Levenshtein Distance Technique in Dictionary Lookup Methods: An Improved Approach

TL;DR

This paper introduces an improved Levenshtein distance method for dictionary lookup, enhancing accuracy by grouping similar characters, which reduces search overhead and improves recognition of ambiguous OCR letters.

Contribution

The paper proposes a novel modification to the Levenshtein distance technique by grouping similar characters, leading to better performance in dictionary lookup tasks.

Findings

Marked improvement over traditional Levenshtein distance

Reduced search overhead in dictionary lookup

Enhanced recognition of ambiguous OCR characters

Abstract

Dictionary lookup methods are popular in dealing with ambiguous letters which were not recognized by Optical Character Readers. However, a robust dictionary lookup method can be complex as apriori probability calculation or a large dictionary size increases the overhead and the cost of searching. In this context, Levenshtein distance is a simple metric which can be an effective string approximation tool. After observing the effectiveness of this method, an improvement has been made to this method by grouping some similar looking alphabets and reducing the weighted difference among members of the same group. The results showed marked improvement over the traditional Levenshtein distance technique.