Comparison of Levenshtein Distance Algorithm and Needleman-Wunsch Distance Algorithm for String Matching

String similarity measures play anincreasingly important role in text related researchand applications in tasks and operate on stringsequences and character composition. A string metricis a metric that String_Based measures similarity ordissimilarity (distance) between two strings forapproximate string matching or comparison.Determining similarity between texts is crucial tomany applications such as clustering, duplicateremoval, merging similar topics or themes, textretrieval and etc. Among many methods of Stringsimilarity, Levenshtein Distance Algorithm andNeedleman-Wunsch Distance Algorithm are used inthis proposed system. The proposed system intendedto present by comparing Levenshtein DistanceAlgorithm and Needleman-Wunsch DistanceAlgorithm based on their f-score. So, user can searcheffectively the required song by typing the title ofsongs or artist name using English language in thisproposed system. Then the proposed system retrievethe user’s required song information with similarityscore. The matching efficiencies of these algorithmsare compared by searching f-score and executiontime. The proposed system uses song title and artistfeature of billboard song dataset from year 1965-2015 and implements using Java programminglanguage