{"title":"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","authors":"Litian Huang, Xinguo Yu, Bin He","doi":"10.1109/IEIR56323.2022.10050038","DOIUrl":null,"url":null,"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.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"84 Pt 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Novel Geometry Problem Understanding Method based on Uniform Vectorized Syntax-Semantics Model\",\"authors\":\"Litian Huang, Xinguo Yu, Bin He\",\"doi\":\"10.1109/IEIR56323.2022.10050038\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":183709,\"journal\":{\"name\":\"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)\",\"volume\":\"84 Pt 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEIR56323.2022.10050038\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEIR56323.2022.10050038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Geometry Problem Understanding Method based on Uniform Vectorized Syntax-Semantics Model
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.