Dr.Shini George

Dr. Shini George
Assossiate  Professor

[email protected]

PhD in Computer Science (Data Mining) from Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore

Experience

18  years of Industrial experience.

Publications

  1. Implicit aspect based sentiment analysis for restaurant review using LDA topic modelling and ensemble approach (May 2023), International Journal of Advanced Technology and Engineering Exploration, Vol.10 Issue:102, 553-567, http://dx.doi.org/10.19101/IJATEE.2022.10100099, (UGC CARE-Group II- Scopus).
  2. A REVIEW ON TECHNIQUES FOR FEATURE EXTRACTION IN OPINION MINING,         (December 2022), Journal of Pharmaceutical Negative Results, Volume 13 ¦ Special Issue 9, 9356-9361
  3. Automated Summarization of Restaurant Reviews using Hybrid Approaches (July 2022), ICTACT Journal on soft computing, Vol.12  Issue: 04, 2690 – 2696, DOI: 10.21917/ijsc.2022.0374.                    (UGC CARE- Group I ).
  4. Performance Evaluation of Sentiment Analysis on Balanced and Imbalanced Dataset Using Ensemble Approach,(May 2022) , Indian Journal of Science and Technology, Vol: 15 Issue: 17, 790-797, DOI: 10.17485/IJST/v15i17.2339. (Web of Science)
  5. Aspect-based Sentiment Analysis of Restaurant Reviews using Ensemble Algorithms,(July 2021 ), Turkish Online Journal of Qualitative Inquiry (TOJQI) Vol12, Issue 7, 6698 – 6705.
  6. Comparison of LDA and NMF topic modelling Techniques for Restaurant Reviews,(Oct 2020), Indian Journal of Natural Sciences, Vol.10, Issue 62, 210-219. (Web of Science)

Conferences

  1. Feature Extraction Techniques for Opinion Mining- A Review, International Web Conference on Smart Engineering Technologies, IWCSET, June 2020, ISBN: 978-93-5407-648-0.
2.       Feature-Based Opinion Mining using Machine learning Algorithms, International Conference on Applications of AI and Machine Learning, ICAML, May 2020,            ISBN: 978-81-941048-7-3.

Cross-Domain Sentiment Analysis Techniques-A Brief Survey, International Conference on Breakthrough in Engineering, Science & Technology, April 2019, ISBN: 978-81-940569-0-4.