Time based Web User Personalization and Search

The information on the World Wide Web is growing without bound. Users may have very diversified preferences in the pages they target through a search engine. It is therefore a challenging task to adapt a search engine to suit the needs of a particular user. In mobile search, the interaction between users and mobile devices are constrained by the small form factors of the mobile devices. To reduce the amount of user‟s interactions with the search interface, an important requirement for mobile search engine is to be able to understand the users‟ needs and preferences on that instant and deliver highly relevant information to the users. To effectively aid this task, we propose an efficient approach for web user personalization and search. In our approach, user‟s interests and preferences according to time are extracted by mining time of access, search results and their clickthroughs. User profile will be created and updated using RSVM training. Experimental result shows that, personalization according to time preference improve the effectiveness rate of personalization and search. General Terms Mobile users, Web user Personalization

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