Affiliations: Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, India
Correspondence:
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Corresponding author. Anita Ramalingam, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur – 603 203, India. [email protected].
Abstract: Thirukkural, a Tamil classic literature, which was written in 300 BCE is a didactic literature. Though Thirukkural comprises 1330 couplets which are organized into three sections and 133 chapters, in order to retrieve meaningful Thirukkural for a given query in search systems, a better organization of the Thirukkural is needed. This paper lays such a foundation by classifying the Thirukkural into ten new categories called superclasses that is helpful for building a better Information Retrieval (IR) system. The classifier is trained using Multinomial Naïve Bayes algorithm. Each superclass is further classified into two subcategories based on the didactic information. The proposed classification framework is evaluated using precision, recall and F-score metrics and achieved an overall F-score of 82.33% and a comparison analysis has been done with the Support Vector Machine, Logistic Regression and Random Forest algorithms. An IR system is built on top of the proposed system and the performance comparison has been done with the Google search and a locally built keyword search. The proposed classification framework has achieved a mean average precision score of 89%, whereas the Google search and keyword search have yielded 59% and 68% respectively.
Keywords: Natural language processing, text classification, information retrieval, multinomial naive bayes classifier, the Thirukkural
, morphological analysis
