文章基本信息

标题：Quine-McCluskey: A Novel Concept for Mining the Frequency Patterns from Web Data
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作者：Bina Bhandari ; R. H. Goudar ; Kaushal Kumar 等
期刊名称：International Journal of Education and Management Engineering(IJEME)
印刷版ISSN：2305-3623
电子版ISSN：2305-8463
出版年度：2018
卷号：8
期号：1
页码：40-47
DOI：10.5815/ijeme.2018.01.05
出版社：MECS Publisher
摘要：With the advancement in the web technology it is considered as one of the vast repository of information. However this information is in the hidden form. Various data mining techniques need to be applied for extracting the meaningful information from the web. In this paper the various techniques are discussed that have been used by many researchers for extracting the information and also shown the disadvantages with the existing approaches. The paper put forward a novel concept of mining the association rule from the web data by using Quine-McCluskey algorithm. This algorithm is an optimization technique over the existing algorithm like Apriori, reverse Apriori, k-map. This paper exhibits the working of the Quine- McCluskey algorithm that can extract the frequently accessed web pages with minimum number of candidate sets generation. However the limitation of Quine-McCluskey algorithm is that it cannot find the infrequent patterns.
关键词：Quine-Mccluskey Algorithm;K-Map;Apriori Algorithm;Users Access Pattern