Web page access prediction using hierarchical clustering based on modified levenshtein distance and higher order Markov model

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Harish Kumar, B.T. and Vibha, L. and Venugopal, K.R. (2016) Web page access prediction using hierarchical clustering based on modified levenshtein distance and higher order Markov model. In: Region 10 Symposium (TENSYMP), 2016 IEEE, 9-11 May 2016, Bangalore.

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Official URL: https://doi.org/10.1109/TENCONSpring.2016.7519368

Abstract

Web Page access prediction is a challenging task in the current scenario, which draws the attention of many researchers. Predictions need to keep track of history data to analyze the usage behavior of the users. Web Usage behavior of a user can be analyzed using the web log file of a specific website. User behavior can be analyzed by observing the navigation patterns. This approach requires user session identification, clustering the sessions into similar clusters and developing a model for prediction using the current and earlier accesses. Most of the previous works in this field have used K-Means clustering technique with Euclidean distance for computation. The drawbacks of K-Means is that deciding on the number of clusters, choosing the initial random center are difficult and the order of page visits are not considered. The proposed research work uses hierarchical clustering technique with modified Levenshtein distance, Page Rank using access time length, frequency and higher order Markov model for prediction. Experimental results prove that the proposed approach for prediction gives better accuracy over the existing techniques.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Access Time; Frequency; Hierarchical Cluster;Levenshtein Distance; Markov Model; Prediction
Subjects: Faculty of Engineering > Computer Science & Information Science Engineering
Divisions: University Visvesvarayya College of Engineering > Department of Computer Science and Information Science Engineering
Depositing User: Ms. Deepa M Kolli
Date Deposited: 21 Oct 2016 06:23
Last Modified: 21 Oct 2016 06:23
URI: http://eprints-bangaloreuniversity.in/id/eprint/6699

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