文章基本信息

标题：Evaluation of Document Clustering Approach based on Particle Swarm Optimization Method for Twitter Dataset
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作者：Baljeet Kaur ; Sheetal Kundra ; Harish Kundra 等
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 .