A Survey on User Navigation Pattern Prediction from Web Log Data

Authors

  • Bhalerao Y Department of Computer Engineering, University of Pune, India
  • PP Rokade Department of Computer Engineering, University of Pune, India

Keywords:

Clustering, Classification, Recommender, N-Grams, User Sessions, Web Usage Mining

Abstract

This paper proposes a survey of Web Page Prediction Methods. Prefetching of Web pages has been mostly used to reduce the access latency problem of the WWW users. However, if Prefetching of Web page is not accurate and Prefetched web pages are not visited by the users in their accesses, the limited bandwidth of network and services of Data Center and Cloud will not be used efficiently and may face the problem of access delay. Therefore, it is critical that we need an effective prediction method during prefetching of Services. The Markov models have been widely used to predict and analyze users navigational behavior. All the activities of web users have been saved in web log files. The stored users session is used to extract popular web navigation paths traverse and predict current users next web page Action in domain.

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Published

2015-05-30

How to Cite

[1]
Y. Bhalerao and P. Rokade, “A Survey on User Navigation Pattern Prediction from Web Log Data”, Int. J. Comp. Sci. Eng., vol. 3, no. 5, pp. 133–137, May 2015.

Issue

Vol. 3 No. 5 (2015): IJCSE May Edition

Section

Survey Article

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