Dr. Manju Venugopalan currently serves as Assistant Professor (Sr.Gr) at the Department of Computer Science & Engineering, Amrita School of Computing, Bengaluru. She has 11 years of teaching experience, with more than 10 years being at Amrita Vishwa Vidyapeetham, Bengaluru. She acquired her M.Tech in 2015 and Ph.D. in the year 2023 from Amrita Vishwa Vidyapeetham, Bengaluru. Her research interests include Natural Language Processing, Machine Learning, Big Data Analytics and Text Analytics. She is currently exploring the areas of multimodal sentiment analysis, transfer learning, Name Entity Recognition and NLP in medical domain.
Education
Year : 2022
Cite this Research Publication : Deepa Gupta, Manju Venugopalan, Peeta Basa Pati, “An Automated System for Identifying an Optimal Set for Text Labelling”, 202141044434, 28th Sep 2022.
Year : 2022
Cite this Research Publication : Manju Venugopalan, Gupta Deepa, A reinforced active learning approach for optimal sampling in aspect term extraction for sentiment analysis, Expert Systems with Applications,Volume 209,2022,118228,(IF: 8.665)
Publisher : Expert Systems with Applications
Year : 2022
Cite this Research Publication : Manju Venugopalan and Gupta Deepa, an enhanced guided LDA model augmented with BERT based semantic strength for aspect term extraction in sentiment analysis, Knowledge-Based Systems (2022)
Publisher : Knowledge-Based Systems
Year : 2021
Cite this Research Publication : Ojha, Chinmayee; Manju Venugopalan, Gupta, Deepa, (2021), “A Rule Based Approach For Aspect Extraction In Hindi Reviews”, Journal of intelligent and fuzzy-systems, 1-9, 2021, (IF: 1.851)
Publisher : Journal of intelligent and fuzzy-systems
Year : 2015
Cite this Research Publication : Manju Venugopalan and Dr. Deepa Gupta, “An Enhanced Polarity Lexicon by Learning-based Method Using Related Domain Knowledge”, International Journal of Information Processing and Management, vol. 6, no. 2, pp. 61–72, 2015.
Publisher : International Journal of Information Processing and Management
Year : 2021
Cite this Research Publication : Manju Venugopalan, Deepa Gupta , Vartika Bhatia , A supervised approach to aspect term extraction using minimal robust features for sentiment analysis. In Progress in Advanced Computing and Intelligent Engineering (pp. 237-251). Springer, Singapore.
Publisher : Springer
Year : 2020
Cite this Research Publication : Dwivedi, G., Venugopalan, M., & Gupta, D. (2019). A statistical-semantic PSO model for customer reviews-based question answering systems. In International Conference on Soft Computing and Signal Processing (pp. 137-151). Springer, Singapore
Publisher : Springer
Year : 2020
Cite this Research Publication : Aich, P., Venugopalan, M., & Gupta, D. (2020). Enhancing personalized response to product queries using product reviews incorporating semantic information. In Advances in Data and Information Sciences (pp. 497-509). Springer, Singapore.
Publisher : Springer
Year : 2020
Cite this Research Publication : Venugopalan, M., & Gupta, D. (2020). An unsupervised hierarchical rule based model for aspect term extraction augmented with pruning strategiesE. Procedia Computer Science, 171, 22-31.
Publisher : Elsevier
Year : 2019
Cite this Research Publication : Krishnan, D., Bharathy, P., & Venugopalan, M. (2019). A supervised approach for extractive text summarization using minimal robust features. In 2019 International Conference on Intelligent Computing and Control Systems (ICCS) (pp. 521-527). IEEE.
Publisher : IEEE
Year : 2018
Cite this Research Publication : Aich, P., Venugopalan, M., & Gupta, D. (2018). Content based spam detection in short text messages with emphasis on dealing with imbalanced datasets. In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA) (pp. 1-5). IEEE.
Publisher : IEEE
Year : 2018
Cite this Research Publication : Manju Venugopalan, G. Nalayini, G. Radhakrishnan & Deepa Gupta . (2018). Rating prediction model for reviews using a novel weighted textual feature method. In Recent findings in intelligent computing techniques (pp. 177-190). Springer, Singapore.
Publisher : Springer
Year : 2018
Cite this Research Publication : V. Kasi Viswanath, Madhuri, C. Gayathri V., Raviteja, C., S. Saravanan, and Venugopalan, M., “Hadoop and Natural Language Processing Based Analysis on Kisan Call Center (KCC) Data”, International Conference on Advances in Computing, Communications and Informatics (ICACCI). PES, Bengaluru, 2018.
Publisher : International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Year : 2017
Cite this Research Publication : Bhavi, M. M., Venugopalan, M., Gupta, D., Aggarwal, A., & Mishra, C. (2017). Family tree generation from electoral data to learn geographical distribution patterns. In 2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC) (pp. 178-183). IEEE.
Publisher : IEEE
Year : 2016
Cite this Research Publication : D. Mishra, Manju Venugopalan, and Dr. Deepa Gupta, “Context Specific Lexicon for Hindi Reviews”, in Procedia Computer Science, 2016, vol. 93, pp. 554 - 563.
Publisher : Procedia Computer Science.
Year : 2015
Cite this Research Publication : Manju Venugopalan and Dr. Deepa Gupta, “Sentiment Classification for Hindi Tweets in a Constrained Environment Augmented Using Tweet Specific Features”, in Mining Intelligence and Knowledge Exploration, 2015, pp. 664–670.
Publisher : Mining Intelligence and Knowledge Exploration, Springer International Publishing
Year : 2015
Cite this Research Publication : Manju Venugopalan and Dr. Deepa Gupta, “Exploring sentiment analysis on Twitter data”, in Eighth International Conference on Contemporary Computing (IC3), 2015.
Publisher : Eighth International Conference on Contemporary Computing (IC3)
