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Distributional term set expansion
RISE - Research Institutes of Sweden, ICT, SICS.
RISE - Research Institutes of Sweden, ICT, SICS.ORCID iD: 0000-0001-5100-0535
2018 (English)In: LREC 2018 - 11th International Conference on Language Resources and Evaluation, 2018, p. 2554-2558Conference paper, Published paper (Refereed)
Abstract [en]

This paper is a short empirical study of the performance of centrality and classification based iterative term set expansion methods for distributional semantic models. Iterative term set expansion is an interactive process using distributional semantics models where a user labels terms as belonging to some sought after term set, and a system uses this labeling to supply the user with new, candidate, terms to label, trying to maximize the number of positive examples found. While centrality based methods have a long history in term set expansion (Sarmento et al., 2007; Pantel et al., 2009), we compare them to classification methods based on the the Simple Margin method, an Active Learning approach to classification using Support Vector Machines (Tong and Koller, 2002). Examining the performance of various centrality and classification based methods for a variety of distributional models over five different term sets, we can show that active learning based methods consistently outperform centrality based methods.

Place, publisher, year, edition, pages
2018. p. 2554-2558
Keywords [en]
Active Learning, Distributional Semantics, Lexicon Acquisition, Term Set Expansion, Word Embeddings, Artificial intelligence, Semantics, Embeddings, Set expansions, Iterative methods
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-37335Scopus ID: 2-s2.0-85059894892ISBN: 9791095546009 (print)OAI: oai:DiVA.org:ri-37335DiVA, id: diva2:1281522
Conference
11th International Conference on Language Resources and Evaluation, LREC 2018, 7 May 2018 through 12 May 2018
Available from: 2019-01-22 Created: 2019-01-22 Last updated: 2019-01-25Bibliographically approved

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Sahlgren, Magnus

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
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More styles
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  • Other locale
More languages
Output format
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