An Approach Proposed for Detecting Users activities from Recorded Log

The development of the web has created a big challenge for directing the client to the website pages in their area of interest. Accordingly, just option is to capture the intuition of the client and provide them a list of recommendation. Most specifically, online navigation activities develop with day by day; consequently extract information with the capability of intelligence, from these activities is a tedious job. Webmaster of an organization ought to utilize methods of web mining to fetch intuition, Web usage mining (WUM) is one among them.WUM is designed to operate on web server logs; logs contain client's navigation history which is very useful for the web recommendation. Recommendation is an application of web usage mining. Consequently, recommendation system can be utilized to forecast the navigation pattern of client and recommend those to client in a form of recommendation list. This paper, suggest a recommendation principal that recommends a list of pages on the basis of client's past navigation history (recorded within the web log). This approach brings the advance within the precision of displayed pages for the client or users.

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