Efficient joint clustering algorithms in optimization and geography domains

Chia Hao Lo*, Wen-Chih Peng

*此作品的通信作者

研究成果: Conference contribution同行評審

6 引文 斯高帕斯(Scopus)

摘要

Prior works have elaborated on the problem of joint clustering in the optimization and geography domains. However, prior works neither clearly specify the connected constraint in the geography domain nor propose efficient algorithms. In this paper, we formulate the joint clustering problem in which a connected constraint and the number of clusters should be specified. We propose an algorithm K-means with Local Search (abbreviated as KLS) to solve the joint clustering problem with the connected constraint. Experimental results show that KLS can find correct clusters efficiently.

原文English
主出版物標題Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings
頁面945-950
頁數6
DOIs
出版狀態Published - 9 6月 2008
事件12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008 - Osaka, Japan
持續時間: 20 5月 200823 5月 2008

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
5012 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008
國家/地區Japan
城市Osaka
期間20/05/0823/05/08

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