An Improved Genetic Algorithm for Text Clustering

摘要：

The genetic algorithm (GA) is a self-adapted probability search method used to solve optimization problems which has been applied widely in science and engineering.In this paper,we propose an improved variable string length genetic algorithm (IVGA) for text clustering.Our algorithm has been exploited for automatically evolving the optimal number of clusters as well as providing proper data set clustering.The chromosome is encoded by special indices to indicate the location of each gene.More effective version of evolutional steps can automatically adjust the influence between the diversity of the population and selective pressure during generations.The superiority of the improved genetic algorithm over conventional variable string length genetic algorithm (VGA) is demonstrated by providing proper text clustering.

关键词： text clustering genertic algorithm gene index

作者: Shidong YU Hang LI Qi XU

作者单位: College of Software Shenyang Normal University Shenyang 110034,China Physical Science and Technical College Shenyang Normal University Shenyang 110034,China

会议类型: 国际会议

会议名称: 2010 4th International Conference on Intelligent Information Techonlogy Application(第四届智能信息技术应用国际学术研讨会 IITA 2010)

会议地点: 秦皇岛

会议语种:英文

页码: 342-345

在线出版日期: 2010-11-05（万方平台首次上网日期，不代表论文的发表时间）