. Factorizing yago: scalable machine learning for linked data. In Proceedings of the 21st International Conference on World Wide Web, WWW '12, 271–280. New York, NY, USA, 2012. ACM. URL: http://doi.acm.org/10.1145/2187836.2187874, doi:10.1145/2187836.2187874. [Bibtex]

@inproceedings{Nickel_et_al_2012,
    author = "Nickel, Maximilian and Tresp, Volker and Kriegel, Hans-Peter",
    title = "Factorizing YAGO: Scalable Machine Learning for Linked Data",
    booktitle = "Proceedings of the 21st International Conference on World Wide Web",
    series = "WWW '12",
    year = "2012",
    isbn = "978-1-4503-1229-5",
    location = "Lyon, France",
    pages = "271--280",
    numpages = "10",
    url = "http://doi.acm.org/10.1145/2187836.2187874",
    doi = "10.1145/2187836.2187874",
    acmid = "2187874",
    publisher = "ACM",
    address = "New York, NY, USA",
    keywords = "large-scale machine learning, linked open data, relational learning, semantic web, tensor factorization"
}

S. Riedel, L. Yao, and A. McCallum. Modeling relations and their mentions without labeled text. Machine learning and knowledge discovery in databases, pages 148–163, 2010. [Bibtex] [PDF]

@article{riedel2010modeling,
    author = "Riedel, Sebastian and Yao, Limin and McCallum, Andrew",
    title = "Modeling relations and their mentions without labeled text",
    journal = "Machine learning and knowledge discovery in databases",
    pages = "148--163",
    year = "2010",
    publisher = "Springer",
    PDF = "https://link.springer.com/content/pdf/10.1007/978-3-642-15939-8_10.pdf"
}

Ontology-induction

Z. Kozareva and E. H. Hovy. A semi-supervised method to learn and construct taxonomies using the web. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, EMNLP 2010, 9-11 October 2010, MIT Stata Center, Massachusetts, USA, A meeting of SIGDAT, a Special Interest Group of the ACL, 1110–1118. ACL, 2010. [Bibtex] [PDF]

@inproceedings{KozarevaHovy_EMNLP_2010,
    author = "Kozareva, Zornitsa and Hovy, Eduard H.",
    title = "A Semi-Supervised Method to Learn and Construct Taxonomies Using the Web",
    booktitle = "Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, {EMNLP} 2010, 9-11 October 2010, {MIT} Stata Center, Massachusetts, USA, {A} meeting of SIGDAT, a Special Interest Group of the {ACL}",
    pages = "1110--1118",
    publisher = "{ACL}",
    year = "2010",
    pdf = "http://www.aclweb.org/anthology/D10-1108",
    timestamp = "Tue, 18 Jan 2011 11:52:24 +0100",
    biburl = "http://dblp.uni-trier.de/rec/bib/conf/emnlp/KozarevaH10",
    bibsource = "dblp computer science bibliography, http://dblp.org"
}

R. Snow, D. Jurafsky, and A. Y. Ng. Semantic taxonomy induction from heterogenous evidence. In N. Calzolari, C. Cardie, and P. Isabelle, editors, ACL 2006, 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, Sydney, Australia, 17-21 July 2006. The Association for Computer Linguistics, 2006. [Bibtex] [PDF]

@inproceedings{SnowJN_ACL_2006,
    author = "Snow, Rion and Jurafsky, Daniel and Ng, Andrew Y.",
    editor = "Calzolari, Nicoletta and Cardie, Claire and Isabelle, Pierre",
    title = "Semantic Taxonomy Induction from Heterogenous Evidence",
    booktitle = "{ACL} 2006, 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, Sydney, Australia, 17-21 July 2006",
    publisher = "The Association for Computer Linguistics",
    year = "2006",
    pdf = "http://aclweb.org/anthology/P06-1101",
    timestamp = "Mon, 04 Mar 2013 20:57:24 +0100",
    biburl = "http://dblp.uni-trier.de/rec/bib/conf/acl/SnowJN06",
    bibsource = "dblp computer science bibliography, http://dblp.org"
}

