关键词: 语用分析, 关联推理, 模糊概念图, 认知语境

Abstract: Focused on the issue that computer cannot automatically carry out a pragmatic analysis of the deep meaning    of whole discourse at present, this paper designs the relevance inference algorithm based on fuzzy conceptual graph. In the algorithm, aiming at the specific dialog mode of Chinese pragmatic analysis, the discourses of speakers and the knowledge of cognitive context are expressed in fuzzy conceptual graph, and the relevance inference is conducted from computer science. The problem that computer automatically deduces the deep meaning of whole discourse is resolved. Through the experimental analysis, accuracy can reach 78%. In addition, the algorithm has been applied in analyzing public opinion and mining social network. After the preprocessed discourses of speaker by this relevance inference algorithm based on fuzzy conceptual graph, this algorithm can reduce the missed alarm rate and false alarm rate of Mutton and AdaBoost methods based on multi-features fusion and increase the accuracy of SBV polar transfer algorithm. The algorithm can deduce the deeper meaning of answerer??s discourse at specific dialog mode.

Key words:  pragmatic analysis, relevance inference, fuzzy conceptual graph, cognitive context