A self-organized semantic clustering approach for super-peer networks

Baiyou Qiao; Guoren Wang; Kexin Xie

doi:10.1007/11912873_46

A self-organized semantic clustering approach for super-peer networks

Baiyou Qiao^*
, Guoren Wang
, Kexin Xie

^*Corresponding author for this work

Northeastern University China

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

3 Citations (Scopus)

Abstract

Partitioning a P2P network into distinct semantic clusters can efficiently increase the efficiency of searching and enhance scalability of the network. In this paper, two semantic-based self-organized algorithms aimed at taxonomy hierarchy semantic space are proposed, which can dynamically partition the network into distinct semantic clusters according to network load, with semantic relationship among data within a cluster and load balance among clusters all well maintained. The experiment indicates good performance and scalability of these two clustering algorithms.

Original language	English
Title of host publication	Web Information Systems - WISE 2006
Subtitle of host publication	7th International Conference on Web Information Systems Engineering, Proceedings
Publisher	Springer Verlag
Pages	448-453
Number of pages	6
ISBN (Print)	3540481052, 9783540481058
DOIs	https://doi.org/10.1007/11912873_46
Publication status	Published - 2006
Externally published	Yes
Event	7th International Conference on Web Information Systems Engineering, WISE 2006 - Wuhan, China Duration: 23 Oct 2006 → 26 Oct 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4255 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Conference on Web Information Systems Engineering, WISE 2006
Country/Territory	China
City	Wuhan
Period	23/10/06 → 26/10/06

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10.1007/11912873_46

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Qiao, B., Wang, G., & Xie, K. (2006). A self-organized semantic clustering approach for super-peer networks. In Web Information Systems - WISE 2006: 7th International Conference on Web Information Systems Engineering, Proceedings (pp. 448-453). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4255 LNCS). Springer Verlag. https://doi.org/10.1007/11912873_46

Qiao, Baiyou ; Wang, Guoren ; Xie, Kexin. / A self-organized semantic clustering approach for super-peer networks. Web Information Systems - WISE 2006: 7th International Conference on Web Information Systems Engineering, Proceedings. Springer Verlag, 2006. pp. 448-453 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A self-organized semantic clustering approach for super-peer networks",

abstract = "Partitioning a P2P network into distinct semantic clusters can efficiently increase the efficiency of searching and enhance scalability of the network. In this paper, two semantic-based self-organized algorithms aimed at taxonomy hierarchy semantic space are proposed, which can dynamically partition the network into distinct semantic clusters according to network load, with semantic relationship among data within a cluster and load balance among clusters all well maintained. The experiment indicates good performance and scalability of these two clustering algorithms.",

author = "Baiyou Qiao and Guoren Wang and Kexin Xie",

year = "2006",

doi = "10.1007/11912873\_46",

language = "English",

isbn = "3540481052",

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

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booktitle = "Web Information Systems - WISE 2006",

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note = "7th International Conference on Web Information Systems Engineering, WISE 2006 ; Conference date: 23-10-2006 Through 26-10-2006",

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Qiao, B, Wang, G & Xie, K 2006, A self-organized semantic clustering approach for super-peer networks. in Web Information Systems - WISE 2006: 7th International Conference on Web Information Systems Engineering, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4255 LNCS, Springer Verlag, pp. 448-453, 7th International Conference on Web Information Systems Engineering, WISE 2006, Wuhan, China, 23/10/06. https://doi.org/10.1007/11912873_46

A self-organized semantic clustering approach for super-peer networks. / Qiao, Baiyou; Wang, Guoren; Xie, Kexin.
Web Information Systems - WISE 2006: 7th International Conference on Web Information Systems Engineering, Proceedings. Springer Verlag, 2006. p. 448-453 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4255 LNCS).

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

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AU - Wang, Guoren

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SN - 9783540481058

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

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Qiao B, Wang G, Xie K. A self-organized semantic clustering approach for super-peer networks. In Web Information Systems - WISE 2006: 7th International Conference on Web Information Systems Engineering, Proceedings. Springer Verlag. 2006. p. 448-453. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11912873_46

A self-organized semantic clustering approach for super-peer networks

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