A Personalized Search Algorithm by Using Content-Based Filtering

Abstract

Traditional information retrieval technologies satisfy users need to a great extent. However, for their all-purpose characteristics, they can not satisfy any query from the different background, with the different intention and at the different time. A personalized search algorithm by using content-based filtering is presented in this paper. The user model is represented as the probability distribution over the domain classification model. A method of computing similarity and a method of revising user model are provided. Compared with the vector space model, the probability model is more effective on describing a users interests.