A Dynamic Genetic Algorithm for Clustering Web Pages

摘要：

Though the hybrid clustering algorithm (HCA)iloi isvery effective to cluster Web pages, it needs the auto k value calculation (AKVC) method113 to cakulate the number of clusters in advance and its clustering result is affected by the number. A dynamic genetic algorithm(DGA) is designed in this paper by improving the AKVC method and the HCAs population, genetic operators and fitness function. The experiments show that DGA can obtain a more accurate number of clusters than AKVC and more accurate clusters of Web pages than HCA.

关键词： GA Web page Clustering algorithm

作者: ZHU Zhengyu HAN Ping YU Chunlei LI Lipe

作者单位: College of Computer Science, Chongqing University,Chongqing (400030), China

会议类型: 国际会议

会议名称: The 2nd International Conference on Software Engineering and Data Mining(IEEE 第二届国际软件工程和数据挖掘学术大会 SEDM 2010)

会议地点: 成都

会议语种:英文

页码: 457-462

在线出版日期: 2010-06-23（万方平台首次上网日期，不代表论文的发表时间）