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The availability of data and information across the internet grows exponentially with time. The web acts as a powerful and useful tool for users to access and retrieve relevant information. Search engines play a vital role in bringing relevant information to the users on a query basis. Web page recommendation systems play a vital role in identifying users' information requirements and make their browsing efficient. Numerous web page recommendation systems are built that chooses as well as suggests online pages that are appropriate with users need of the hour. In current years, there is raising attention in using data mining techniques in the web content to construct web page recommendation systems. The primitive data mining techniques are not found to be efficient owing to their incapability to handle the pages that are created dynamically. PASO-WPR can carry out dependent upon incorporating semantic info with data mining techniques on the web usage data as well as clustering of pages dependent upon similarity in their semantics.