摘要
针对现有的个性化信息检索系统存在的问题,提出一种新的基于用户兴趣的个性化Web信息检索方法,采用自动隐式学习方式来建立和更新用户兴趣库,采用本体技术来进行语义扩展,从而提高Web信息检索的查准率和查全率。文中给出了个性化Web信息检索系统的体系结构和个性化机制的关键技术及相关算法,全面描述了基于用户兴趣的个性化处理过程。该方法能更好地满足用户的需求,为其提供个性化服务。
We present a new personalized web information retrieval method based on interest to solve the problem that existing personalized information retrieval systems have not consider. We use auto implicit learning algorithm to create and update user profile, and use ontology technology to do query expansion. Therefore, the web information retrieval system＇s precision and recall will be improved. A framework of the system and key technologies or relevant algorithms of the personalized mechanism are given in the paper. And the processing of users＇ personalized information retrieval based on interest is discussed thoroughly. We proposed approach can better answer users＇ needs and provide personalized services for them.
出处
《电子设计工程》
2010年第7期60-62,共3页
Electronic Design Engineering
关键词
个性化
信息检索
个体
用户兴趣
personalization
information retrieval
ontology
user profile
