ILS中知识的聚类和表示

在网络教育中，传统的导航方式或搜索引擎方式引导学习过程有着自身固有的缺陷，无法实现智能化、个性化学习，采用一种反映知识模块间关系的知识混合结构方式，通过对知识的规范录入和基于关联规则的知识聚类，得到一系列相关的知识项，以知识项和知识交流域(上下文)的映射来引导学习过程，能智能地向学习者提供建议性的相关学习内容及上下文，是一种有效的智能学习解决方案。

Knowledge representing and clustering in intelligent learning system

In network- based education, a traditional navigator or a searching engine had some inherent weaknesses, so individualized intelligent learning has been difficult to realize. This paper presenteds a combined knowledge structure which reflecteds the relationships among knowledge modules. A series of association knowledge items was obtained by standardizing input ways and knowledge clustering based on association rules. Based on the mapping of knowledge items to the knowledge domain, the proposed knowledge representing and clustering in intelligent learning system could provide the learner intelligent clues of association learning which is an effective scheme of intelligent learning.