Intelligent Information Retrieval System for the Metadata of Korean Technical Journals

초록

In this paper, we present the framework design and implementation issues of metadata retrieval system called IMAS for Korean technical journals with the capability of user adaptation. Even though much research has been performed on the development of efficient retrieval engines, most of them have focused on the performance of the system but not friendly and efficient user interface. The satisfaction of users is at least as important as the functionality and performance in retrieval systems. Therefore, sophisticated user interface is critical for a successful design. Intelligent user interface methodology is employed to make a metadata system more intelligent, natural, and efficient. Human-computer interaction model called H-COS is presented for the IMAS, and the IMAS is designed and implemented based on the model. Decision tree based CBR(Case-Based Reasoning) and neural network have been employed for long term and short term adaptations, respectively.