A clustering model for mining evolving web user patterns in data stream environment

Edmond H. Wu; Michael K. Ng; Andy M. Yip; Tony F. Chan

doi:10.1007/978-3-540-28651-6_83

A clustering model for mining evolving web user patterns in data stream environment

Edmond H. Wu^*, Michael K. Ng, Andy M. Yip, Tony F. Chan

^*Corresponding author for this work

Department of Mathematics

Research output: Chapter in book/report/conference proceeding › Chapter › peer-review

3 Citations (Scopus)

Abstract

With the fast growing of the Internet and its Web users all over the world, how to manage and discover useful patterns from tremendous and evolving Web information sources become new challenges to our data engineering researchers. Also, there is a great demand on designing scalable and flexible data mining algorithms for various time-critical and data-intensive Web applications. In this paper, we purpose a new clustering model for generating and maintaining clusters efficiently which represent the changing Web user patterns in Websites. With effective pruning process, the clusters can be fast discovered and updated to reflect the current or changing user patterns to Website administrators. This model can also be employed in different Web applications such as personalization and recommendation systems.

Original language	English
Title of host publication	Intelligent Data Engineering and Automated Learning - IDEAL 2004
Subtitle of host publication	5th International Conference, Exeter, UK, August 25-27, 2004, Proceedings
Editors	Zheng Rong Yang, Richard Everson, Hujun Yin
Publisher	Springer Berlin Heidelberg
Pages	565-571
Number of pages	7
Edition	1st
ISBN (Electronic)	9783540286516
ISBN (Print)	9783540228813
DOIs	https://doi.org/10.1007/978-3-540-28651-6_83
Publication status	Published - 13 Aug 2004
Event	5th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2004 - Exeter, United Kingdom Duration: 25 Aug 2004 → 27 Aug 2004 https://link.springer.com/book/10.1007/b99975

Publication series

Name	Lecture Notes in Computer Science
Volume	3177
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	IDEAL: International Conference on Intelligent Data Engineering and Automated Learning

Conference

Conference	5th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2004
Abbreviated title	IDEAL 2004
Country/Territory	United Kingdom
City	Exeter
Period	25/08/04 → 27/08/04
Internet address	https://link.springer.com/book/10.1007/b99975

Scopus Subject Areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-28651-6_83

Cite this

Wu, E. H., Ng, M. K., Yip, A. M., & Chan, T. F. (2004). A clustering model for mining evolving web user patterns in data stream environment. In Z. R. Yang, R. Everson, & H. Yin (Eds.), Intelligent Data Engineering and Automated Learning - IDEAL 2004: 5th International Conference, Exeter, UK, August 25-27, 2004, Proceedings (1st ed., pp. 565-571). (Lecture Notes in Computer Science; Vol. 3177), (IDEAL: International Conference on Intelligent Data Engineering and Automated Learning). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-28651-6_83

Wu, Edmond H. ; Ng, Michael K. ; Yip, Andy M. et al. / A clustering model for mining evolving web user patterns in data stream environment. Intelligent Data Engineering and Automated Learning - IDEAL 2004: 5th International Conference, Exeter, UK, August 25-27, 2004, Proceedings. editor / Zheng Rong Yang ; Richard Everson ; Hujun Yin. 1st. ed. Springer Berlin Heidelberg, 2004. pp. 565-571 (Lecture Notes in Computer Science). (IDEAL: International Conference on Intelligent Data Engineering and Automated Learning).

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title = "A clustering model for mining evolving web user patterns in data stream environment",

abstract = "With the fast growing of the Internet and its Web users all over the world, how to manage and discover useful patterns from tremendous and evolving Web information sources become new challenges to our data engineering researchers. Also, there is a great demand on designing scalable and flexible data mining algorithms for various time-critical and data-intensive Web applications. In this paper, we purpose a new clustering model for generating and maintaining clusters efficiently which represent the changing Web user patterns in Websites. With effective pruning process, the clusters can be fast discovered and updated to reflect the current or changing user patterns to Website administrators. This model can also be employed in different Web applications such as personalization and recommendation systems.",

author = "Wu, {Edmond H.} and Ng, {Michael K.} and Yip, {Andy M.} and Chan, {Tony F.}",

note = "Publisher copyright: {\textcopyright} 2004 Springer-Verlag Berlin Heidelberg; 5th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2004, IDEAL 2004 ; Conference date: 25-08-2004 Through 27-08-2004",

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Wu, EH, Ng, MK, Yip, AM & Chan, TF 2004, A clustering model for mining evolving web user patterns in data stream environment. in ZR Yang, R Everson & H Yin (eds), Intelligent Data Engineering and Automated Learning - IDEAL 2004: 5th International Conference, Exeter, UK, August 25-27, 2004, Proceedings. 1st edn, Lecture Notes in Computer Science, vol. 3177, IDEAL: International Conference on Intelligent Data Engineering and Automated Learning, Springer Berlin Heidelberg, pp. 565-571, 5th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2004, Exeter, United Kingdom, 25/08/04. https://doi.org/10.1007/978-3-540-28651-6_83

A clustering model for mining evolving web user patterns in data stream environment. / Wu, Edmond H.; Ng, Michael K.; Yip, Andy M. et al.
Intelligent Data Engineering and Automated Learning - IDEAL 2004: 5th International Conference, Exeter, UK, August 25-27, 2004, Proceedings. ed. / Zheng Rong Yang; Richard Everson; Hujun Yin. 1st. ed. Springer Berlin Heidelberg, 2004. p. 565-571 (Lecture Notes in Computer Science; Vol. 3177), (IDEAL: International Conference on Intelligent Data Engineering and Automated Learning).

Research output: Chapter in book/report/conference proceeding › Chapter › peer-review

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Wu EH, Ng MK, Yip AM, Chan TF. A clustering model for mining evolving web user patterns in data stream environment. In Yang ZR, Everson R, Yin H, editors, Intelligent Data Engineering and Automated Learning - IDEAL 2004: 5th International Conference, Exeter, UK, August 25-27, 2004, Proceedings. 1st ed. Springer Berlin Heidelberg. 2004. p. 565-571. (Lecture Notes in Computer Science). (IDEAL: International Conference on Intelligent Data Engineering and Automated Learning). doi: 10.1007/978-3-540-28651-6_83

A clustering model for mining evolving web user patterns in data stream environment

Abstract

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