A fuzzy ontology for geography knowledge of China's College Entrance Examination

Abstract

Aiming at the Knowledge Based System of the robots which will attend China's College Entrance Examination in a few years, we propose a fuzzy ontology for geography knowledge representation. Once a multiple-choice question is input into the system, it will be translated into ontology language and trigger the reasoning processes to acquire the answer. Different from classical ontologies, the descriptions of questions in natural languages can be better handled with fuzzy ontology, which allow us to reason about vague, incomplete, and uncertain knowledge. This paper mainly introduce fuzzy ontology techniques which are applied to our prototype system. As a result, we demonstrate that the inclusion of fuzzy concepts and relations in the ontology provide benefits during the reasoning process with respect to crisp approaches.