摘要：Now a day World Wide Web become very popular and collaborative for transferring of information. The web is huge, diverse and active and thus increases the scalability, multimedia data and temporal matters. The several kinds of data have to be organized in a manner that they can be accessed by several users effectively and efficiently. So the usage of data mining methods and knowledge discovery on the web is now on the spotlight of a boosting number of researchers. Web mining is the extraction of exciting and constructive facts and inherent information from artifacts or actions related to the WWW. Web usage mining is a kind of data mining method that can be useful in recommending the web usage patterns with the help of users' session and behavior. Web usage mining includes three process, namely, preprocessing, pattern discovery and pattern analysis. After the completion of these three phases the user can find the required usage patterns and use this information for the specific needs. Web usage mining requires data abstraction for pattern discovery. This data abstraction is achieved through data preprocessing. In this paper we survey about the data preprocessing activities like data cleaning, user identification, session identification, path completion
