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  • 标题:Evaluation of Document Clustering Approach based on Particle Swarm Optimization Method for Twitter Dataset
  • 本地全文:下载
  • 作者:Baljeet Kaur ; Sheetal Kundra ; Harish Kundra
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2015
  • 卷号:6
  • 期号:4
  • 页码:3338-3341
  • 出版社:TechScience Publications
  • 摘要:This research present a survey on clustering of twitter dataset with the help of particle swarm optimization technique. Twitter dataset having no of tweets which may include video, photos and 140 character of text and link etc. Recently tweets achieved alot of significance because most of social website like facebook and twitter permit users to post short message on their frontpage and their capability to spread information rapidly . Particle swarm optimization (PSO) technique is the best method to solve clustering problem. PSO optimizes problem with large no of candidate solutions. PSO is a procedure which solve a problem by iteratively updating a candidate solution .In PSO algorithm problem is optimized by no of candidate solutions .Here different particles are used for finding the appropriate solution where every particle have some velocity and position
  • 关键词:Document Clustering; PSO; Swarms ;Twitter;inertia component; cognitive component; acceleration;coefficient .
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