A Novel Model for Web Usage Mining Based on CMAC Neural Network

The problem of anticipating human behavior is regarded as a great challenge in different fields including computer science. Specifically, web user mining is examined from viewpoint of machine learning and web usage mining is offered on this basis. Web usage mining (WUM) consists of 3 main stages including: preprocessing, knowledge discovery, sample analysis. Results of this research maybe applicable by the managers of websites for more effective management and personalization of their websites and in this way the specific requirements of unique groups are met and the profitability is increased. Moreover, web usage mining, covers the hidden samples of web log, which shows browsing behavior of the user.Clustering is an object based process and in this research, an intelligent system is offered for solving this problem. In this research the laboratory for Ambient Intelligence and mobile Robotic (DIBRIS,University of Genova) site is gone under preprocessing, discovery, analysis and Clustering is offered based on CMAC neural network. The CMAC neural network operates based on human cerebellum and some of the advantages of this neural network in comparison to other networks are including higher speed and less error.

کلیدواژه ها:

preprocessing ، knowledge discovery ، CMAC ، clustering ، WUM