Presentation | 1995/7/21 Adaptive Scaling of a Semantic Space Hideki Kozima, Akira Ito, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper proposes a computationally feasible method for measuring context-sensitive semantic distance between words. The distance is computed by adaptive scaling of the semantic space where each word in the vocabulary V is represented by a multi-dimensional Q-vector. The vectors are obtained through a principal component analysis on the P-vectors generated from an English dictionary. Given a word set C which specified a context, each dimension of the semantic space is scaled up or down according to the distribution of C on the dimension. In the scaled space, word distance becomes sensitive to the context which comes out from C. An evaluation through word prediction shows that the proposed distance works well as an context-sensitive word distance. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | semantic distance / word similarity / association / thesauri / context processing |
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Conference Information | |
Committee | NLC |
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Conference Date | 1995/7/21(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Natural Language Understanding and Models of Communication (NLC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Adaptive Scaling of a Semantic Space |
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Keyword(1) | semantic distance |
Keyword(2) | word similarity |
Keyword(3) | association |
Keyword(4) | thesauri |
Keyword(5) | context processing |
1st Author's Name | Hideki Kozima |
1st Author's Affiliation | Kansai Advanced Research Center Communications Research Laboratory() |
2nd Author's Name | Akira Ito |
2nd Author's Affiliation | Kansai Advanced Research Center Communications Research Laboratory |
Date | 1995/7/21 |
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Volume (vol) | vol.95 |
Number (no) | 169 |
Page | pp.pp.- |
#Pages | 8 |
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