Using Rough Set Theory to Construct E-Learning FAQ Retrieval Infrastructure

摘要：

We propose a framework of e-Learning FAQ (frequently asked questions) retrieval system by applying hierarchical agglomerative clustering method and rough set theory. We try to provide a possible solution to improve the learning performance of e-Learning system. The clustering method and FAQ collection are used to construct a FAQ clustering concept hierarchy. Then, we use lower/upper approximations in rough set theory to classify users’ queries. The rough set theory can help solve uncertain problem well. Finally, the relevant FAQs for the user query are generated. The relevant FAQs are those in the cluster to which the user query is assigned.

关键词： e-learning Frequently asked questions Hierarchical agglomerative clustering method Rough set theory Concept hierarchy

作者: Deng-Yiv Chiu Ya-Chen Pan Wen-Chih Chang

作者单位: Department of Information Management,Chung Hua University,HsinChu,Taiwan 300,China

会议类型: 国际会议

会议名称: The First IEEE International Conference on Ubi-Media Coputing and Workshops(第一届泛媒体处理国际会议)

会议地点: 兰州

会议语种:英文

在线出版日期: 2008-07-15（万方平台首次上网日期，不代表论文的发表时间）