KeywordsĪlSallal M, Iqbal R, Palade V, Amin S, Chang V (2017) An integrated approach for intrinsic plagiarism detection. It is observed that the Naive Bayes (NB) classifier provides higher accuracy in comparison with the other methods as it shows 93.9, 85, and 86.7% of accuracy while considering the stop words for our three data sets, respectively. Six methods of machine learning were used for the author identification, and high accuracy had been achieved from these methods while applied to the data sets D2A, D4A, and D7A, which were built from Bengali song lyrics. It presents the first work on machine learning-based computational approach for author attribution from the lyrics of Bengali songs. This paper demonstrates a guideline to identify the author of a Bengali song from the lyrics of that song using machine learning. Authorship attribution is one of the ways of identifying the author from a linguistic corpus. As a result, author identification from songs, more specifically from lyrics, is an important and realistic possibility. Although songs are very popular among the enthusiasts, authors of them get little recognition. Bangladesh is no exception as it has a great history of music with a great tradition of song writings over centuries. Every country or region in the world has its own form and style of music. People listen to music both as a form of entertainment and means of relaxation.
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