Web Log Mining, also known as Web Usage Mining (WUM) is the application of Data Mining techniques, which is applied on web log data to extract interesting patterns. An enormous increase in the use of web applications as medium of the organizations and institutions, the web page hits are consistently increasing. The web servers have the facility to save the web navigational sequence as web log file. The enormous amount of irrelevant information in the web log file demands proper preprocessing. This renders the file, with the intent of making it more appropriate for a variety of downstream purposes such as analytics. There are various traditional techniques involved in preprocessing. The implementation of preprocessing model presented in this paper over other traditional preprocessing methods is to employ an efficient Structured Query Language (SQL) based technique. The proposed SQL based preprocessing technique reduces process time drastically. The resulting structured log file is well suited for further pattern mining and analytics.

Preprocessing, Web Log Mining, Server log, User Identification, Session Identification

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