Downloading: Recommendation of Web Pages for Online users using Web Log Data
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR) | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

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Recommendation of Web Pages for Online users using Web Log Data

V.Chitraa, Antony Selvadoss Thanamani

Abstract: World Wide Web is a huge repository of web pages and links. It provides abundance of information for the Internet users. To reduce users browsing time lot of research is taken place. Web Usage Mining is a type of web mining which applies mining techniques in log data to extract the behaviour of users which is used in various applications like personalized services, adaptive web sites, customer profiling, prefetching and creating attractive web sites. Users accesses are recorded in web logs. Because of the tremendous usage of web, the web log files are growing at a faster rate and the size is becoming huge. Web usage mining consists of three phases preprocessing, pattern discovery and pattern analysis. Soft Clustering is the most suitable method for web usage mining since same user can have more than one pattern and pattern analysis classifies the new user browsing in the knowledge base. Recommendations are given to the new user so that users browsing time is utilized effectively. This paper describes the methodology for all phases of web usage mining.

Keywords: Preprocessing, Fuzzy clustering, Session Identification, Recommendation, Web Log Mining