个性化知识服务中基于Ontology的用户兴趣挖掘研究

Research on Ontology-Based User Interests Mining in Personalized Knowledge Services

个性化知识服务是知识经济时代信息服务发展的必然趋势，是满足信息用户多样化、专门化知识需求的高层次服务模式。用户兴趣知识的挖掘和用户兴趣模型的建立是个性化知识服务的重要研究内容。本文将Ontology技术与个性化知识服务结合起来，研究用户兴趣知识的Ontology表示，并以此为基础提出了一种动态的用户兴趣学习和挖掘方法，分析了该方法中参考Ontology的建立、用户兴趣知识的初步学习和用户兴趣模型的完善等关键步骤。研究结果表明，基于Ontology的用户兴趣挖掘可以较为准确地表示、跟踪和学习用户的个性化知识，实现隐性用户兴趣的发现和利用，满足用户特殊的信息需求，是一种提高个性化知识服务质量的有效方法。

In current times of knowledge economy, personalized knowledge services is the inevitable trend of information services development, and it is a high level service pattern to satisfy users＇ diversified and specialized knowledge requirement. The mining of user interests and the building of user profile are essential to personalized knowledge services research. In this paper, we introduced Ontology into this research, and studied the representation of user interests knowledge using Ontology, and based on which, developed a dynamic method of learning and mining user interests. We analyzed the three key steps of this method including reference Ontology building, user interests knowledge primitive learning and user profile optimizing. The conclusion of our study shows that Ontology-based user interests mining can better represent, trace and learn personalized user knowledge, realize the discovery and utilization of user implicit interests, and satisfy users＇ special information needs so that it can provide personalized knowledge services of good quality.