Anita Ramalingam

@srmist.edu.in

Assistant Professor / Department of Computing Technologies / Faculty of Engineering and Technology
SRM Institute of Science and Technology

Anita Ramalingam


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https://researchid.co/anitaramalingam

EDUCATION

M.E., Ph.D

RESEARCH INTERESTS

Natural Language Processing
23

Scopus Publications

Scopus Publications

  • Predictive Maintenance Using ML and DL Techniques
    Utkarsh Saboo, R. Anita
    Advances in Science Technology and Innovation, 2026
  • To the Point: Text Summarization on English and Indic Languages Using NLP and Multilingual API
    Dorjee W. Namgyal, Abhinandan Singh, R. Anita
    Smart Innovation Systems and Technologies, 2026
  • Fine-Tuning Multilingual BERT for Melancholic Emotion Detection in Kuruntokai
    Anita Ramalingam, Briskilal Joseph, Subalalitha Chinnaudayar Navaneethakrishnan, Hasmath Farhana Thariq Ahmed, Suresh Merugu
    Journal of Intelligent and Fuzzy Systems, 2026
    Tamil is one of the world's oldest classical languages still in use. The Tamil language boasts a rich and extensive literary tradition, dating back over 2,000 years. Tamil literature addresses various aspects of life, such as love, war, social values and religion. Tamil classical literature encodes human emotions through dense metaphor, symbolism, and cultural convention, posing significant challenges for automatic emotion analysis. This research investigates the classification of melancholic emotions in Kuruntokai , a Sangam-era Tamil poetic anthology, focusing on two dominant affective categories: Lamentation and Consolation . A manually annotated dataset of 401 poems, along with their explanatory prose ( urai ), is used to evaluate classical machine learning models, recurrent neural networks, and a fine-tuned multilingual BERT (mBERT) model. To address the linguistic complexity of classical Tamil, the framework incorporates morphological analysis, a word reformation algorithm tailored to poetic constructs, and subword-level tokenization. Experimental results show that while Support Vector Machines perform best among classical classifiers, the fine-tuned mBERT model achieves superior performance, attaining an accuracy of 78% on urai-based classification. Quantitative analysis, supported by statistical significance tests and confidence intervals, demonstrates that explanatory prose provides richer emotional cues than the original poems. Qualitative error analysis further reveals how metaphorical compression in poetry leads to misclassification, which is resolved through urai. The findings highlight the effectiveness of transformer-based models for emotion classification in classical Tamil literature and underscore the importance of explanatory prose for reliable affective modelling.
  • Empowering Sustainable Water Management: Blockchain Innovations for Achieving the SDGs
    M.K. VIDHYALAKSHMI, R. ANITHA, Aswathy K. CHERIAN, B. YAMINI, N. NITHIYANANDAM, Sundaravadivazhagn BALASUBARAMANIAN
    Blockchain and the Water Supply Chain Opportunities Challenges and Innovations, 2025
    Control of water supply combined with enduring water resource management stands as Sustainable Development Goal 6 of the United Nations with its 2030 objective. IoT monitoring solutions integrate water infrastructure to track precise data about water quality and availability and usage patterns, which helps organizations optimize their management strategies and designate intervention measures. The promise of blockchain technology allows for greater accuracy in water monitoring. By using a decentralized and transparent ledger, water quality data can be recorded without fears of manipulation. Blockchain technology enables decentralized water management that resolves current water industry problems along with pricing mechanisms and water supply fraud prevention. Crowdsourcing and DeFi technologies are changing the funds for projects in water with an inclusive, transparent and accessible financing solution. Adoption of the blockchain technology for water management can be accelerated through public-private partnerships wherein oversight from the government is combined with innovative private sector solutions.
  • Enhancing Hindi Question Answering in RAG Systems via Fine-Tuned Retrieval and Generation Models
    Anita R, Himanshu Nainwal, Koshti Vanshika Shaileshbhai, Gruhit Kaneriya
    Proceedings of 3rd International Conference on Sustainable Computing and Data Communication Systems Icscds 2025, 2025
