The use of syntax trees in order to automate the correction of LaTeX documents

Abstract

The problem is to automate the correction of LaTeX documents. Each document is represented as a parse tree. The modified Zhang-Shasha algorithm is used to construct a mapping of tree vertices of the original document to the tree vertices of the edited document, which corresponds to the minimum editing distance. Vertex to vertex maps form the training set, which is used to generate rules for automatic correction. The statistics of the applicability to the edited documents is collected for each rule. It is used for quality assessment and improvement of the rules.

Keywords

• automation
• editing distance
• LaTeX
• lexeme
• machine learning
• metric
• parse tree
• regular expression
• reinforcement learning
• syntax tree
• text analysis
• token