Presentation 2001/3/16
Information Retrieval System Using Concept Vectors Based on PDDP
Minoru Sasaki, 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 / PDDP
Paper # TL2000-42,NLC2000-77
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Committee NLC
Conference Date 2001/3/16(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Information Retrieval System Using Concept Vectors Based on PDDP
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
Keyword(6) PDDP
1st Author's Name Minoru Sasaki
1st Author's Affiliation Faculty of Engineering, Tokushima University()
2nd Author's Name Kenji Kita
2nd Author's Affiliation Faculty of Engineering, Tokushima University
Date 2001/3/16
Paper # TL2000-42,NLC2000-77
Volume (vol) vol.100
Number (no) 700
Page pp.pp.-
#Pages 8
Date of Issue