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New Measures to Investigate Term Typology by Distributional Data
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0003-4042-4919
2013 (English)In: Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013), May 22–24, 2013, Oslo University, Norway. NEALT Proceedings Series 16 / [ed] Stephan Oepen, Kristin Hagen, Janne Bondi Johannessen, Linköping: Linköping University Electronic Press, 2013Conference paper, Poster (Refereed)
Abstract [en]

This report describes a series of exploratory experiments to establish whether terms of different semantic type can be distinguished in useful ways in a semantic space constructed from distributional data. The hypotheses explored in this paper are that some words are more variant in their distribution than others; that the varying semantic character of words will be reflected in their distribution; and this distributional difference is encoded in current distributional models, but that the information is not accessible through the methods typically used in application of them. This paper proposes some new measures to explore variation encoded in distributional models but not usually put to use in understanding the character of words represented in them. These exploratory findings show that some proposed measures show a wide range of variation across words of various types.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2013.
Keyword [en]
Term typology, distributional semantics
National Category
Language Technology (Computational Linguistics)
URN: urn:nbn:se:kth:diva-122920ISBN: 1650-3740OAI: diva2:624092
19th Nordic Conference of Computational Linguistics (NODALIDA 2013)
Swedish Research Council

QC 20130710

Available from: 2013-05-30 Created: 2013-05-30 Last updated: 2013-07-10Bibliographically approved

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