The Personalized Information Retrieval Model Based on User Interest

Abstract

Personalized information retrieval systems can help customers to gain orientation in information overload by determining which items are relevant for their interests. One type of information retrieval is content-based filtering. In content-based filtering, items contain words in natural language. Meanings of words in natural language are often ambiguous. The problem of word meaning disambiguation is often decomposed to determining semantic similarity of words. In this paper, the architecture of personalized information retrieval based on user interest is presented. The architecture includes user interface model, user interest model, detecting interest model and update model. It established a user model for personalized information retrieval based on user interest keyword list on client server, which can supply personalized information retrieval service for user with the communications and collaboration of all modules of the architecture.