Text stemming: Approaches, applications, and challenges J Singh, V Gupta ACM Computing Surveys (CSUR) 49 (3), 1-46, 2016 | 124 | 2016 |
A systematic review of text stemming techniques J Singh, V Gupta Artificial Intelligence Review 48, 157-217, 2017 | 103 | 2017 |
Analytical review of clustering techniques and proximity measures M Vivek, S Bawa, J Singh Artificial Intelligence Review, 2020 | 42 | 2020 |
A novel unsupervised corpus-based stemming technique using lexicon and corpus statistics J Singh, V Gupta Knowledge-Based Systems 180, 147-162, 2019 | 36 | 2019 |
WEClustering: word embeddings based text clustering technique for large datasets V Mehta, S Bawa, J Singh Complex & intelligent systems 7 (6), 3211-3224, 2021 | 24 | 2021 |
An Efficient Corpus-Based Stemmer J Singh, V Gupta Cognitive Computation 9 (5), 671-688, 2017 | 17 | 2017 |
An ensemble approach for extractive text summarization P Singh, P Chhikara, J Singh 2020 International Conference on Emerging Trends in Information Technology …, 2020 | 13 | 2020 |
Stamantic clustering: combining statistical and semantic features for clustering of large text datasets V Mehta, S Bawa, J Singh Expert Systems with Applications 174, 114710, 2021 | 11 | 2021 |
Enhancing Indian sign language recognition through data augmentation and visual transformer V Singla, S Bawa, J Singh Neural Computing and Applications, 1-14, 2024 | 2 | 2024 |
Improving accuracy using ML/DL in vision based techniques of ISLR V Singla, S Bawa, J Singh Multimedia Tools and Applications 83 (7), 20677-20698, 2024 | 1 | 2024 |
Comparative Analysis of Effect of Corpus-Based Stemmers in Sentiment Analysis F Alotaibi, V Gupta, J Singh INTERNATIONAL JOURNAL OF RESEARCH IN ELECTRONICS AND COMPUTER ENGINEERING 6 …, 2018 | | 2018 |