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Automatically Proving Plane Geometry Theorems Stated by Text and Diagram

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成果类型:
期刊论文
作者:
Gan, Wenbin*;Yu, Xinguo(余新国);Zhang, Ting;Wang, Mingshu
通讯作者:
Gan, Wenbin
作者机构:
[Yu, Xinguo; Gan, Wenbin; Zhang, Ting; Wang, Mingshu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
通讯机构:
[Gan, Wenbin] C
Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
语种:
英文
关键词:
Geometry;Mining;Semantics;Statistical tests;Syntactics;Geometric relations;Geometry theorem;High confidence;Mining methods;Model method;Plane geometry;Relation extraction;theorem understanding;Theorem proving
期刊:
International Journal of Pattern Recognition and Artificial Intelligence
ISSN:
0218-0014
年:
2019
卷:
33
期:
7
页码:
1940003
基金类别:
This work is supported by National Natural Science Foundation of China under Grant 61802142. The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation.
机构署名:
本校为第一且通讯机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
This paper presents an algorithm for proving plane geometry theorems stated by text and diagram in a complementary way. The problem of proving plane geometry theorems involves two challenging subtasks, being theorem understanding and theorem proving. This paper proposes to consider theorem understanding as a problem of extracting relations from text and diagram. A syntax-semantics (S2) model method is proposed to extract the geometric relations from theorem text, and a diagram mining method is proposed to extract geometry relations from diagram...

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