A Novel Framework for Personalized Web Search

One hundred users, one hundred needs. Current web search engines are built to serve all users, independent of the needs of any individual user. Personalized web search is considered as a promising solution in this direction and is an area of immense research potential. The main objective of this paper is to establish the significance of evolutionary techniques for providing personalized web search. The paper provides a framework of interactive personalized query expansion model that provides a thematically rich query expansion. The model uses knowledge base at the back end. The knowledge is derived from knowledge rich open directories and user's browsing history. User's browsing history helps in identifying the needs of user, while open directories provide topic specific knowledge that act as a source for selecting the terms for expanding the query. Further Genetic algorithm has been used to select thematically rich term for expansion. The model offers the personalization at query crafting itself.