Publications

SCI Journals

  • Nithya B, Mala C, E. Sivasankar, “Channel status based sliding contention window (CS-SCW) algorithm a fuzzy control approach for medium access in wireless networks”, Soft Computing, Vol. 21(8), 1991–2004, Apr-2017.
  • Selvi, C., and E. Sivasankar, “A novel Adaptive Genetic Neural Network (AGNN) model for recommender systems using modified k-means clustering approach”, Multimedia Tools and Applications, Vol. 11, 14303-14330, Nov-2018.
  • Vijaya J, Sivasankar E, “Computing efficient features using rough set theory combined with ensemble classification techniques to improve the customer churn prediction in telecommunication sector”, Computing, 839-860, Aug-2018.
  • Selvi, C., and E. Sivasankar, “A novel similarity measure towards effective recommendation using Matusita coefficient for Collaborative Filtering in a sparse dataset”, Sādhanā, Vol. 43(12), 1-13, Dec-2018.
  • Selvi C, Sivasankar E, “A novel optimization algorithm for recommender system using modified fuzzy c-means clustering approach”, Soft Computing, 1901-1916, Mar-2019.
  • Vijaya J, Sivasankar E, “An efficient system for customer churn prediction through particle swarm optimization-based feature selection model with simulated annealing”, Cluster Computing, 10757-10768, Sep-2019.
  • Sivasankar E, Vijaya J, “Hybrid PPFCM-ANN model: an efficient system for customer churn prediction through probabilistic possibilistic fuzzy clustering and artificial neural network”, Neural Computing and Applications, 7181-7200, Nov-2019.
  • Sivasankar E, Selvi C, Mahalakshmi S, “Rough set-based feature selection for credit risk prediction using weight-adjusted boosting ensemble method”, Soft Computing, 3975-3988, Mar- 2020.
  • Krishnakumari, K., E. Sivasankar, and Sam Radhakrishnan, “Hyperparameter tuning in convolutional neural networks for domain adaptation in sentiment classification (HTCNN-DASC)”, Soft Computing, 24(5), 3511-3527, Mar-2020.
  • Sivasankar E, Krishnakumari K, Balasubramanian P, “An enhanced sentiment dictionary for domain adaptation with multi-domain dataset in Tamil language (ESD-DA)”, Soft Computing, 25(5), 3697-3711, Mar-2021.
  • Balasubramanian P, Sivasankar E, Vignesh Viswanathan, “CB-Fake: A multimodal deep learning framework for automatic fake news detection using capsule neural network and BERT”, Multimedia Tools and Applications, 1-34, Nov-2021.

Scopus Journals

  • E. Sivasankar, Rengan Sivagurunathan Rajesh, “Appendicitis diagnosis system using fuzzy logic-and neural network-based classifier”, International Journal of Medical Engineering and Informatics, 3(4), 337-350, Jan-2011.
  • Siva Brahmasani, E. Sivasankar, “Two level verification for detection of DNS rebinding attacks”, International Journal of System Assurance Engineering and Management, 4(2), Apr-2013.
  • Sivasankar, E., and J. Vijaya, “A study of feature selection techniques for predicting customer retention in telecommunication sector”, International Journal of Business Information Systems, 31(1), 1-26, May-2019.
  • Sivasankar, E., Pradeep, R., Sivanandham, S, “Identification of important biomarkers for detection of chronic kidney disease using feature selection and classification algorithms”, International Journal of Medical Engineering and Informatics, Vol. 11, 2019.
  • E. Sivasankar, A. Sathish Kumar, J. Sanjivi, P. Balasubramanian, “Analysis and prediction of breast cancer through feature selection and classification techniques”, International Journal of Medical Engineering and Informatics, 13(5), 359-375, Sep-2021.

