A Study on Web Usage Mining Theory and Applications

Abstract

World Wide Web is an enormous store of links and web pages. It provides huge amount of information for the Internet clients. The development of web is great as about one million pages are added every day. Users' accesses are traced in web logs. Because of the great usage of web, the web log files are increasing at a more rapidly rate and the range is becoming enormous. Web Usage Mining relates mining techniques in log data to extract the performance of users which is used in different applications like Support to the Design, E-commerce, Modified services, pre-fetching etc. Web usage mining has three phases as preprocessing, pattern detection and pattern learning. Web log data is generally noisy and confusing, thus preprocessing and pattern analysis is an essential method before mining. For learning patterns gathering are to be constructed professionally. This paper is presents work done in the web usage mining. Finally a glance of various applications of web usage mining is presented. Web Usage Mining has develop into a dynamic region of study in field of data mining because of its crucial values. This paper affords a widespread conversation of the all the stages in Web Usage Mining and Problems with related works in this research areas.