Indexing by latent semantic analysis
Article first published online: 7 JAN 1999
Copyright © 1990 John Wiley & Sons, Inc.
Journal of the American Society for Information Science
Volume 41, Issue 6, pages 391–407, September 1990
How to Cite
Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K. and Harshman, R. (1990), Indexing by latent semantic analysis. J. Am. Soc. Inf. Sci., 41: 391–407. doi: 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9
- Issue published online: 7 JAN 1999
- Article first published online: 7 JAN 1999
- Manuscript Accepted: 5 APR 1988
- Manuscript Revised: 4 APR 1988
- Manuscript Received: 26 AUG 1987
A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higher-order structure in the association of terms with documents (“semantic structure”) in order to improve the detection of relevant documents on the basis of terms found in queries. The particular technique used is singular-value decomposition, in which a large term by document matrix is decomposed into a set of ca. 100 orthogonal factors from which the original matrix can be approximated by linear combination. Documents are represented by ca. 100 item vectors of factor weights. Queries are represented as pseudo-document vectors formed from weighted combinations of terms, and documents with supra-threshold cosine values are returned. Initial tests find this completely automatic method for retrieval to be promising. © 1990 John Wiley & Sons, Inc.