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. Among many methods of String
similarity, Levenshtein Distance Algorithm and
Needleman-Wunsch Distance Algorithm are used in
this proposed system. The proposed system intended
to present by comparing Levenshtein Distance
Algorithm and Needleman-Wunsch Distance
Algorithm based on their f-score. So, user can search
effectively the required song by typing the title of
songs or artist name using English language in this
proposed system. Then the proposed system retrieve
the user’s required song information with similarity
score. The matching efficiencies of these algorithms
are compared by searching f-score and 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.
