For accessing the information from web log, this is very important task and this task can be accomplished by web usage mining technique. Through web usage mining technique we can find out visitors behavior which can automatically and very fast access intrinsic information from huge amount of web log data, such as interesting access path, identify the user, accessing the web page group, web user clustering and web pre-fetching. Web usage mining is milestone for decision making process for an organization. Data preprocessing is very important concepts for the mining process. If our web log data is preprocessed then we can easily find out the desire information about visitor and also retrieve other hidden information from web log data. In this paper we focus on data preprocessing technique of web usage mining, after completion of data preprocessing, any king of irrelevant information can be sort out. We have also proposed an algorithm and its implementation for web log preprocessing in web usage mining. Every page has been assigned with an individual token. According to this token and frequency, data mining technique (Classification, Association Rules, and Clustering) can be applied. In this article we can easily find the highest and lowest value according to page access frequency.

Web Usage Mining, Preprocessing, Web Log Data, Frequency, Clustering

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