International Conferences

  • Sivasankar, E., and R. S. Rajesh, “Knowledge discovery in medical datasets using a Fuzzy Logic rule based classifier”, IEEE Second International Conference on Electronic Computer Technology Conference, Kuala Lumpur, 208-213, 2010.
  • Sivasankar, E., and R. S. Rajesh, “Design and Development of a Clinical Decision Support System for diagnosing appendicitis Computing”, IEEE Communications and Applications Conference (ComComAp), Hong Kong, 316-321, 2012.
  • Nithya, B; Mala, C; Sivasankar, E, “A novel cross layer approach to enhance QoS performance in multihop adhoc networks”, IEEE Network-Based Information Systems (NBiS), 2014 17th International Conference, 229-236, 2014.
  • Srikrishnan, V; Sivasankar, E; Pitchiah, R, “A performance comparison of scheduling distributed mining in cloud”, Networks & Soft Computing (ICNSC) 2014 First International Conference, 375-379, 2014.
  • Sridevi, M; Mala, C; Sivasankar, E; You, Ilsun, “Optimized multilevel threshold selection using evolutionary computing”, IEEE Network-Based Information Systems (NBiS) 2014 17th International Conference on, 149-156, 2014.
  • Ramya, AV; Sivasankar, E, “Distributed pattern matching and document analysis in big data using Hadoop MapReduce model”, Parallel, Distributed and Grid Computing (PDGC) 2014 IEEE International Conference, 312-317, 2014.
  • Srikrishnan, V; Sivasankar, E; Pitchiah, R, “A log data analytics based scheduling in open source cloud software “, Parallel, Distributed and Grid Computing (PDGC) 2014 IEEE International Conference, 390-395, 2014.
  • Raja, P Vignesh; Sivasankar, E, “Modern framework for distributed healthcare data analytics based on Hadoop”, Information and Communication Technology-Eur Asia Conference, Springer, 348-355, 2014.
  • Selvi, C; Ahuja, Chakshu; Sivasankar, E, “A Comparative Study of Feature Selection and Machine Learning Methods for Sentiment Classification on Movie Data Set”, Intelligent Computing and Applications, Springer, 367-379, 2015.
  • Mahalakshmi, S; Sivasankar, E, “Cross domain sentiment analysis using different machine learning techniques”, Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO-2015), Springer, Cham, 77-87, 2015.
  • Raja, P Vignesh; Sivasankar, E; Pitchiah, R, “Framework for smart health: toward connected data from big data”, Intelligent Computing and Applications, Springer, New Delhi, 423-433, 2015.
  • Sivasankar, E; Vijaya, J, “Customer Segmentation by Various Clustering Approaches and Building an Effective Hybrid Learning System on Churn Prediction Dataset”, Computational Intelligence in Data Mining, Springer, 181-191, 2017.
  • Sivasankar, E; Selvi, C; Mala, C, “A Study of Dimensionality Reduction Techniques with Machine Learning Methods for Credit Risk Prediction”, Computational Intelligence in Data Mining, Springer, 65-76, 2017.
  • Vijaya, J., E. Sivasankar, and S. Gayathri, ”Fuzzy Clustering with Ensemble Classification Techniques to Improve the Customer Churn Prediction in Telecommunication Sector”, Recent Developments in Machine Learning and Data Analytics, 261-274, 2018.
  • Shriram S, Sivasankar E, “Anomaly detection on shuttle data using unsupervised learning techniques”, International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 221-225, 2019.
  • Singh, B. Emil Richard, and E. Sivasankar, “Enhancing Prediction Accuracy of Default of Credit Using Ensemble Techniques”, First International Conference on Artificial Intelligence and Cognitive Computing, 427-436, 2018.
  • Avinash, M., and E. Sivasankar. A study of feature extraction techniques for sentiment analysis In Emerging Technologies in Data Mining and Information Security, 475-486, 2018.
  • Selvi, C., and E. Sivasankar, “An efficient context-aware music recommendation based on emotion and time context”, In Data Science and Big Data Analytics, 215-228, 2018.
  • Krishnakumari K, Sivasankar E, “Scalable Aspect-Based Summarization in the Hadoop Environment”, Big Data Analytics, Springer, 439-449, 2018.
  • Ahuja C, Sivasankar E, ”Cross-Domain Sentiment Analysis Employing Different Feature Selection and Classification Techniques”, Information and Communication Technology for Sustainable Development, Springer, 167-179, 2018.
  • Vijaya, J; Sivasankar, E; “Improved Churn Prediction Based on Supervised and Unsupervised Hybrid Data Mining System”, Information and Communication Technology for Sustainable Development, Springer, 485-499, 2018.
  • Singh, B Emil Richard; Sivasankar, E; “Risk Analysis in Electronic Payments and Settlement System Using Dimensionality Reduction Techniques”, IEEE International Conference on Cloud Computing, Data Science & Engineering, 14-19, 2018.
  • Selvi, C; Sivasankar, E; “A Novel Singularity Based Improved Tanimoto Similarity Measure for Effective Recommendation Using Collaborative Filtering”, IEEE International Conference on Cloud Computing, Data Science & Engineering, 256-262, 2018.
  • Shriram S, Sivasankar E, “Anomaly detection on shuttle data using unsupervised learning techniques, IEEE International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 221-225, 2019.
  • Sathyamoorthy, Sruthi, and E. Sivasankar, “A Clustering-based Framework for Fast Training of Classifiers”, International Conference on Innovative Trends in Information Technology (ICITIIT), 1-6, 2020.
  • Ganesh, Venkataramana, Vignesh Viswanathan, Harshitha Sanjeev Kumar, and E. Sivasankar., “Financial Sentiment Analysis: A Study of Feature Engineering Methodologies”, In Soft Computing and Signal Processing, 225-240, 2021.
  • A. Sivarajan, E. Sivasankar, Bala Adithya, “Comparing the predictive accuracy of machine learning algorithms for neonatal mortality risk classification”, 3rd International Conference on Machine Intelligence and Signal Processing (MISP 2021), NIT Arunachal Pradesh, 2021.