Study on Visual Knowledge Structure Reasoning

Abstract

Intelligent Topic Map (ITM) embodies the multi-level, multi-granularity and the inherent relevant characteristics of knowledge. With ITM as infrastructure, this paper presents a visual knowledge structure reasoning method integrates the logic-based knowledge reasoning and the structure-based knowledge reasoning. The logic-based knowledge reasoning implements knowledge consistency checking and the implicit associations reasoning between knowledge points, it can help us obtain the optimal description of knowledge. In order to construct the complete knowlege structure, a Knowledge Unit Circle Search strategy for structure-based knowledge reasoning is proposed, by which more detailed semantic association of knowledge is provided and the inherent relevant characteristics of knowledge is obtained. The knowledge reasoning results are visualized by ITM, which provides a visual knowledge map. It is available for users to acquire the knowledge and associations among them. A prototype system has been implemented and applied to the massive knowledge organization, management and service for education.