Design and Analysis of Web Page Recommendation System based on Web Usage Data

Abstract

The World Wide Web store, share and distribute information in the large scale. There is large number of internet users on the web. They are facing many problems like information overload due to the significant and rapid growth in the amount of information and the number of users. As a result, how to provide web users with more exactly needed information is becoming a critical issue in web applications. Web mining extracts interesting pattern or knowledge from web data. It is classified into three types as web content mining, web structure, and web usage mining. Web usage mining is the process of extracting useful knowledge from the server logs. This useful knowledge can be applied to target marketing and in the design of web portals. It may give information that is useful for improving the services offered by web portals and information access and retrieval tools. Here, the researcher, propose a new approach for web page recommendation along with user profile generation. The approach makes use of evolutionary biclustering technique for web page recommendation. Different datasets have been used for performing data mining operations, one is clickstream data and other used is web access log file of Kadi Sarva Vishwavidyalaya (KSV). The outcome of the approach using optimal biclusters and evolutionary biclustering techniques have been analyzed in the thesis and the results shows that, almost all records of the database are used and accurate results are generated, which is further useful for making strategic decision in the applications like target marketing and direct marketing. newlineIn our Research work we developed one embedded system which takes web log file as an input and produced results on most frequent navigational path followed by users of website. By using these frequent navigation patterns modification of websiteand#8223;s design can be done. Main phases of our approach were Pre-processing, Pattern Discovery and Pattern analysis. First of all we took NASAand#8223;s log file and did some pre-processing tasks on it such as log c