Title of article
A novel prediction model based on hierarchical characteristic of web site
Author/Authors
Lee، نويسنده , , Chu-Hui and Lo، نويسنده , , Yu-lung and Fu، نويسنده , , Yu-Hsiang، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2011
Pages
9
From page
3422
To page
3430
Abstract
Internet has developed in a rapid way in the recent 10 years,and the information of web site has also been increasing fast. Predicting web user’s behavior becomes a crucial issue following the purposes like increasing the user’s browsing speed efficiently, decreasing the user’s latency as well as possible and reducing the loading of web server. In this paper, we propose an efficient prediction model, two-level prediction model (TLPM), using a novel aspect of natural hierarchical property from web log data. TLPM can decrease the size of candidate set of web pages and increase the speed of predicting with adequate accuracy. The experiment results prove that TLPM can highly enhance the performance of prediction when the number of web pages is increasing.
Keywords
Markov model , Prediction , Bayesian theorem , Data preprocessing , Web usage mining
Journal title
Expert Systems with Applications
Serial Year
2011
Journal title
Expert Systems with Applications
Record number
2348995
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