Using Random walks for mining web document associations

Kasim Candan; Wen Syan Li

Using Random walks for mining web document associations

Kasim Candan, Wen Syan Li

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

15 Scopus citations

Abstract

World Wide Web has emerged as a primetry means for storing and structuring information. In this paper, we present a framework for mining implicit associations among Web documents. We focus on the following problem: “For a given set of seed URLs, find a list of Web pages which reflect the association among these seeds.” In the proposed framework, associations of two documents are induced by the connectivity and linking path length. Based on this framework, we have developed a random walk-hased Web mining technique and validated it by experiments on real Web data. In this paper, we also discuss the extension of the algorithm for considering document contents.

Original language	English (US)
Title of host publication	Knowledge Discovery and Data Mining
Subtitle of host publication	Current Issues and New Applications - 4th Pacific-Asia Conference, PAKDD 2000, Proceedings
Editors	Arbee L.P. Chen, Takao Terano, Huan Liu
Publisher	Springer Verlag
Pages	294-305
Number of pages	12
ISBN (Print)	3540673822, 9783540673828
State	Published - Jan 1 2000
Event	4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000 - Kyoto, Japan Duration: Apr 18 2000 → Apr 20 2000

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1805
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000
Country/Territory	Japan
City	Kyoto
Period	4/18/00 → 4/20/00

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Cite this

Candan, K., & Li, W. S. (2000). Using Random walks for mining web document associations. In A. L. P. Chen, T. Terano, & H. Liu (Eds.), Knowledge Discovery and Data Mining: Current Issues and New Applications - 4th Pacific-Asia Conference, PAKDD 2000, Proceedings (pp. 294-305). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1805). Springer Verlag.

Using Random walks for mining web document associations. / Candan, Kasim; Li, Wen Syan.
Knowledge Discovery and Data Mining: Current Issues and New Applications - 4th Pacific-Asia Conference, PAKDD 2000, Proceedings. ed. / Arbee L.P. Chen; Takao Terano; Huan Liu. Springer Verlag, 2000. p. 294-305 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1805).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Candan, K & Li, WS 2000, Using Random walks for mining web document associations. in ALP Chen, T Terano & H Liu (eds), Knowledge Discovery and Data Mining: Current Issues and New Applications - 4th Pacific-Asia Conference, PAKDD 2000, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1805, Springer Verlag, pp. 294-305, 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000, Kyoto, Japan, 4/18/00.

Candan K, Li WS. Using Random walks for mining web document associations. In Chen ALP, Terano T, Liu H, editors, Knowledge Discovery and Data Mining: Current Issues and New Applications - 4th Pacific-Asia Conference, PAKDD 2000, Proceedings. Springer Verlag. 2000. p. 294-305. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Candan, Kasim ; Li, Wen Syan. / Using Random walks for mining web document associations. Knowledge Discovery and Data Mining: Current Issues and New Applications - 4th Pacific-Asia Conference, PAKDD 2000, Proceedings. editor / Arbee L.P. Chen ; Takao Terano ; Huan Liu. Springer Verlag, 2000. pp. 294-305 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{4c9d670b064e4ef2a86df0ec2437c4e5,

title = "Using Random walks for mining web document associations",

abstract = "World Wide Web has emerged as a primetry means for storing and structuring information. In this paper, we present a framework for mining implicit associations among Web documents. We focus on the following problem: “For a given set of seed URLs, find a list of Web pages which reflect the association among these seeds.” In the proposed framework, associations of two documents are induced by the connectivity and linking path length. Based on this framework, we have developed a random walk-hased Web mining technique and validated it by experiments on real Web data. In this paper, we also discuss the extension of the algorithm for considering document contents.",

author = "Kasim Candan and Li, {Wen Syan}",

year = "2000",

month = jan,

day = "1",

language = "English (US)",

isbn = "3540673822",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "294--305",

editor = "Chen, {Arbee L.P.} and Takao Terano and Huan Liu",

booktitle = "Knowledge Discovery and Data Mining",

note = "4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000 ; Conference date: 18-04-2000 Through 20-04-2000",

}

TY - GEN

T1 - Using Random walks for mining web document associations

AU - Candan, Kasim

AU - Li, Wen Syan

PY - 2000/1/1

Y1 - 2000/1/1

N2 - World Wide Web has emerged as a primetry means for storing and structuring information. In this paper, we present a framework for mining implicit associations among Web documents. We focus on the following problem: “For a given set of seed URLs, find a list of Web pages which reflect the association among these seeds.” In the proposed framework, associations of two documents are induced by the connectivity and linking path length. Based on this framework, we have developed a random walk-hased Web mining technique and validated it by experiments on real Web data. In this paper, we also discuss the extension of the algorithm for considering document contents.

AB - World Wide Web has emerged as a primetry means for storing and structuring information. In this paper, we present a framework for mining implicit associations among Web documents. We focus on the following problem: “For a given set of seed URLs, find a list of Web pages which reflect the association among these seeds.” In the proposed framework, associations of two documents are induced by the connectivity and linking path length. Based on this framework, we have developed a random walk-hased Web mining technique and validated it by experiments on real Web data. In this paper, we also discuss the extension of the algorithm for considering document contents.

UR - http://www.scopus.com/inward/record.url?scp=79960590091&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79960590091&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:79960590091

SN - 3540673822

SN - 9783540673828

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 294

EP - 305

BT - Knowledge Discovery and Data Mining

A2 - Chen, Arbee L.P.

A2 - Terano, Takao

A2 - Liu, Huan

PB - Springer Verlag

T2 - 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000

Y2 - 18 April 2000 through 20 April 2000

ER -

Using Random walks for mining web document associations

Abstract

Publication series

Other

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this