{"title":"理解显式算术字问题和显式平面几何问题使用语法-语义模型","authors":"Xinguo Yu, Wenbin Gan, Mingshu Wang","doi":"10.1109/IALP.2017.8300590","DOIUrl":null,"url":null,"abstract":"This paper presents two algorithms for understanding explicit arithmetic word problems (EAWPs) and explicit plane geometry problems (EPGPs) following the sharing approach, respectively. This approach proposed in this paper models understanding math problems as a problem of relation extraction, instead of as the problem of understanding the semantics of natural language. Then it further proposes a syntax-semantics (S2) model method to extract math relations. The S2 model method is very effective in that only 116 models can extract most of relations in EAWPs and that only 48 models can extract most of relations in EPGP texts. The experimental results show that the proposed algorithms can understand EAWPs and EPGPs very well.","PeriodicalId":183586,"journal":{"name":"2017 International Conference on Asian Language Processing (IALP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Understanding explicit arithmetic word problems and explicit plane geometry problems using syntax-semantics models\",\"authors\":\"Xinguo Yu, Wenbin Gan, Mingshu Wang\",\"doi\":\"10.1109/IALP.2017.8300590\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents two algorithms for understanding explicit arithmetic word problems (EAWPs) and explicit plane geometry problems (EPGPs) following the sharing approach, respectively. This approach proposed in this paper models understanding math problems as a problem of relation extraction, instead of as the problem of understanding the semantics of natural language. Then it further proposes a syntax-semantics (S2) model method to extract math relations. The S2 model method is very effective in that only 116 models can extract most of relations in EAWPs and that only 48 models can extract most of relations in EPGP texts. The experimental results show that the proposed algorithms can understand EAWPs and EPGPs very well.\",\"PeriodicalId\":183586,\"journal\":{\"name\":\"2017 International Conference on Asian Language Processing (IALP)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Asian Language Processing (IALP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IALP.2017.8300590\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Asian Language Processing (IALP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IALP.2017.8300590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Understanding explicit arithmetic word problems and explicit plane geometry problems using syntax-semantics models
This paper presents two algorithms for understanding explicit arithmetic word problems (EAWPs) and explicit plane geometry problems (EPGPs) following the sharing approach, respectively. This approach proposed in this paper models understanding math problems as a problem of relation extraction, instead of as the problem of understanding the semantics of natural language. Then it further proposes a syntax-semantics (S2) model method to extract math relations. The S2 model method is very effective in that only 116 models can extract most of relations in EAWPs and that only 48 models can extract most of relations in EPGP texts. The experimental results show that the proposed algorithms can understand EAWPs and EPGPs very well.