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As the number of Internet users and accessible Web pages grows; it is becoming increasingly difficult for users to find documents that are relevant to their particular needs. Users must either browse through a large hierarchy of concepts to find the information for which they are looking or submit a query to a publicly available search engine and wade through hundreds of results, most of them irrelevant. The core problem is that whether the user is browsing or searching, whether they are novice web users or experts, the identical information result is retrieved and presented commonly without any difference. The goal of Web search personalization is to tailor search results to a particular user based on that user's interests and preferences, thus allowing for more efficient and relevant information access. Personalization of information retrieval involves two major challenges: identifying the user context and organizing them in such a way that improves the search precision. This leads to the development of user profiles in a hierarchical structure namely ontology for user profiles. The main goal of this paper is to propose a technique that implicitly builds ontology-based user profiles. We build and update profiles dynamically by monitoring and storing the user's browsing habits.