An Efficient Web Prediction Model Using Modified Markov Model with ANN

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2014 by IJCTT Journal
Volume-9 Number-6                          
Year of Publication : 2014
Authors : M. Sivasankari
  10.14445/22312803/IJCTT-V9P152

MLA

M. Sivasankari."An Efficient Web Prediction Model Using Modified Markov Model with ANN". International Journal of Computer Trends and Technology (IJCTT) V9(6):275-278, March 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Web prediction is a classification problem in which we try to predict the preceding set of Web pages in which a user may visit supported on the knowledge of the previously visited pages. While serving the Internet user’s behavior prediction can be applied effectively in various critical applications. Such application has usual tradeoffs between modeling complexity and prediction accuracy. In this paper we proposed artificial neural network (ANN) for predicting web by the user. In addition modified Markov model has been analysed and presented in prediction of web. A prediction framework uses ANN based on the training samples. By doing this the proposed framework shows the improved prediction time without compromising prediction accuracy.

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Keywords
Markovian model, Artifical neural network, data mining-gram