R. Snow, D. Jurafsky, and A. Y. Ng. Learning syntactic patterns for automatic hypernym discovery. In Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, NIPS 2004, December 13-18, 2004, Vancouver, British Columbia, Canada], 1297–1304. 2004. [Bibtex] [PDF]

@inproceedings{SnowJN_NIPS_2004,
    author = "Snow, Rion and Jurafsky, Daniel and Ng, Andrew Y.",
    title = "Learning Syntactic Patterns for Automatic Hypernym Discovery",
    booktitle = "Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, {NIPS} 2004, December 13-18, 2004, Vancouver, British Columbia, Canada]",
    pages = "1297--1304",
    year = "2004",
    pdf = "http://papers.nips.cc/paper/2659-learning-syntactic-patterns-for-automatic-hypernym-discovery.pdf",
    timestamp = "Thu, 11 Dec 2014 17:34:08 +0100",
    biburl = "http://dblp.uni-trier.de/rec/bib/conf/nips/SnowJN04",
    bibsource = "dblp computer science bibliography, http://dblp.org"
}

M. A. Hearst. Automatic acquisition of hyponyms from large text corpora. In Proceedings of the 14th conference on Computational linguistics-Volume 2, 539–545. Association for Computational Linguistics, 1992. [Bibtex] [PDF]

@inproceedings{hearst1992automatic,
    author = "Hearst, Marti A",
    title = "Automatic acquisition of hyponyms from large text corpora",
    booktitle = "Proceedings of the 14th conference on Computational linguistics-Volume 2",
    pages = "539--545",
    year = "1992",
    pdf = "http://www.anthology.aclweb.org/C/C92/C92-2082.pdf",
    organization = "Association for Computational Linguistics"
}

Relation identification

O. Levy, M. Seo, E. Choi, and L. Zettlemoyer. Zero-shot relation extraction via reading comprehension. In Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 333–342. Vancouver, Canada, August 2017. Association for Computational Linguistics. URL: https://www.aclweb.org/anthology/K17-1034, doi:10.18653/v1/K17-1034. [Bibtex]

@inproceedings{levy-etal-2017-zero,
    author = "Levy, Omer and Seo, Minjoon and Choi, Eunsol and Zettlemoyer, Luke",
    title = "Zero-Shot Relation Extraction via Reading Comprehension",
    booktitle = "Proceedings of the 21st Conference on Computational Natural Language Learning ({C}o{NLL} 2017)",
    month = "August",
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/K17-1034",
    doi = "10.18653/v1/K17-1034",
    pages = "333--342",
    abstract = "We show that relation extraction can be reduced to answering simple reading comprehension questions, by associating one or more natural-language questions with each relation slot. This reduction has several advantages: we can (1) learn relation-extraction models by extending recent neural reading-comprehension techniques, (2) build very large training sets for those models by combining relation-specific crowd-sourced questions with distant supervision, and even (3) do zero-shot learning by extracting new relation types that are only specified at test-time, for which we have no labeled training examples. Experiments on a Wikipedia slot-filling task demonstrate that the approach can generalize to new questions for known relation types with high accuracy, and that zero-shot generalization to unseen relation types is possible, at lower accuracy levels, setting the bar for future work on this task."
}

F. Mesquita, J. Schmidek, and D. Barbosa. Effectiveness and efficiency of open relation extraction. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 447–457. Association for Computational Linguistics, October 2013. [Bibtex] [PDF]

@inproceedings{Mesquita_etal_EMNLP2013,
    Author = "Mesquita, Filipe and Schmidek, Jordan and Barbosa, Denilson",
    Booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing",
    Month = "October",
    Pages = "447--457",
    Pdf = "http://www.aclweb.org/anthology/D13-1043",
    Publisher = "Association for Computational Linguistics",
    Title = "Effectiveness and Efficiency of Open Relation Extraction",
    Year = "2013"
}

