Year : 2021
A class imbalance-aware review rating prediction using hybrid sampling and ensemble learning
Cite this Research Publication : Dr. Anbazhagan M and Arock, M., “A class imbalance-aware review rating prediction using hybrid sampling and ensemble learning”, Multimedia Tools and Applications, vol. Vol. 80, 2021.
Publisher : Multimedia Tools and Applications
Year : 2020
Integrated topic modeling and sentiment analysis: a review rating prediction approach for recommender systems
Cite this Research Publication : Dr. Anbazhagan M and Arock, M., “Integrated topic modeling and sentiment analysis: a review rating prediction approach for recommender systems”, Turkish Journal of Electrical Engineering and Computer Sciences, vol. 28, pp. 107-123, 2020.
Publisher : Turkish Journal of Electrical Engineering and Computer Sciences
Year : 2019
Review rating prediction using combined latent topics and associated sentiments: an empirical review
Cite this Research Publication : Dr. Anbazhagan M and Arock, M., “Review rating prediction using combined latent topics and associated sentiments: an empirical review”, Service Oriented Computing and Applications volume, 2019.
Publisher : Service Oriented Computing and Applications
Year : 2016
Collaborative Filtering Algorithms for Recommender Systems
Cite this Research Publication : Dr. Anbazhagan M and Arock, M., “Collaborative Filtering Algorithms for Recommender Systems”, International Journal of Control Theory and Applications, vol. Vol. 9, No. 27 vol., pp. pp. 127-136, 2016.
Publisher : International Journal of Control Theory and Applications
Year : 2012
Sensor Grid Based Vision Status Monitoring in Eye Care System
Cite this Research Publication : Dr. Anbazhagan M, Anitha, M., and Mohamed, M. A. Maluk, “Sensor Grid Based Vision Status Monitoring in Eye Care System”, International Journal of Future Computer and Communication, vol. 1, 1 vol., 2012.
Publisher : International Journal of Future Computer and Communication
Year : 2011
An improved kangaroo transaction model using surrogate objects for distributed mobile system
Cite this Research Publication : R. S. and Dr. Anbazhagan M, “An improved kangaroo transaction model using surrogate objects for distributed mobile system”, National Level Conference on Emerging Trends in Computing and Network Technologies, 2011.
Publisher : National Level Conference on Emerging Trends in Computing and Network Technologies