Kumar RG

Dr. R.G.Kumar has 10+ years of Academic experience and handles courses for CSE (B.Tech & M.Tech), and MCA, he has 6+ years of research experience.
He has done his B.E. in CSE from Veltech Engineering College affiliated with Anna University and M.Tech in Software Engineering from B.S.Abdur Rahman University where he stood second top and received the university Silver Medal for his PG course. He has done his Doctorate at Bharathiar University, Coimbatore in 2021. He has guided 15+ UG projects in his experience and 2 PG projects. Kumar acts as a SpoC for APSSDC, Virtusa, Indo-Euro Synchronization and Coordinator for ICT Academy, and College Nodal Officer for APSCHE. His area of interest is Sentiment Analysis and Data
Mining-related works. He also established Research Projects in the Department of CSE and also organized International, National Conference,
FDP, seminar, Workshop, and symposium.

EDUCATION

 DOCTOR OF PHILOSOPHY: Pursuing Ph.D in Machine Learning/Natural Language Processing - Sentiment Analysis from Bharathiar University, Coimbatore, in Nov 2021.
 POST GRADUATION: M.Tech in Software Engineering from B.S.Abdur Rahman University, Chennai with 9.05 as the CGPA in the year 2012.
 UNDER GRADUATION: B.E in Computer Science and Engineering from Veltech Multitech Dr. RR & Dr. SR Engineering College affiliated with Anna University, Chennai with 72.07% aggregate in the year 2010.
 INTERMEDIATE: Taking Maths, Physics and Chemistry as a major, from Sri Sai Jyothi Junior College, Puttur and affiliated to Board of Intermediate Education, Andhra Pradesh with 78.50% aggregate in the year 2004.
 SSC: X from Little Flower (EM) High School, Board of Secondary Education, Andhra Pradesh with 72.20% in the year 2002.

RESEARCH INTERESTS

Sentiment Analysis, Natural Language Processing, Information Retrieval, Data Mining, Mobile Computing

Scopus Publications

Genre Classification of Telugu and English Movie Based on the Hierarchical Attention Neural Network
Kumar Govindaswamy, Shriram Ragunathan, and
International Journal of Intelligent Engineering and Systems, 2021
Genre Classification of movies is useful in the movie recommendation system for video streaming applications like Amazon, Netflix, etc. The existing methods used either video or audio data as input that requires more computation resources to process the data for the genre classification of movies. In this study, the Hierarchical Attention Neural Network (HANN) is proposed for genre classification of movies based on the social media called Twitter data as input. Twitter data related to the Telugu and English movies are collected and applied to HANN for movie’s genre classification. IMDB data are used to evaluate the performance of the proposed HANN method. The hierarchical structures of the twitter data is considered by the proposed HANN method and the most important words related to genre classification is identified by the attention mechanism, where the other neural networks such as Artificial Neural Network and Convolutional Neural Network (CNN) returns only the important weights resulting from previous words. The HANN method has the advantages of encoding the relevant information that helps to improve the performance of the recommendation system. The experimental results show that the HANN method achieve higher performance compared to other classifiers Long Short-Term Memory (LSTM) and Bidirectional LSTM (Bi-LSTM). The HANN method achieves accuracy of 73.15% in classification, while the existing BiLSTM method achieve the accuracy of 68% in classification.
The statistical analysis and E-risks of major E-commerce systems in India
International Journal of Advanced Science and Technology, 2019