Hybrid pre-query term expansion using latent semantic analysis

Laurence A.F. Park; Kotagiri Ramamohanarao

doi:10.1109/ICDM.2004.10085

Hybrid pre-query term expansion using latent semantic analysis

Laurence A.F. Park
, Kotagiri Ramamohanarao

University of Melbourne

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

14 Citations (Scopus)

Abstract

Latent semantic retrieval methods (unlike vector space methods) take the document and query vectors and map them into a topic space to cluster related terms and documents. This produces a more precise retrieval but also a long query time. We present a new method of document retrieval which allows us to process the latent semantic information into a hybrid Latent Semantic-Vector Space query mapping. This mapping automatically expands the users query based on the latent semantic information in the document set. This expanded query is processed using a fast vector space method. Since we have the latent semantic data in a mapping, we are able to store and retrieve vector information in the same fast manner that the vector space method offers. Multiple mappings are combined to produce hybrid latent semantic retrieval which provide precision results 5% greater than the vector space method and fast query times.

Original language	English
Title of host publication	Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
Editors	R. Rastogi, K. Morik, M. Bramer, X. Wu
Pages	178-185
Number of pages	8
DOIs	https://doi.org/10.1109/ICDM.2004.10085
Publication status	Published - 2004
Externally published	Yes
Event	Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004 - Brighton, United Kingdom Duration: 1 Nov 2004 → 4 Nov 2004

Publication series

Name	Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004

Conference

Conference	Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
Country/Territory	United Kingdom
City	Brighton
Period	1/11/04 → 4/11/04

Access to Document

10.1109/ICDM.2004.10085

Cite this

Park, L. A. F., & Ramamohanarao, K. (2004). Hybrid pre-query term expansion using latent semantic analysis. In R. Rastogi, K. Morik, M. Bramer, & X. Wu (Eds.), Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004 (pp. 178-185). (Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004). https://doi.org/10.1109/ICDM.2004.10085

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title = "Hybrid pre-query term expansion using latent semantic analysis",

abstract = "Latent semantic retrieval methods (unlike vector space methods) take the document and query vectors and map them into a topic space to cluster related terms and documents. This produces a more precise retrieval but also a long query time. We present a new method of document retrieval which allows us to process the latent semantic information into a hybrid Latent Semantic-Vector Space query mapping. This mapping automatically expands the users query based on the latent semantic information in the document set. This expanded query is processed using a fast vector space method. Since we have the latent semantic data in a mapping, we are able to store and retrieve vector information in the same fast manner that the vector space method offers. Multiple mappings are combined to produce hybrid latent semantic retrieval which provide precision results 5\% greater than the vector space method and fast query times.",

author = "Park, \{Laurence A.F.\} and Kotagiri Ramamohanarao",

year = "2004",

doi = "10.1109/ICDM.2004.10085",

language = "English",

isbn = "0769521428",

series = "Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004",

pages = "178--185",

editor = "R. Rastogi and K. Morik and M. Bramer and X. Wu",

booktitle = "Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004",

note = "Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004 ; Conference date: 01-11-2004 Through 04-11-2004",

}

Park, LAF & Ramamohanarao, K 2004, Hybrid pre-query term expansion using latent semantic analysis. in R Rastogi, K Morik, M Bramer & X Wu (eds), Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004. Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004, pp. 178-185, Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004, Brighton, United Kingdom, 1/11/04. https://doi.org/10.1109/ICDM.2004.10085

Hybrid pre-query term expansion using latent semantic analysis. / Park, Laurence A.F.; Ramamohanarao, Kotagiri.
Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004. ed. / R. Rastogi; K. Morik; M. Bramer; X. Wu. 2004. p. 178-185 (Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004).

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

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AB - Latent semantic retrieval methods (unlike vector space methods) take the document and query vectors and map them into a topic space to cluster related terms and documents. This produces a more precise retrieval but also a long query time. We present a new method of document retrieval which allows us to process the latent semantic information into a hybrid Latent Semantic-Vector Space query mapping. This mapping automatically expands the users query based on the latent semantic information in the document set. This expanded query is processed using a fast vector space method. Since we have the latent semantic data in a mapping, we are able to store and retrieve vector information in the same fast manner that the vector space method offers. Multiple mappings are combined to produce hybrid latent semantic retrieval which provide precision results 5% greater than the vector space method and fast query times.

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BT - Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004

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Hybrid pre-query term expansion using latent semantic analysis

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