Web Log Mining using K-Apriori Algorithm
TL;DR: A novel method called K-Apriori algorithm is proposed here, to find the frequently accessed web pages from the very large binary weblog databases, to show higher performance in terms of objectivity and subjectivity.
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Abstract: log mining is a data mining technique which extracts useful information from the World Wide Web's (WWW) client usage details. Automated data gathering has resulted in extremely large information about web access and it can be represented in binary form. A novel method called K-Apriori algorithm is proposed here, to find the frequently accessed web pages from the very large binary weblog databases. Experimental results show that the proposed method has shows higher performance in terms of objectivity and subjectivity.
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Web mining techniques and applications: Literature review and a proposal approach to improve performance of employment for young graduate in Morocco
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Novel Hybrid k-D-Apriori Algorithm for Web Usage Mining
Foram Shah,Joanne Gomes +1 more
TL;DR: 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 association rule generation as compared to D-A Priori algorithm.
Analyzing the Usage Pattern of University Website using Apriori Algorithm through Frequent Item set Generation
S. MuthuMari,T. Meyyappan +1 more
TL;DR: The Web server log is analyzed into two different ways, Frequent pattern and analyzed with IP address of the visitor and also with time of visit, and the Apriori algorithm generates the mined patterns that occur frequently.
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