On updating problems in latent semantic indexing
Journal Article
·
· SIAM Journal on Scientific Computing
The authors develop new SVD-updating algorithms for three types of updating problems arising from latent semantic indexing (LSI) for information retrieval to deal with rapidly changing text document collections. They also provide theoretical justification for using a reduced-dimension representation of the original document collection in the updating process. Numerical experiments using several standard text document collections show that the new algorithms give higher (interpolated) average precisions that the existing algorithms, and the retrieval accuracy is comparable to that obtained using the complete document collection.
- Research Organization:
- Pennsylvania State Univ., University Park, PA (US)
- Sponsoring Organization:
- US Department of Energy; National Science Foundation
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 20015659
- Journal Information:
- SIAM Journal on Scientific Computing, Journal Name: SIAM Journal on Scientific Computing Journal Issue: 2 Vol. 21; ISSN 1064-8275; ISSN SJOCE3
- Country of Publication:
- United States
- Language:
- English
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