Abstract:
String similarity measures play an increasingly important role in text related
research and applications in tasks and operate on string sequences and character
composition. A string metric is a metric that String_Based measures similarity or
dissimilarity (distance) between two strings for approximate string matching or
comparison. Determining similarity between texts is crucial to many applications such
as clustering, duplicate removal, merging similar topics or themes, text retrieval and
etc.
String matching algorithms are used to find the similar characters between the
source string and the target string. The proposed system is intended to match song
information by comparing Levenshtein Distance Algorithm and Needleman-Wunch
Distance Algorithm based on their f-score and execution time. So, user can search
effectively their required song information by the title of songs or artist name using
English language. Then the proposed system retrieves the user’s required song
information with similarity score. The matching efficiencies of these algorithms are
compared by searching f-score and the execution time. The proposed system uses
song title and artist feature of billboard song dataset from year 1965-2015 and
implements using Java programming language.
