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Volumn 41, Issue 5, 2005, Pages 1051-1063

Clustered SVD strategies in latent semantic indexing

Author keywords

Clustering; Latent semantic indexing; SVD; Text retrieval

Indexed keywords

APPROXIMATION THEORY; DATA ACQUISITION; DATA STORAGE EQUIPMENT; INFORMATION RETRIEVAL; MATRIX ALGEBRA; SEMANTICS; TEXT PROCESSING;

EID: 16244363649     PISSN: 03064573     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipm.2004.10.005     Document Type: Article
Times cited : (56)

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    • I.S. Dhillon, and D.S. Modha Concept decompositions for large sparse text data using clustering Machine Learning 42 2001 143 175
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  • 8
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    • Dumais, S. T. (1993). LSI meets TREC: A status report. In The First Text REtrieval Conference, NIST Special Pub. 500-207 (pp. 137-152), Gaithersburg, MD
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  • 9
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    • Sparsification strategies in latent semantic indexing
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    • Gao, J., & Zhang, J. (2003). Sparsification strategies in latent semantic indexing. In Proceedings of the 2003 Text Mining Workshop (pp. 93-103), San Francisco, CA
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    • On the use of singular value decomposition for text retrieval
    • Philadelphia, PA
    • Husbands, P., Simon, H., & Ding, C. (2001). On the use of singular value decomposition for text retrieval. In Computational Information Retrieval (SIAM) (pp. 45-156), Philadelphia, PA
    • (2001) Computational Information Retrieval (SIAM) , pp. 45-156
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  • 13
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    • Application of principle direction divisive partitioning and singular value decomposition in information retrieval
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.