Seetha Hari

Dr Hari Seetha obtained her Master’s degree in Engineering Physics with specialization in electronics from National Institute of Technology (formerly R. E. C.)Warangal and obtained M.Phil as well as Ph.D from V.I.T University. She has research interests in the fields of pattern recognition, data mining, text mining and machine learning. She has published a few research papers in national and international journals and conferences. She is a member of editorial board for various International Journals. She is presently guiding 5 Ph.D students. She is listed in the 2014 edition of Who’s who in the world published by Marquis Who’s Who, as the biographical reference representing the world’s most accomplished individuals. She had been a co-investigator to a major research project sponsored by the Department of Science and Technology, Government of India. She is currently working as Associate Professor in the School of Computer Engineering at VIT University, Vellore, India. She is also a Division Chair for Software Systems division and Program Chair for B.Tech (CSE) program, in the School of Computer Engineering at VIT University, Vellore, India.

Publications

Crime Prediction Using Twitter Data
Crime Prediction Using Twitter Data
Lydia Jane G., Seetha Hari. © 2021. 13 pages.
As social media platforms are being increasingly used across the world, there are many prospects to using the data for prediction and analysis. In the Twitter platform, there are...
Analysis of Crime Data Using Neighbourhood Rough Sets
Analysis of Crime Data Using Neighbourhood Rough Sets
Lydia J Gnanasigamani, Seetha Hari. © 2020. 15 pages.
Crime analysis has been carried out to find out patterns and associations in crime incidents. A few of the different latitudes that research has been carried out are the...
Learning From Imbalanced Data
Learning From Imbalanced Data
Lincy Mathews, Seetha Hari. © 2019. 12 pages.
A very challenging issue in real-world data is that in many domains like medicine, finance, marketing, web, telecommunication, management, etc. the distribution of data among...
Learning From Imbalanced Data
Learning From Imbalanced Data
Lincy Mathews, Seetha Hari. © 2018. 10 pages.
A very challenging issue in real world data is that in many domains like medicine, finance, marketing, web, telecommunication, management etc., the distribution of data among...