Automatic Ontology Population Task
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An Automatic Ontology Population Task is an ontology population task that is an closed automatic information extraction task.
- AKA: Corpus-based Ontology Population.
- Context:
- It can be solved by a Corpus-based Ontology Population System that applies an (Corpus-based Ontology Population Algorithm.
- See: Ontology Design Task, IE Task.
References
2016
- http://cacm.acm.org/magazines/2016/9/206254-a-new-look-at-the-semantic-web/fulltext
- QUOTE: Latent semantics: Obviously, there is a lot of semantics that is already on the Web, albeit mostly in text, or in data that machines cannot readily interpret. To complement formally developed ontologies, we must be able to extract latent, evidence-based models that capture the way that users structure their knowledge implicitly. We need to explore these questions: How much of the semantics can we learn automatically and what is the quality of the resulting knowledge? As ontologies are learned or enhanced automatically, what is the very meaning of "formal ontologies"? How do we develop some notion of approximate correctness? Do similar or different reasoning mechanisms apply to the ontologies that are extracted in this way? How do crowdsourcing approaches allow us to capture semantics that may be less precise but more reflective of the collective wisdom?
2010
- (Wimalasuriya & Dou, 2010) ⇒ Daya C. Wimalasuriya, and Dejing Dou. (2010). “Ontology-based information extraction: An introduction and a survey of current approaches.” In: Journal of Information Science, 36(3). doi:10.1177/0165551509360123
- (Wei, Barnaghi & Bargiela, 2010) ⇒ Wang Wei and Payam Barnaghi and Andrzej Bargiela. (2010). “Probabilistic Topic Models for Learning Terminological Ontologies.” In: IEEE Transactions on Knowledge and Data Engineering (TKDE), 22(7). doi:10.1109/TKDE.2009.122
2009
- (Wimalasuriya & Dou, 2009) ⇒ Daya C. Wimalasuriya, and Dejing Dou. (2009). “Using Multiple Ontologies in Information Extraction.” In: Proceedings of the Eighteenth Conference on Information and Knowledge Management (CIKM 2009) doi:10.1145/1645953.1645985
2008
- (Buitelaar et al., 2008) ⇒ Paul Buitelaar, Philipp Cimiano, Anette Frank, Matthias Hartung, and Stefania Racioppa. (2008). “Ontology-based Information Extraction and Integration from Heterogeneous Data Sources.” In: International Journal of Human-Computer Studies, 66(11).
2006
- (Magnini et al., 2006) ⇒ Bernardo Magnini, Emanuele Pianta, Octavian Popescu, and Manuela Speranza. (2006). “Ontology Population from Textual Mentions: Task Definition and Benchmark.” In: Proceedings of the Ontology Population and Learning Workshop at ACL/Coling 2006.
- (Maynard et al., 2006) ⇒ Diana Maynard, Wim Peters, and Yaoyong Li. (2006). “Metrics for Evaluation of Ontology-based Information Extraction.” In: WWW 2006 Workshop on Evaluation of Ontologies for the Web (EON 2006).
- (Tanev & Magnini, 2006) ⇒ Hristo Tanev, and Bernardo Magnini. (2006). “Weakly Supervised Approaches for Ontology Population.” In: Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2006).
2003
- (Popov et al., 2003) ⇒ Borislav Popov, Atanas Kiryakov, Damyan Ognyanoff, Dimitar Manov, Angel Kirilov, and Damyan Goranov, (2003). “KIM - Semantic Annotation Platform.” In: Proceedings of the 2nd International Semantic Web Conference.