M. Mintz, S. Bills, R. Snow, and D. Jurafsky. Distant supervision for relation extraction without labeled data. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2, ACL '09, 1003–1011. Stroudsburg, PA, USA, 2009. Association for Computational Linguistics. [Bibtex] [PDF]

@inproceedings{Mintz_2009_DSR_1690219_1690287,
    author = "Mintz, Mike and Bills, Steven and Snow, Rion and Jurafsky, Dan",
    title = "Distant Supervision for Relation Extraction Without Labeled Data",
    booktitle = "Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2",
    series = "ACL '09",
    year = "2009",
    isbn = "978-1-932432-46-6",
    location = "Suntec, Singapore",
    pages = "1003--1011",
    numpages = "9",
    pdf = "http://web.stanford.edu/~jurafsky/mintz.pdf",
    acmid = "1690287",
    publisher = "Association for Computational Linguistics",
    address = "Stroudsburg, PA, USA"
}

Named Entity Recognition/Disambiguation

Z. Guo and D. Barbosa. Robust named entity disambiguation with random walks. Semantic Web, 9(4):459–479, 2018. doi:10.3233/SW-170273. [Bibtex] [PDF]

@article{Guo_Barbosa_2018,
    author = "Guo, Zhaochen and Barbosa, Denilson",
    title = "Robust named entity disambiguation with random walks",
    journal = "Semantic Web",
    volume = "9",
    number = "4",
    pages = "459--479",
    year = "2018",
    doi = "10.3233/SW-170273",
    pdf = "http://webdocs.cs.ualberta.ca/~denilson/files/publications/swj1511.pdf"
}

J. Hoffart, M. A. Yosef, I. Bordino, H. Furstenau, M. Pinkal, M. Spaniol, B. Taneva, S. Thater, and G. Weikum. Robust disambiguation of named entities in text. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, 782–792. 2011. URL: http://www.aclweb.org/anthology/D11-1072. [Bibtex]

@inproceedings{Hoffart_AIDA_EMNLP11,
    author = "Hoffart, Johannes and Yosef, Mohamed Amir and Bordino, Ilaria and Furstenau, Hagen and Pinkal, Manfred and Spaniol, Marc and Taneva, Bilyana and Thater, Stefan and Weikum, Gerhard",
    title = "Robust Disambiguation of Named Entities in Text",
    booktitle = "Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, EMNLP 2011",
    pages = "782--792",
    year = "2011",
    url = "http://www.aclweb.org/anthology/D11-1072",
    biburl = "http://dblp.uni-trier.de/rec/bib/conf/emnlp/HoffartYBFPSTTW11",
    bibsource = "dblp computer science bibliography, http://dblp.org"
}

Web Tables

M. Cannaviccio, D. Barbosa, and P. Merialdo. Towards annotating relational data on the web with language models. In Proceedings of The Web Conference 2018, 1307–1316. 2018. doi:10.1145/3178876.3186029. [Bibtex] [PDF]

@inproceedings{Cannaviccio_et_al_2018,
    author = "Cannaviccio, Matteo and Barbosa, Denilson and Merialdo, Paolo",
    title = "Towards Annotating Relational Data on the Web with Language Models",
    booktitle = "Proceedings of The Web Conference 2018",
    pages = "1307--1316",
    year = "2018",
    doi = "10.1145/3178876.3186029",
    PDF = "http://webdocs.cs.ualberta.ca/~denilson/files/publications/CannaviccioBM_WWW2018.pdf"
}

V. Efthymiou, O. Hassanzadeh, M. Rodriguez-Muro, and V. Christophides. Matching web tables with knowledge base entities: from entity lookups to entity embeddings. In International Semantic Web Conference, 260–277. Springer, 2017. [Bibtex] [PDF]

