A Novel Geometry Problem Understanding Method based on Uniform Vectorized Syntax-Semantics Model

Litian Huang, Xinguo Yu, Bin He
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引用次数: 1

Abstract

The first step in solving geometry problems is to understand problems, and automatic understanding of geometry problems by computers has always been a challenge due to the massive advanced knowledge implied in the text and diagram. This paper proposes a method for geometry problem understanding based on vectorized Syntax-Semantics (S2) model. The proposed method divides the understanding of geometry problems into three parts. Firstly, we modified and optimized vectorized S2 model for understanding explicit arithmetic word problems, and applied it to the text understanding of geometry problems to extract basic geometric relations. Then, based on the idea that a diagram is an extension of problem text, we designed vectorized S2 model of diagram understanding according to the same framework as that of text understanding. All geometry diagrams are transformed into vectors for understanding in a uniform way. Finally, we designed a derived relations generation model based on the diagramet theory to extract derived geometric relations from the basic relations. Experimental results show that the proposed method is effective in understanding geometry problems with diagrams.
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一种基于统一向量化语法语义模型的几何问题理解新方法
解决几何问题的第一步是理解问题,由于文本和图表中隐含的大量高级知识,计算机自动理解几何问题一直是一个挑战。提出了一种基于向量化语法语义(S2)模型的几何问题理解方法。该方法将对几何问题的理解分为三个部分。首先,对理解显式算术字词问题的矢量化S2模型进行改进和优化,并将其应用于几何问题的文本理解中,提取基本几何关系。然后,基于图是问题文本的扩展这一思想,按照与文本理解相同的框架,设计了图理解的矢量化S2模型。为了便于理解,所有的几何图形都被统一转化为矢量。最后,设计了基于图论的派生关系生成模型,从基本关系中提取派生的几何关系。实验结果表明,该方法对图形几何问题的理解是有效的。
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