使用图形重写的数学识别

Ann Grbavec, D. Blostein
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引用次数: 82

摘要

本文研究了图形重写作为二维数学符号高级识别的一种工具。“高级识别”是根据符号识别器的输出确定图表含义的过程。高级数学识别的特征问题包括:确定符号的递归子表达式的分组和解决依赖于全局上下文的歧义。我们的图重写方法使用了数学符号约定的知识,例如运算符优先级和运算符范围,比语法方法或以前的结构方法更有效。图形重写为操作二维模式提供了灵活的形式和强大的理论基础。它已被证明是一种有用的技术,用于高级识别电路图和乐谱。通过展示用于数学识别的图形重写策略,本文为图形重写作为图形识别的通用工具提供了进一步的证据,并确定了在探索这种潜力时必须考虑的一些问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematics recognition using graph rewriting
This paper investigates graph rewriting as a tool for high-level recognition of two-dimensional mathematical notation. "High-level recognition" is the process of determining the meaning of a diagram from the output of a symbol recognizer. Characteristic problems of high-level mathematics recognition include: determining the groupings of symbols into recursive subexpressions and resolving ambiguities that depend upon global context. Our graph-rewriting approach uses knowledge of the notational conventions of mathematics, such as operator precedence and operator range, more effectively than syntactic or previous structural methods. Graph rewriting offers a flexible formalism with a strong theoretical foundation for manipulating two-dimensional patterns. It has been shown to be a useful technique for high-level recognition of circuit diagrams and musical scores. By demonstrating a graph-rewriting strategy for mathematics recognition, this paper provides further evidence for graph rewriting as a general tool for diagram recognition, and identifies some of the issues that must be considered as this potential is explored.
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