An online navigation behavior grows each passing day, and thus extracting information intelligently from it is a difficult issue. Web Usage Mining (WUM) is the process of extracting knowledge from Web users access data by exploiting Data Mining technologies. It can be used for different purposes such as personalization, system improvement and site modification. In our propose work, user navigation patterns describe as the common browsing behaviors among a group of users. Since many users may have common interests up to a point during their navigation, navigation patterns should capture the overlapping interests or the information needs of these users. In addition, navigation patterns should also be capable to distinguish among web pages based on their different significance to each pattern. we would perfect the algorithm and apply some classification methods for classifying user request. This can be used in WUM based prediction systems. We proposed a complete generic framework that utilizes underlying domain ontology available at web applications. On which any sequential pattern mining algorithm can fit.

Ontology, Semantic Distance , Next Page Request Prediction ,Web Prefetching

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