所属单位：外国语学院
教研室：第一英语教研室
发表刊物：2009 International Symposium on Intelligent Ubiquitous Computing and Education
项目来源：省教育厅社科项目
关键字：causal semantic representation; logical rules; generalized information theory
摘要：For reasoning with uncertain knowledge causal semantic analysis is proposed to construct logical rules, which are extracted from decision tree induction and bayes inference based on generalized information theory. These rules can represent multi-level semantic knowledge of the relationship between the data and information implicated. Empirical studies on a set of natural domains show that the semantic completeness of generalized information theory has clear advantage in representing semantic knowledge from different levels.
合写作者：王利民,周爽
第一作者：左欣
论文类型：论文集
页面范围：2
是否译文：否
发表时间：2009-06-16