With the huge amount of data in web, web mining is the process to extract useful data from web. Web usage mining is the type of web mining to retrieve data from web in form of logs, and it is also called web log mining. Web log mining extract useful pattern or information from log files and it help to determine user behaviour. In this paper we proposed an algorithm for data pre-processing and personalization in web usage mining. Firstly collect the data from server and merge these log files into single log file. After collection of data separate each field using field separate algorithm, then cleaning the data to remove noise and unwanted data and after personalize these data for further used.

Data Cleaning, Data field Extraction, Cluster, Session Identification, User Identification, Pre-processing, personalization.

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