A knowledge representation selection criteria
Date of Publication
Master of Science in Teaching in Computer Science
College of Computer Studies
Defense Panel Chair
Defense Panel Member
Jopillo, Marilou Jopillo
Kang Mun Arturo Tan
Work in AI concerns the nature and functioning of knowledge wherein flexible representations are required in order to understand and generate expert behavior. Growing interest in generating expert behavior through the use of expert system/decision support system technology raises the issue on the importance of knowledge representation (KR) for this technology as several existing knowledge representation schemes affect and effect inference in significantly different ways. As a result, knowledge engineer (KE) is, often, failed to come up with a correct representational framework to formulate knowledge in a way the system is expected to behave. Furthermore, the unavailability of a relevant criteria for a good knowledge representation scheme itself has been a basic and big barrier in their work. Thus, this study focuses on: 1) properties of consistent knowledge representation framework and designs a criteria set 2) analysis and evaluation of existing KR schemes on the basis of designed criteria set thereby, giving aid to KE to select ideal KR scheme based on a relevant criteria. This study can be extended with the implementation of the KR schemes and can be evaluated according to the designed criteria set to obtain performance measurements for different problem domains.
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
 p., 28 cm.
Knowledge representation (Information theory)
Wadhwa, N. (1989). A knowledge representation selection criteria. Retrieved from https://animorepository.dlsu.edu.ph/etd_masteral/1216