论文部分内容阅读
提出一种基于概念格发现数字图书馆用户浏览行为相关性的信息推送方法。以形式概念分析理论为基础、数据挖掘技术为手段将研究方向相似的用户自动聚类,以用户为对象、用户浏览兴趣为属性构造某一学科下的用户用法概念格,挖掘出用户群中知识点间的关联规则,并根据知识间的相关性为用户推送信息,解决以往推送方法中用户需求获取方式单一以及推送信息与用户信息需求的时效性统一程度低等问题。
This paper proposes a method of information push based on the concept lattice to find out the relevance of users’ browsing behavior in digital library. Based on the formal concept analysis theory, data mining technology is a means to automate clustering of users with similar research directions, user-oriented, user browsing interest as a property to construct user usage concept lattice under a certain discipline, to dig out the knowledge in user base According to the correlation between knowledge, this system can push information to users, and solve the problems of single requirement for user’s requirement acquisition and low timeliness of push information and user information requirements.