Enhancing personalized web search re-ranking algorithm by incorporating user profile

In order to solve the problems of information overload on the web when searching for concrete information, the current information retrieval algorithms need to be improved. It is difficult to find satisfactory information that accurately matches user information needs even if it is present in the web database. Hence, much more "intelligence" should be embedded to retrieval algorithms to provide better search, retrieval, filtering and present relevant information according to individual needs. This paper presents an analysis and overview of the next generation search and retrieval in the context of personalization which is going to bring a new dimension in the field of information technology by giving a better search and retrieval facility on the web. Current web search engines are designed in such a way that the needs of any individual user are not understood and it satisfy users without considering the particular needs. Personalization of web search enables the users to obtain relevant information by incorporating individual interests and preferences. An enhanced web search re-ranking algorithm is proposed by incorporating user information obtained from various sources. The proposed algorithm is implemented in java and experimented with real time datasets and proved that the retrieval quality is improved and individual needs are addressed.