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Web 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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