2016 International Conference on Big Data and Smart Computing (BigComp) (2016)
Hong Kong, China
Jan. 18, 2016 to Jan. 20, 2016
Keejun Han , Dept. of Knowledge Service Engineering, KAIST, Daejeon, South Korea
Eunkyung G. Lee , Dept. of Knowledge Service Engineering, KAIST, Daejeon, South Korea
Hyunwoo Je , Dept. of Knowledge Service Engineering, KAIST, Daejeon, South Korea
Mun Y. Yi , Dept. of Knowledge Service Engineering, KAIST, Daejeon, South Korea
Experiential knowledge is knowledge obtained through reflection on experience. In case of experiential knowledge within a specialized domain, this knowledge is strengthened over time as a field expert accumulates more experience in the chosen field. However, it is unfortunate that the knowledge is often confined within each individual in implicit form and it is hardly well-managed by an organization. Although there are several systems designed to acquire and exploit experiential knowledge, escalating maintenance costs pose serious challenges to their adoption and continuous use. In this paper, we propose a new knowledge-based system that acquires experiential knowledge through natural interactions with domain experts and keeps it growing by adding specialization rules, thereby reducing maintenance costs substantially. We also present the overall flow of how the acquired knowledge is processed and applied to decision supporting process, particularly in diagnosing potential diseases from blood tests.
Knowledge engineering, Knowledge based systems, Maintenance engineering, Reliability, Pathology, Decision making
Keejun Han, E. G. Lee, Hyunwoo Je and M. Y. Yi, "Introducing experiential knowledge platform: A smart decision supporter for field experts," 2016 International Conference on Big Data and Smart Computing (BigComp)(BIGCOMP), Hong Kong, China, 2016, pp. 404-407.