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A k-means++ Algorithm for Internet Shopping Search Engine

  • Jian-Ji Ren (Dept. of Computer Engineering, Dong-A University) ;
  • Jae-kee Lee (Dept. of Computer Engineering, Dong-A University)
  • 발행 : 2008.11.14

초록

Nowadays, as the indices of the major search engines grow to a tremendous proportion, vertical search services can help customers to find what they need. Search Engine is one of the reasons for Internet shopping success in today's world. The import one part of search engine is clustering data. The objective of this paper is to explore a k-means++ algorithm to calculate the clustering data which in the Internet shopping environment. The experiment results shows that the k-means++ algorithm is a faster algorithm to achieved a good clustering.

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