为解决传统搜索引擎个性化的局限性问题，在研究用户感兴趣搜索引擎现状基础上，通过多Agent较全面记录、分析用户搜索的行为，提出了一种新的综合用户搜索行为，构建用户感兴趣搜索引擎研究框架——

基于多Agent搜索行为分析的用户兴趣模型。研究结果表明，依据用户搜索行为构建用户兴趣模型，使搜索引擎返回结果更贴近用户需求。满足用户个性化服务，提高了信息搜索的查全率和查准率。-In order to solve the limitations of search engine personalization issues of interest to users in the study based on the status of the search engine, through a more comprehensive record of more than Agent, analysis of user search behavior, a new integrated user search behavior, build the user a sense of Research interest in the framework of the search engine- search for Behavior Analysis Based on Multi-Agent user interest model. The results show that the user search behavior based on user interest model is constructed so that the search engine returns results more close to user needs. Personalized services to meet customers and improve the information search recall and precision.