    Retrieval-Augmented Generation (RAG) systems enhance natural language understanding by retrieving relevant context before generating responses. However, due to poor embedding representations and generation errors, existing models struggle with handling Hindi questions. This work presents a fine-tuned Hindi RAG system using paraphrase- multilingual-mpnet-base-v2 as the retriever and facebook/mbart- large-50 as the generator. The retriever was trained with Multiple Negatives Ranking Loss to improve query-context alignment, while the generator was fine-tuned for concise, high- quality responses. Our model achieved an average retrieval similarity of 0.8700, ensuring effective query-context alignment, a BLEU score of 0.6833, reflecting high response quality, and a semantic similarity of 0.9200, demonstrating strong meaning retention. As expected, the exact match rate was 0, as the model generates fluent yet non-identical responses. These results confirm the system’s effectiveness in improving retrieval accuracy and response fluency for Hindi QA applications.
  • Rider Helmet Detection Using YOLOv5 Image Targeting Algorithm
    Bhavishya Sharma, Nachiketa Barve, Anita Ramalingam
    Aip Conference Proceedings, 2024
  • Hiding Data in Images Using Deep Neural Networks
    Ajay Samuel Victor, Tanushka Roy, Anita Ramalingam
    Aip Conference Proceedings, 2024
  • Estimation of NPK requirements using Random Forest
    Tilak Bhansali, Sagar Bhardwaj, Anita Ramalingam
    Aip Conference Proceedings, 2024
  • Multi Organ Tumor Detection Using Deep Learning
    Shaurya Sachdev, Atharva Karangale, Anita Ramalingam
    Aip Conference Proceedings, 2024
  • Revolutionizing Resume Screening: BERT and BiLSTM for Contextual Candidate Profiling
    M.K.Vidhyalakshmi, Anita Ramalingam, Poovammal. E
    1st International Conference on Communication Computing Smart Materials and Devices Icccsmd 2024, 2024
    In today’s competitive labor market, companies must quickly identify top candidates to increase productivity and competitiveness. For the most part, traditional screening methods are based on manual assessments, which are slow and biased. The main goal of this study was to develop an intelligent system known as BERT- BiLSTM for Resume Screening (BBRS), integrating Bidirectional Encoder Representations from Transformers (BERT) for feature extraction with Bidirectional Long Short-Term Memory (BiLSTM) for model transfer learning. Utilizing BERT, this method effectively captures contextual information from resumes, thereby providing rich semantic feature representations. BiLSTM further processes these features with dual-directional capability to enhance contextual understanding and improve classification accuracy. The BBRS framework addressed key challenges in automated resume screening and achieved a high accuracy of 94%, precision of 92%, recall of 94%, and F1 score of 92.5%.
  • Innovations in Real-Time Speech Translation: Leveraging Griffin-Lim Algorithm
    Himanshu Maithani, Aditya Giri Goswami, R Anita, J D Dorathi Jayaseeli, Sourabh Tiwari, Rashmi T Shankarappa
    2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024
  • Contextual Analysis of Tamil Proverbs for Automatic Meaning Extraction
    Anita Ramalingam, Subalalitha Chinnaudayar Navaneethakrishnan
    Communications in Computer and Information Science, 2023
  • A Novel classification framework for the Thirukkural for building an efficient search system
    Anita Ramalingam, Subalalitha Chinnaudayar Navaneethakrishnan
    Journal of Intelligent and Fuzzy Systems, 2022
  • An Analysis on Semantic Interpretation of Tamil Literary Texts
    Anita Ramalingam, Subalalitha Chinnaudayar Navaneethakrishnan
    Journal of Mobile Multimedia, 2022
  • Neural Machine Translation Using Attention Mechanism
    Sai Yashwanth Velpuri, Sonakshi Karanwal, R. Anita
    Lecture Notes in Networks and Systems, 2022
  • A Discourse-Based Information Retrieval for Tamil Literary Texts
    Anita Ramalingam, Subalalitha Chinnaudayar Navaneethakrish
    Journal of Information and Communication Technology, 2021
  • Emotionally intelligent chatbot for mental healthcare and suicide prevention
    International Journal of Advanced Science and Technology, 2020
  • Housing property recommendation with automated requirement prediction
    International Journal of Advanced Science and Technology, 2020
  • Open world chatbot using neural networks in green cloud environment
    Journal of Green Engineering, 2020
  • Sentiment analysis of movie using artificial neural network
    Devansh Nema, Devansh Bhudolia, O, G Virginia, A, et al.
    International Journal of Innovative Technology and Exploring Engineering, 2019
  • An Approach to Cluster Tamil Literatures Using Discourse Connectives
    R. Anita, C.N. Subalalitha
    2019 IEEE 1st International Conference on Energy Systems and Information Processing Icesip 2019, 2019
  • Semantic search using Latent Semantic Indexing and Word Net
    Arpn Journal of Engineering and Applied Sciences, 2017
  • An approach to page ranking based on discourse structures
    Subalalitha Chinnaudayar Navaneethakrishnan, , Anita Ramalingam, and
    Journal of Communications Software and Systems, 2016