Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 47, Pages: 1-4
Pandian*, V. V. Ramalingam and R. P. Vishnu Preet
Department of Computer Science and Engineering, SRM University, Kattankulathur, Chennai - 603203, Tamil Nadu, India; [email protected]
Objective: To classify the authors of unknown Tamil dataset based on the work of known authors. Methods/Analysis: Text processing is the method of deriving high quality information from text that includes statistical patterns from the text. This paper proposes text processing method to extract features and perform classification on the same. Findings: The accuracy of the classifier turns out to be 94.1%. Classifier accuracy is improved from 88.23% to 94.1% by varying the classification algorithm (Bayes Net). Novelty/Improvement: This method can be further extended to all regional languages. By doing this, authors of various other poems in Tamil language can be identified which will be helpful to the society.
Keywords: Authorship, Classification, Feature Selection, Tamil Articles
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