ExTaSem! Extending, taxonomizing and semantifying domain terminologies

Espinosa-Anke, Luis ORCID: https://orcid.org/0000-0001-6830-9176, Saggion, Horacio, Ronzano, Francesco and Navigli, Roberto 2016. ExTaSem! Extending, taxonomizing and semantifying domain terminologies. Presented at: Thirtieth AAAI Conference on Artificial Intelligence, Phoenix, AZ, USA, 12-17 February 2016. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence. AAAI, pp. 2594-2600.

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Abstract

We introduce EXTASEM!, a novel approach for the automatic learning of lexical taxonomies from domain terminologies. First, we exploit a very large semantic network to collect thousands of in-domain textual definitions. Second, we extract (hyponym, hypernym) pairs from each definition with a CRF-based algorithm trained on manuallyvalidated data. Finally, we introduce a graph induction procedure which constructs a full-fledged taxonomy where each edge is weighted according to its domain pertinence. EXTASEM! achieves state-of-the-art results in the following taxonomy evaluation experiments: (1) Hypernym discovery, (2) Reconstructing gold standard taxonomies, and (3) Taxonomy quality according to structural measures. We release weighted taxonomies for six domains for the use and scrutiny of the community.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	AAAI
Date of Acceptance:	1 January 2016
Last Modified:	26 Oct 2022 08:25
URI:	https://orca.cardiff.ac.uk/id/eprint/127411

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