@inproceedings{efthymiou2017matching,
    author = "Efthymiou, Vasilis and Hassanzadeh, Oktie and Rodriguez-Muro, Mariano and Christophides, Vassilis",
    title = "Matching web tables with knowledge base entities: From entity lookups to entity embeddings",
    booktitle = "International Semantic Web Conference",
    pages = "260--277",
    year = "2017",
    organization = "Springer",
    PDF = "https://link.springer.com/chapter/10.1007/978-3-319-68288-4_16"
}

D. Ritze, O. Lehmberg, and C. Bizer. Matching HTML tables to dbpedia. In Proceedings of the 5th International Conference on Web Intelligence, Mining and Semantics, 10. ACM, 2015. [Bibtex] [PDF]

@inproceedings{ritze2015matching,
    author = "Ritze, Dominique and Lehmberg, Oliver and Bizer, Christian",
    title = "Matching {HTML} tables to dbpedia",
    booktitle = "Proceedings of the 5th International Conference on Web Intelligence, Mining and Semantics",
    pages = "10",
    year = "2015",
    organization = "ACM",
    PDF = "https://dl.acm.org/citation.cfm?id=2797118"
}

Question Answering

R. Das, M. Zaheer, S. Reddy, and A. McCallum. Question answering on knowledge bases and text using universal schema and memory networks. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 358–365. Vancouver, Canada, July 2017. Association for Computational Linguistics. URL: https://www.aclweb.org/anthology/P17-2057, doi:10.18653/v1/P17-2057. [Bibtex]

@inproceedings{das_etal_2017_question,
    author = "Das, Rajarshi and Zaheer, Manzil and Reddy, Siva and McCallum, Andrew",
    title = "Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks",
    booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
    month = "July",
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/P17-2057",
    doi = "10.18653/v1/P17-2057",
    pages = "358--365",
    abstract = "Existing question answering methods infer answers either from a knowledge base or from raw text. While knowledge base (KB) methods are good at answering compositional questions, their performance is often affected by the incompleteness of the KB. Au contraire, web text contains millions of facts that are absent in the KB, however in an unstructured form. Universal schema can support reasoning on the union of both structured KBs and unstructured text by aligning them in a common embedded space. In this paper we extend universal schema to natural language question answering, employing Memory networks to attend to the large body of facts in the combination of text and KB. Our models can be trained in an end-to-end fashion on question-answer pairs. Evaluation results on Spades fill-in-the-blank question answering dataset show that exploiting universal schema for question answering is better than using either a KB or text alone. This model also outperforms the current state-of-the-art by 8.5 F1 points."
}

D. Savenkov and E. Agichtein. When a knowledge base is not enough: question answering over knowledge bases with external text data. In Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 235–244. ACM, 2016. doi:10.1145/2911451.2911536. [Bibtex] [PDF]

@inproceedings{savenkov2016knowledge,
    author = "Savenkov, Denis and Agichtein, Eugene",
    title = "When a knowledge base is not enough: Question answering over knowledge bases with external text data",
    booktitle = "Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval",
    pages = "235--244",
    year = "2016",
    organization = "ACM",
    DOI = "10.1145/2911451.2911536",
    PDF = "https://dl.acm.org/citation.cfm?id=2911536"
}

M. Yahya, D. Barbosa, K. Berberich, Q. Wang, and G. Weikum. Relationship queries on extended knowledge graphs. In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, San Francisco, CA, USA, February 22-25, 2016, 605–614. ACM, 2016. doi:10.1145/2835776.2835795. [Bibtex] [PDF]

@inproceedings{Yahya_etal_WSDM2016,
    author = "Yahya, Mohamed and Barbosa, Denilson and Berberich, Klaus and Wang, Qiuyue and Weikum, Gerhard",
    title = "Relationship Queries on Extended Knowledge Graphs",
    booktitle = "Proceedings of the Ninth {ACM} International Conference on Web Search and Data Mining, San Francisco, CA, USA, February 22-25, 2016",
    pages = "605--614",
    publisher = "{ACM}",
    year = "2016",
    doi = "10.1145/2835776.2835795",
    timestamp = "Mon, 08 Feb 2016 15:38:27 +0100",
    biburl = "http://dblp.uni-trier.de/rec/bib/conf/wsdm/YahyaBBWW16",
    bibsource = "dblp computer science bibliography, http://dblp.org",
    pdf = "http://webdocs.cs.ualberta.ca/~denilson/files/publications/p605-yahya.pdf"
}

