A Novel Approach to Determine the Rules for Web Page Prediction using Dynamically Chosen K-Order Markov Models
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2013, Vol 2, Issue 12
Abstract
The problem of predicting user’s behavior on a Web site has fundamental significance due to the rapid growth of the World Wide Web. Recent research initiatives have addressed the need for improved performance of Web page prediction that would profit many applications, ebusiness in particular. Despite the various efforts so far, there is still room for advancement in this field. Although traditional Markov models have been found to be suited for addressing this problem, they have serious limitations. Thus, good predictions require new Markov models. This paper endeavors to provide improved prediction accuracy by using a novel approach to determine the rules for web page prediction by making use of k-order markov models where the value of ‘k’ is chosen dynamically.
Authors and Affiliations
Jyoti Verma, Ashok Kumar Sharma, Amit Goel
Keywords
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