Showing papers by "Geun-Sik Jo published in 2001"

Collaborative information filtering by using categorized bookmarks on the web

Abstract: A bookmark means the URL information stored for memorizing a user's own footprints and revisiting that website. This paper regards this bookmark as one of the most meaningful information representing user preferences. An original bookmark indicating only address information is categorized for merging semantic meanings by using public web directory services. These categorized bookmarks are expressed in a hierarchical tree structure. However, most current web directory services cannot afford to normalize and manage the topic hierarchy. There are several kinds of structural incompleteness such as multiple references and heterogeneous tree structures. In order to extract user prefer-ences, this paper proposes a method for driving these problems and the influence propagation methods based on Bayesian networks. Therefore, the preference maps representing users' interests are also established as tree structures. With respect to the user clustering, an approximate tree matching method is used for mapping (overlapping) users' preference maps. It is possible to make queries and process them efficiently according to categories. Finally, this paper is applied to implement collaborative web browsing that can guide and explore the web efficiently and adaptively.

Case-Based Student Model using Knowledge Markup Language for Intelligent e-learning Systems.

Abstract: The knowledge management in e-learning systems is classified into knowledge about students, strategies of teaching and learning, management of the learning content, and the system management. The construction of the student’s knowledge, namely the student model, is a core component used to develop an intelligent e-learning system. The student model can be used as an effective method of learning by constructing a knowledge base in the distributed e-learning system. However, existing e-learning systems have many problems sharing knowledge in a heterogeneous student model and a distributed knowledge base. Because the methods of knowledge representation are different in each e-learning system, the accumulated knowledge cannot be used or shared without a great deal of difficulty. In order to share this knowledge, existing systems must reconstruct the knowledge bases or must incur an extra-cost to convert a knowledge base. Consequently, we propose a new a Case-based student model and a knowledge markup language based on XML in order to overcome these problems. A distributed e-learning system can have the advantage of easily sharing and managing the heterogeneous knowledge base proposed by the student model and CaseML. In this paper, we have done our research based on the design and development of the case-based student model in order to construct an intelligent e-learning system. Furthermore, we have designed and developed a CaseML by using a knowledge markup language.