文章基本信息

标题：Human Interaction Pattern Mining Using Enhanced Artificial Bee Colony Algorithm
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作者：S. Uma ; Dr. J. Suguna
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：9
DOI：10.15680/IJIRCCE.2015. 0309058
出版社：S&S Publications
摘要：Interactions between human beings occur often in meeting discussions. Semantic knowledge of suchmeetings can be revealed by discovering interaction patterns from them. Artificial Bee Colony (ABC) algorithm is arelatively new swarm intelligence algorithm that has attracted great pact of attention from researchers with theadvantage of less control parameters and strong global optimization ability than other optimization algorithms. In thisresearch work ABC algorithm is enhanced using Partial Least Square (PLS) mechanism in order to extract frequentinteraction among patterns. The objectives of the research are three-fold such as detecting more number of interactionsmade, more number of frequent interactions made and reducing the execution time of the algorithm. The experimentalresults shows that by using Enhanced Artificial Bee Colony algorithm more interesting patterns that are useful for theinterpretation of human behavior in meeting discussioncan be extracted.
关键词：Tree Based Mining; Enhanced Artificial Bee Colony; Human Interaction Pattern Mining; Partial;Least Square; Partial Ancestral Graph meet