初等数学应用题题意理解中的常识库系统构建

类人计算领域, 题意的机器理解是数学应用题自动求解的难点. 常识性知识的缺失直接影响到题意理解的准确性. 本研究以常识为研究对象, 收集了历年初等数学古典概型的典型案例, 分析了古典概型类应用题的常识特征, 并进行了常识类型划分; 设计了XML结构存储常识性知识, 构建常识库系统实现古典概型常识的分类、表征及存储, 辅助计算机进行题意理解. 通过典型案例的应用, 其结果显示本研究构建的常识库对古典概型应用题的题意正确理解是十分有帮助的.

Constructing of Commonsense Knowledge Base in Problem Understanding of Elementary Mathematics

In the field of artificial intelligence, problem understanding has always been one of the most important and difficult problems in the automatic solution of mathematical application problems. In this work, we systematically studied the problem of lacking commonsense knowledge in solving elementary mathematical problems, and constructed a commonsense knowledge base to assist computer in problem understanding. We collected the real and simulated questions of the classical probability for college entrance examination over the years as the research object. On the basis of in-depth analysis of topics, this study put forward the concept of commonsense knowledge definition, analyzed and classified its features, and stored commonsense knowledge with XML tags. On this basis, the commonsense knowledge base was applied in practice. The experimental results indicate that the commonsense knowledge base constructed in this study is very helpful for the automatic solution of classical probabilistic application problems.