A survey of eigenvector methods for Web information retrieval

被引：237

作者：

Langville, AN ^{[1
]}

Meyer, CD ^{[1
]}

机构：

[1] N Carolina State Univ, Dept Math, Raleigh, NC 27695 USA

来源：

SIAM REVIEW | 2005年 / 47卷 / 01期

关键词：

eigenvector; Markov chain; information retrieval; HITS; PageRank; SALSA;

D O I：

10.1137/S0036144503424786

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Web information retrieval is significantly more challenging than traditional well-controlled, small document collection information retrieval. One main difference between traditional information retrieval and Web information retrieval is the Web's hyperlink structure. This structure has been exploited by several of today's leading Web search engines, particularly Google and Teoma. In this survey paper, we focus on Web information retrieval methods that use eigenvector computations, presenting the three popular methods of HITS, PageRank, and SALSA.

引用

页码：135 / 161

页数：27

共 63 条

[1]

[Anonymous], 2000, ICML

[2]

[Anonymous], 2003, 2 EIGENVALUE GOOGLE

[3]

[Anonymous], 2003, P 12 INT WORLD WID W

[4]

ARASU A, 2002, P 11 INT WORLD WID W

[5]

Barabasi A.-L., 2003, LINKED NEW SCI NETWO

[6] Matrices, vector spaces, and information retrieval [J].

Berry, MW ;

Drmac, Z ;

Jessup, ER .

SIAM REVIEW, 1999, 41 (02) :335-362

[7] When experts agree: Using non-affiliated experts to rank popular topics [J].

Bharat, K ;

Mihaila, GA .

ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2002, 20 (01) :47-58

[8]

Bharat K., 1998, Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, P104, DOI 10.1145/290941.290972

[9]

BIANCHINI M, 2005, IN PRESS ACM T INTER, V5

[10]

Bianchini Monica, 2002, P 11 INT WORLD WID W

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