计算机科学 ›› 2013, Vol. 40 ›› Issue (8): 196-199.

• 人工智能 • 上一篇    下一篇

面向平面几何命题理解的融合算法研究

黄焕,刘清堂,陈矛   

  1. 华中师范大学国家数字化学习工程技术研究中心 武汉430079;华中师范大学国家数字化学习工程技术研究中心 武汉430079;华中师范大学国家数字化学习工程技术研究中心 武汉430079
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(61272205),中央高校基本科研业务费项目(CCNU10C01003)资助

Merging Algorithm Research Oriented to Understanding of Geometry Proposition

HUANG Huan,LIU Qing-tang and CHEN Mao   

  • Online:2018-11-16 Published:2018-11-16

摘要: 随着初等几何命题可视化机器证明的发展,如何让几何教学辅助软件能够直接理解几何命题的含义,自动生成对应的几何图形并进行推理证明,成为当前研究的一个新问题。现有的几何命题理解方法虽然在一定程度上实现了几何命题向形式化命令的转化,但是这些方法均没有考虑几何命题中分句间的逻辑关系,无法解决分句间形式化命令的冗余和冲突问题,导致后期自动作图和推理的准确率不高。针对这一问题,在前期工作的基础上提出了一个几何命题分句间形式化命令融合算法,并将该融合算法集成应用于已有的自然语言几何作图接口进行实验论证。结果显示,几何命题分句间形式化命令融合算法将自然语言几何作图的准确率从原来的84.17%提高到了91.67%,能够有效提高几何命题理解的准确性。

关键词: 几何命题,融合算法,几何作图,自然语言

Abstract: As the development of machine proof technology,how to make the existing geometry instructional softwares to understand the latent semantics of the geometry proposition,automatically generate the figure and give out the reasoning process,is becoming a new challenge.Although the existing methods can transform the geometry proposition into figure or other machine-readable forms to a certain extent,they do not consider the dependent relationship between simple clauses,so they can not avoid the redundancies and inconsistence between construction commands of adjacent simple clauses.To resolve this problem,this paper proposed a merging algorithm,and further integrated the merging algorithm into exist natural language interface for automatic geometry construction to verify its effectiveness.The experiment results suggest that the merging algorithm can enhance the accuracy of automatic geometry construction from 84.17% to 91.67%,and can improve the accuracy of geometry proposition understanding.

Key words: Geometry proposition,Merging algorithm,Geometry construction,Natural language

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