Document (#34397)

Author
Deerwester, S.
Dumais, S.
Landauer, T.
Furnass, G.
Beck, L.
Title
Improving information retrieval with latent semantic indexing
Source
ASIS'88. Information technology: planning for the next fifty years. Proceedings of the 51st Annual Meeting of the American Society for Information Science, Atlanta, Georgia, 23.-27.10.1988. Vol.25. Ed. by C.L. Borgman and E.Y.H. Pai
Imprint
Medford, New Jersey : Learned Information Inc.
Year
1988
Pages
S.36-40
Abstract
Describes a latent semantic indexing (LSI) approach for improving information retrieval. Most document retrieval systems depend on matching keywords in queries against those in documents. The LSI approach tries to overcome the incompleteness and imprecision of latent relations among terms and documents. Tested performance of the LSI method ranged from considerably better than to roughly comparable to performance based on weighted keyword matching, apparently depending on the quality of the queries. Best LSI performance was found using a global entropy weighting for terms and about 100 dimensions for representing terms, documents and queries.
Theme
Retrievalalgorithmen
Object
Latent Semantic Indexing

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