K. Xu, S. Reddy, Y. Feng, S. Huang, and D. Zhao. Question answering on freebase via relation extraction and textual evidence. arXiv preprint arXiv:1603.00957, 2016. [Bibtex] [PDF]

@article{xu2016question,
    author = "Xu, Kun and Reddy, Siva and Feng, Yansong and Huang, Songfang and Zhao, Dongyan",
    title = "Question answering on freebase via relation extraction and textual evidence",
    journal = "arXiv preprint arXiv:1603.00957",
    year = "2016",
    PDF = "https://arxiv.org/pdf/1603.00957.pdf"
}

L. He, M. Lewis, and L. Zettlemoyer. Question-answer driven semantic role labeling: using natural language to annotate natural language. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015, Lisbon, Portugal, September 17-21, 2015, 643–653. 2015. [Bibtex] [PDF]

@inproceedings{HeLZ_EMNLP2015,
    author = "He, Luheng and Lewis, Mike and Zettlemoyer, Luke",
    title = "Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language",
    booktitle = "Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015, Lisbon, Portugal, September 17-21, 2015",
    pages = "643--653",
    year = "2015",
    PDF = "http://aclweb.org/anthology/D/D15/D15-1076.pdf"
}

A. Fader, L. Zettlemoyer, and O. Etzioni. Open question answering over curated and extracted knowledge bases. In The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '14, New York, NY, USA - August 24 - 27, 2014, 1156–1165. 2014. doi:10.1145/2623330.2623677. [Bibtex]

@inproceedings{FaderZE_KDD2014,
    author = "Fader, Anthony and Zettlemoyer, Luke and Etzioni, Oren",
    title = "Open question answering over curated and extracted knowledge bases",
    booktitle = "The 20th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining, {KDD} '14, New York, NY, {USA} - August 24 - 27, 2014",
    pages = "1156--1165",
    year = "2014",
    doi = "10.1145/2623330.2623677",
    timestamp = "Wed, 24 Sep 2014 13:01:28 +0200",
    biburl = "http://dblp.uni-trier.de/rec/bib/conf/kdd/FaderZE14",
    bibsource = "dblp computer science bibliography, http://dblp.org"
}

J. Berant, A. Chou, R. Frostig, and P. Liang. Semantic parsing on freebase from question-answer pairs. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013, 18-21 October 2013, Grand Hyatt Seattle, Seattle, Washington, USA, A meeting of SIGDAT, a Special Interest Group of the ACL, 1533–1544. ACL, 2013. URL: http://aclweb.org/anthology/D/D13/D13-1160.pdf. [Bibtex]

@inproceedings{BerantCFL_EMNLP2013,
    author = "Berant, Jonathan and Chou, Andrew and Frostig, Roy and Liang, Percy",
    title = "Semantic Parsing on Freebase from Question-Answer Pairs",
    booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, {EMNLP} 2013, 18-21 October 2013, Grand Hyatt Seattle, Seattle, Washington, USA, {A} meeting of SIGDAT, a Special Interest Group of the {ACL}",
    pages = "1533--1544",
    publisher = "{ACL}",
    year = "2013",
    url = "http://aclweb.org/anthology/D/D13/D13-1160.pdf",
    timestamp = "Fri, 22 Nov 2013 12:57:23 +0100",
    biburl = "http://dblp.uni-trier.de/rec/bib/conf/emnlp/BerantCFL13",
    bibsource = "dblp computer science bibliography, http://dblp.org"
}