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Refining Initial Seeds using Max Average Distance for K-Means Clustering  

Lee, Shin-Won (중원대학교 IT공학부)
Lee, Won-Hee (전북대학교 대학원 컴퓨터공학과)
Publication Information
Journal of Internet Computing and Services / v.12, no.2, 2011 , pp. 103-111 More about this Journal
Abstract
Clustering methods is divided into hierarchical clustering, partitioning clustering, and more. If the amount of documents is huge, it takes too much time to cluster them in hierarchical clustering. In this paper we deal with K-Means algorithm that is one of partitioning clustering and is adequate to cluster so many documents rapidly and easily. We propose the new method of selecting initial seeds in K-Means algorithm. In this method, the initial seeds have been selected that are positioned as far away from each other as possible.
Keywords
clustering; K-Means; initial seed;
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