# 臺灣博碩士論文加值系統

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 An information retrieval system is to search documentsin a large database for those which are relevant to a user query.A well-known method called Krylov subspace method is one ofsubspace methods for IR. It applies the Golub-Kahanbidiagonalization algorithm to a term-document matrix, startingfrom the query vector. Here we will study the famous and powerfulmethod. And term weighting is common for improving the accuracy ofan IR system. After introducing several term weighting schemes, wetest two noted databases, Medline and Cranfield, for differentterm weighting schemes. By transforming term-document matrices, wetry to realize the effect of term weighting for Krylov subspacemethod.
 1 Introduction2 Background 2.1 Information retrieval 2.2 Deﬁnition and notation3 Krylov subspace and Term weighting 3.1 Interpretation of krylov sequences 3.2 Krylov subspace method 3.3 Measuring progress 3.4 Term weighting .4 Numerical experiments
 1. M. W. Berry, S. T. Dumais, and G. W. O'Brien,{Using linear algebra for intelligent information retrieval}, SIAMReview, 37(1995), pp. 573-595.2. S. T. Dumais, G. W. Furnas, T. K. Landauer, S.Deerwester, and R. Harshman, {Indexing by latent semanticanalysis}, J. Amer. Soc. Inform. Sci., 41 (1990), pp. 391-4073. G. H. Golub and C. F. Van Loan, {Matrix Computations},Johns Hopkins University Press, Baltimore, Maryland, 3 ed., 1996.4. K. Blom, {Information Retrieval using the SingularValue Decomposition and Krylov Subspaces}, Technical report1999-5, Department of Mathematics, Chalmers University of Technology, Sweden,1999.5. K. Blom and A. Rune, {Information Retrieval using very short Krylov Sequences}, in Computational Information Retrieval,M. W. Berry, Proc. Appl. Math. 106, SIAM, Philadelphia, 2001, pp.39-52.6. K. Blom and A. Rune, {A Krylov Subspace Method for Information Retrieval}, SIAM J. MATRIX ANAL. APPL. Vol. 26,No. 2, pp. 566-582.7. S. T. Dumais, {Enhancing Performance in Latent Semantic Indexing(LSI) Retrieval}, Bellcore, 21236, 1992.8. Cranfield and Medline collections. (Available at URL:ftp://ftp.cs.cornell.edu/pub/smart).
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