摘要
结合向量空间技术、Agent技术、Web日志挖掘等技术提出了一个基于概念的数字图书馆个性化信息检索模型。该模型根据用户主动提供的初始信息建立基于概念的用户兴趣模型,利用用户对文档的主动评价和用户的访问行为更新用户兴趣模型,并将用户兴趣模型用于检索结果的相关度排序和最新信息的推荐以及合作推荐。最后给出系统的实现方法。
This paper presents a concept-based personalized information retrieval model in digital library which uses many technologies including vector space, Agent and Web log file mining. This model builds the concept-based user interest profile according to the information provided initiatively by the user, updates the user interest profile according to the user＇s interest information explicitly and the user＇s implicit feedback which is obtained by observing the user action when the user visits the digital library. This model can use the user interest profile in queuing the search result by correlation degree, recommending the latest information to the user and collaboration-based recommending. At last a method of system realization is proposed.
出处
《现代图书情报技术》
CSSCI
北大核心
2006年第3期15-19,共5页
New Technology of Library and Information Service
基金
福建省教育厅社科项目"数字图书馆个性化信息服务研究"(项目编号:JA04042S)研究成果之一。
关键词
数字图书馆
个性化信息检索
用户兴趣模型
Digital library Personalized information retrieval User interest profile
作者简介
E—mail：xcmyxb@public．fz．fj．cn
