Users'web browsing behavior prediction model based on Markov model and Bayesian theorem

作者：Bi Meng; Hou Lin; Ni Pan; Zhou Fu Cai^*

来源：Journal of Northeastern University, 2016, 37(6): 775-779 and 799.

DOI：10.3969/j.issn.1005-3026.2016.06.004

• Bayesian Theorem
• Browsing behavior
• Construction method
• Data preprocessing
• Inverted index structures
• Markov model
• Modeling and predictions
• Prediction model

According to the novel aspect of natural hierarchical property of Web site, the inverted index structure was proposed based on Hash table (IIS-HT) to promote the speed of data preprocessing. Based on IIS-HT, a prediction model was also proposed which was based on statistics to predict users'browsing behavior. The design idea, definition, framework and key construction methods of the model were also given. Finally, the proposed model was tested with real data. The experimental results show that the model and prediction algorithm could reduce the scope of candidate pages and improve the speed of prediction with adequate accuracy.

• 出版日期2016
• 单位东北大学