Machine Learning Self-Organizing Map for Identifying Authorship in Tamil Articles Priya R. Lakshmi1,*, Evangil D. Flora2,**, Manimannan G3,*** 1Assistant Professor, Department of Statistics, Dr. Ambedkar Government Arts College, Vyasarpadi, Chennai (Tamilnadu) 2Assistant Professor, Department of Mathematics, ST. Josephs College (Arts & Science), Kovur, Chennai (Tamilnadu) 3Assistant Professor, Department of Mathematics, ST. Josephs College (Arts & Science), Kovur, Chennai (Tamilnadu) *E-mail: priyagayu2006@gmail.com
**floraevangil@gmail.com
***manimannang@gmail.com
Online Published on 12 December, 2023. Abstract This research paper examines the classification of articles written by three prominent Tamil scholars, Mahakavi Bharathiar (MB), SubramniyaIyer (SI), and T. V. Kalyanasundaranar (TVK), of the same period using machine learning algorithms of Self-Organizing Map (SOM). These authors have all published a number of articles on India's Freedom Movement in the magazine called India. In this study, SOM is used to explore the classification model and visualization of the present dataset structure. To classify the writing styles and stylistic features of the three authors, different sets of stylistic features were extracted and used with the help of function words. The results suggest that machine learning data mining tools are a useful tool for the analysis of large authorship databases. Finally, the writing styles and stylistic features of the three authors were distinctly classified and visualized using a bar chart for all parameters. Top Keywords Authorship, Stylistic features, Data Mining, Self-Organizing Map (SOM), Classification and visualization. Top |