On updating problems in latent semantic indexing
- Lawrence Berkeley National Lab., CA (United States)
- Pennsylvania State Univ., University Park, PA (United States). Dept. of Computer Science and Engineering
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 than the existing algorithms and the retrieval accuracy is comparable to that obtained using the complete document collection.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Energy Research, Washington, DC (United States); National Science Foundation, Washington, DC (United States)
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 650342
- Report Number(s):
- LBNL-41101; ON: DE98052316; CNN: Grant CCR-9619452; TRN: AHC2DT04%%256
- Resource Relation:
- Other Information: PBD: Nov 1997
- Country of Publication:
- United States
- Language:
- English
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