Taxonomy beats corpus in similarity identification, but does it matter?

M.N. Lê, A.S. Fokkens

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

We present extensive evaluations comparing the performance of taxonomy-based and corpus-based approaches on SimLex- 999. The results confirm our hypothesis that taxonomy-based approaches are more suitable to identify similarity. We introduce two new measures of evaluation that show that all measures perform well on a coarse-grained evaluation and that it is not always clear which approach is most suitable when a similarity score is used as a threshold. This leads us to conclude that the inferior performance of corpus-based approaches may not (always) matter.
Original languageEnglish
Title of host publicationInternational Conference Recent Advances in NLP 2015
EditorsG. Angelova, K. Bontcheva, R. Mitkov
PublisherINCOMA Ltd
Pages346-355
ISBN (Print)ISSN 1313-8502
Publication statusPublished - 2015
EventRecent Advances in NLP -
Duration: 7 Sep 20149 Sep 2015

Conference

ConferenceRecent Advances in NLP
Period7/09/149/09/15

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