Inferring the user interests using the search history

Personalization involves the process of gathering user-specific information during interaction with the user, which is then used to deliver appropriate results to the user’s needs. This paper presents a statistical method that learns the user interests by collecting evidence from his search history. The method focuses on the use of both user relevance point of view on familiar words in order to infer and express his interests and the use of a correlation metric measure in order to update them.