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Abstract: The Singular Value Decomposition (SVD) has attracted much interest of late as a technique for improving the performance of text retrieval systems (also called Latent Semantic Indexing). Preliminary results have shown modest improvements in retrieval accuracy, but these have mainly explored small collections. In this paper we investigate using the LSI on large document collections (TREC datasets). We focus on properties of the LSI and investigate whether these match our intuition about the... (Update)
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BibTeX entry: (Update)
P. Husbands, H. Simon and C.Ding. On the Use of Singular Value Decomposition for Text Retrieval. Proc. of SIAM Comp. Info. Retrieval Workshop, October 2000. Ed. M. Berry. http://citeseer.ist.psu.edu/article/husbands01use.html More
@inproceedings{ husbands00use,
author = "P. Husbands and H. Simon and C. Ding",
title = "the Use of Singular Value Decomposition for Text Retrieval",
booktitle = "Proc. of SIAM Comp. Info. Retrieval Workshop",
month = "October",
editor = "M. Berry",
year = "2000",
url = "citeseer.ist.psu.edu/article/husbands01use.html" }
Citations (may not include all citations):
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Indexing by latent semantic analysis
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Matrix Perturbation Theory (context) - Stewart, Sun - 1990
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Using linear algebra for intelligent information retrieval
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Latent semantic indexing: A probabilistic analysis
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Improving text retrieval for the routing problem using laten.. (context) - Hull - 1994
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A similarity-based probability model for latent semantic ind..
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A portable implementation of ARPACK for distributed memory p..
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Lawrence Berkeley National Laboratory (context) - Wu, Simon et al. - 1999
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the Use of the Singular Value Decomposition for Large Scale .. (context) - Husbands, Simon et al. - 2000
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Submitted to ICML (context) - Ding, He et al. - 2001
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