Unsupervised techniques for discovering ontology elements from Wikipedia article links

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dc.contributor.authorSyed, Zareen
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-11-14T17:11:22Z
dc.date.available2018-11-14T17:11:22Z
dc.date.issued2010-06-06
dc.descriptionNAACL Workshop on Formalisms and Methodology for Learning by Readingen_US
dc.description.abstractWe present an unsupervised and unrestricted approach to discovering an infobox like ontology by exploiting the inter-article links within Wikipedia. It discovers new slots and fillers that may not be available in the Wikipedia infoboxes. Our results demonstrate that there are certain types of properties that are evident in the link structure of resources like Wikipedia that can be predicted with high accuracy using little or no linguistic analysis. The discovered properties can be further used to discover a class hierarchy. Our experiments have focused on analyzing people in Wikipedia, but the techniques can be directly applied to other types of entities in text resources that are rich with hyperlinks.en_US
dc.description.urihttps://ebiquity.umbc.edu/paper/html/id/475/Unsupervised-techniques-for-discovering-ontology-elements-from-Wikipedia-article-linksen_US
dc.format.extent9 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/M2S46H953
dc.identifier.citationZareen Syed and Tim Finin, Unsupervised techniques for discovering ontology elements from Wikipedia article links, Proceedings of the First International Workshop on Formalisms and Methodology for Learning by Reading, 2010. https://aclanthology.org/W10-0910/.en_US
dc.identifier.urihttp://hdl.handle.net/11603/11975
dc.language.isoen_USen_US
dc.publisherAssociation for Computational Linguisticsen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectlearningen_US
dc.subjectnatural language processingen_US
dc.subjectwikipediaen_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleUnsupervised techniques for discovering ontology elements from Wikipedia article linksen_US
dc.typeTexten_US

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