Title :
A dynamic genetic algorithm for clustering web pages
Author :
Zhengyu, Zhu ; Ping, Han ; Chunlei, Yu ; Lipei, Li
Author_Institution :
Coll. of Comput. Sci., Chongqing Univ., Chongqing, China
Abstract :
Though the hybrid clustering algorithm (HCA) is very effective to cluster Web pages, it needs the auto k value calculation (AKVC) method to calculate 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 HCA´s 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.
Keywords :
Internet; genetic algorithms; pattern clustering; HCA population; auto k value calculation; clustering Web page; dynamic genetic algorithm; fitness function; hybrid clustering algorithm; Algorithm design and analysis; Clustering algorithms; Design methodology; Dissolved gas analysis; Educational institutions; Genetic algorithms; Genetic mutations; Iterative algorithms; Partitioning algorithms; Web pages; Clustering algorithm; GA; Web page;
Conference_Titel :
Software Engineering and Data Mining (SEDM), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-7324-3
Electronic_ISBN :
978-89-88678-22-0
