Emergent Mind

Abstract

The problem of parsing has been studied extensively for various formal grammars. Given an input string and a grammar, the parsing problem is to check if the input string belongs to the language generated by the grammar. A closely related problem of great importance is one where the input are a string ${\cal I}$ and a grammar $G$ and the task is to produce a string ${\cal I}'$ that belongs to the language generated by $G$ and the `distance' between ${\cal I}$ and ${\cal I}'$ is the smallest (from among all the strings in the language). Specifically, if ${\cal I}$ is in the language generated by $G$, then the output should be ${\cal I}$. Any parser that solves this version of the problem is called an {\em error correcting parser}. In 1972 Aho and Peterson presented a cubic time error correcting parser for context free grammars. Since then this asymptotic time bound has not been improved under the (standard) assumption that the grammar size is a constant. In this paper we present an error correcting parser for context free grammars that runs in $O(T(n))$ time, where $n$ is the length of the input string and $T(n)$ is the time needed to compute the tropical product of two $n\times n$ matrices. In this paper we also present an $\frac{n}{M}$-approximation algorithm for the {\em language edit distance problem} that has a run time of $O(Mn\omega)$, where $O(n\omega)$ is the time taken to multiply two $n\times n$ matrices. To the best of our knowledge, no approximation algorithms have been proposed for error correcting parsing for general context free grammars.

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