Abstract
As the Internet usage keeps increasing, the number of web sites and hence the number of web pages also keeps increasing. A recommendation system can be used to provide person alized web service by suggesting the pages that are likely to be accessed in future. Most of the recommendation systems are base d on association rule mining or based on keywords. Using the association rule mining the prediction rate is less as it doesn’t take into account the order of access of the web page s by the users. The recommendation systems that are key-word based prov ides lesser relevant results. This paper proposes a recommendation system that uses the advantages of sequential pattern mining an d semantics over the association rule mining and ke yword based systems respectively.
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