The web is an important source of information retrieval in the present scenario and users belonging to various backgrounds access the internet. Internet is in reach of everyone and its users are increasing day by day. So it is very important in this competitive world here in terms of e- commerce, the companies should know the needs and demands of user. The usage information about the users is recorded in logs of web server which are called as web logs. These web log files are analyzed for the purpose of pattern extraction which is useful, this technique of data mining commonly known as web usage mining. Accuracy in the results of mining of logs of web and efficient prediction of patterns of users navigating online are very necessary as these results help in websites tune up for the users. Actually web log at their first place are not meant for this process of web log mining, they are just stored at server for record. The process of Web log mining initiates with cleaning then data preparation which is termed as data pre-processing, it extracts some hidden knowledge which cannot be found out by using any other conventional methods. For good result better quality of input is required so more emphasis is on cleaning and preprocessing of data. Knowledge obtained is then mined and then it is analyzed which predicts out the user's online behavior and activity pattern. In my research work I have implemented the same phases of web usage mining i. e. pre-processing of web log and Fuzzy C - Mean algorithm is applied on the knowledge gained and then analyzed for users navigation results.

Web Mining Pattern Analysis Navigation Pattern