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A Novel Method for Data Cleaning and User- Session Identification for Web Mining

The World Wide Web(WWW) is serving as a huge widely distributed global information service center for technical information, news, advertisement, e-commerce and other information service. This makes information retrieval process very difficult. Most users may not have good knowledge of the structure of the information network, and may easily get bored by taking many access hops and losing their patience when waiting for the information. These challenges will have been solved efficiently by using Web mining, which is the application of data mining technologies. Web mining employs the technique of data mining process into the documents on the WWW. The overall process of web mining includes extraction of information from the WWW through the conventional practices of the data mining and putting the same into the website features. The task of web mining is to discover and extract interesting knowledge/patterns from Web is classified into three types as Web Structure Mining that focuses on hyperlink structure, Web Contents Mining that focuses on page contents as well as Web Usage Mining that focuses on Web logs. In this paper, we are concerned about Web Usage Mining (WUM), also called as Web log mining. We propose algorithms for cleaning a web log file, user and session identification.