P V RAMANA MURTHY

@mlritm.ac.in

Associate Professor, Data Science Department
Marri Laxman Reddy Institute of Technology and Management

P V RAMANA MURTHY


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https://researchid.co/ramanamurthy

EDUCATION

M.Tech. Computer Science 2005 78.25 First Class with Distinction JNTU, Hyderabad

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Computer Science, Computer Science, Computer Science
3

Scopus Publications

Scopus Publications

  • Natural Language Processing Based Machine Learning Framework for Sentiment Analysis of English Literary Reviews
    P.V. Ramana Murthy, Susmitha Madineni, Gera Vijaya Nirmala, N. Venkatesh, B. Siris Royal, S. Kanakaprabha
    Proceedings of the 4th International Conference on Intelligent Data Communication Technologies and Internet of Things Idciot 2026, 2026
    Natural Language Processing (NLP) is largely based on text classification as its major working process for automatic analysis in different domains. The discipline of text classification has opinion polarity analysis as its significant subset that examines the sentiment in written content. The study explores machine learning methods for examining the feelings of English writers' English literary reviews in Indian writers and determines the style of classification between positive, negative and neutral criticisms. The study used usual machine learning classifications Naive Bayes (NB), Support Vector Machine (SVM), Random Forest (RF) and sentimental analysis. The model performance is improved by applying TF-IDF and word encodings to extract features. The corpus consists of curated reviews collected from various online literary sites as well as book reviews and social media platforms. The test of the model determines its effectiveness using standards such as accuracy, accuracy, recall and F1-score. Among the evaluated models, SVM achieved the highest accuracy of 87.5 %, followed by NB with 86.9 %, while RF recorded the lowest accuracy of 84.2 %. These results promises to deliver the outstanding performance of SVM for sentiment classification of English literary reviews. The study advances automated literary analysis algorithms that identify reader emotions and offer suggestions. It also produce insights that examine how Indian authors are received internationally through sentiment analysis employing computational methods, the project combines literary analysis methodologies with machine learning.
  • Performance Comparison Analysis of Predicting the Heart Diseases using Machine Learning Algorithms
    Dhruva R. Rinku, Sandhya Devi Gogula, Swarnalatha Prathipati, P V Ramana Murthy, Rokesh Kumar Yarava, Uma Devi Kosuri
    2023 4th International Conference on Electronics and Sustainable Communication Systems Icesc 2023 Proceedings, 2023
    In the medical field, the process of Heart Disease (HD) prediction process is a challenging task even in the modern digital world. Even though the data generated by the healthcare industries are huge, the data scientists are working tremendously to determine the correlation between the various parameters that causes the HDs. Therefore, there exists a need to predict the HDs to safeguard the human kind. The proposed method uses the Machine Learning (ML) models to predict the HD based on the existing symptoms of the patients. The dataset from the UPI repository is used to evaluate the performance of the proposed models. The various parameters namely precision (p), recall (r), and accuracy (a) are used evaluate the performance measures of the ML models. Observing the results concluded that, the Random Forest model outperformed the other models such as XGBoost, Decision Tree and traditional Neural Network model regarding the prediction accuracy with respect to UCI dataset.
  • Recognition of online handwritten Telugu letters for different domains and organizations
    Journal of Critical Reviews, 2019

RECENT SCHOLAR PUBLICATIONS

  • Online social Network Trend Discovery Using Frequent Subgraph (FSgM) Mining
    SA Kumar, PVR Murthy, P Srinivas, PAH Kiran
    Solid State Technology 63 (6), 5934-5945 , 2020
    2020.0
  • Cloud Based Home Health Care Systems using IoT
    PVR Murthy, P Srinivas, YLM Latha

MOST CITED SCHOLAR PUBLICATIONS

  • Online social Network Trend Discovery Using Frequent Subgraph (FSgM) Mining
    SA Kumar, PVR Murthy, P Srinivas, PAH Kiran
    Solid State Technology 63 (6), 5934-5945 , 2020
    2020.0
  • Cloud Based Home Health Care Systems using IoT
    PVR Murthy, P Srinivas, YLM Latha