Presentation 2002/6/27
The Method of Constructing Concept Vectors for Information Retrieval
Minoru SASAKI, Takashi OTANI, Kenji KITA,
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Abstract(in English) Text documents are often represented as high-dimensional and sparse vectors using words as features in a multidimensional space. These vectors require a large number of computer resources and it is difficult to capture underlying concepts referred to by the terms. In this paper, we propose to use the technique of dimensionality reduction using Concept Vectors Based on PDDP as a way of solving these problems in the vector space information retrieval model. we give experimental results of the dimensionality reduction by using this method and show that this method is an improvement over conventional vector space model.
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Keyword(in English) Information retrieval / Vector space model / Random projection / Latent semantic indexing / Concept vector
Paper # NLP2002-32
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Conference Information
Committee NLP
Conference Date 2002/6/27(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) The Method of Constructing Concept Vectors for Information Retrieval
Sub Title (in English)
Keyword(1) Information retrieval
Keyword(2) Vector space model
Keyword(3) Random projection
Keyword(4) Latent semantic indexing
Keyword(5) Concept vector
1st Author's Name Minoru SASAKI
1st Author's Affiliation Department of Computer and Information Sciences, Ibaraki University()
2nd Author's Name Takashi OTANI
2nd Author's Affiliation Graduate School of Engineering, Tokushima University
3rd Author's Name Kenji KITA
3rd Author's Affiliation Department of Information Science & Intelligent Systems Faculty of Engineering
Date 2002/6/27
Paper # NLP2002-32
Volume (vol) vol.102
Number (no) 181
Page pp.pp.-
#Pages 6
Date of Issue