Novel Hybrid k-D-Apriori Algorithm for Web Usage Mining
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 4
Abstract
Abstract: The Web usage mining is a branch of web mining in which by clustering the datasets, frequently accessed patterns can be obtained for betterment of social portals, websites. The divisive analysis is one of the types of hierarchical method of data clustering that is used to separate each dataset from the clustered datadepending on previous small clusters. Apriori & k-Apriori are commonly used hierarchical algorithms for web usage mining but they are less efficient for mining dynamic item sets such as twitter dataset. Recently D-Apriori algorithm has been proposed in the literature for mining dynamic dataset to find the frequently accessed web pages from web log database. The disadvantage of D-Apriori is that, it takes more execution time compared to k-Apriori. This research work proposes a new hybrid k-D-Apriori algorithm that reduces the execution time, improves frequent pattern generation, works efficiently with dynamic datasets and gives improved associationrule generation as compared to D-Apriori algorithm
Authors and Affiliations
Foram Shah , Joanne Gomes
Keywords
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