Simplifying String Similarity : A Modern Evaluation of Minimum Edit Distance and N-Gram Overlap Efficiency

Text similarity plays a vital role in natural language processing activities such as translation of languages, detection of plagiarism and read-through the spelling of the text. N-gram overlap and Minimum Edit Distance (MED) are two universally used strategy The unique feature of MED are character-level task like mis-spelling rectification, as it evaluate the least amount of insertions, deletions, and substitutions required to convert one string to another. Information retrieval and document clustering are two main applications of the N-gram overlap approach. It analyses the group of adjacent words or characters and also excels in ascribing phrase-level similarities. The main objective of this paper is to discuss the trade-offs and performance metrics that should be considered for each system. This comparative study also analyses the exactness, scalability, and effectiveness of two schemes.