1. “Future Generation of Recommender systems”, in Research Journal of Computer and Information Technology Sciences ISSN 2320 – 6527 Vol. 5(4), 9-12, June (2017)
2. “A study on text auto completion for easing search of information”, in Research Journal of Computer and Information Technology Sciences ,ISSN 2320 – 6527,Vol. 5(5), 12-14, July (2017)
3. “An Efficient Algorithm for Frequent Pattern Mining using Web Analysis Approach”, (IJCSET) ISSN:2231-0711 July 2012 Vol.2 Issue7,Page 1327-1332
4. “Extraction of Pattern Sequence and Geographical Location of User using Web Analysis Approach an Application of Web Usage Mining”, (IJCSET) ISSN:2231-0711 Feb. 2012 Vol. 2 Issue2, Page 2,877-879
5. "Suspicious URL detection using dynamic learning model with machine learning" with Sanjana Tiwari and Ashok Behra in International journal of reseach in applied science & engg. Technology July 2019 Vol 7 Issue 7 Page 1315
6. "Suspicious URL detection with machine learning" with Sanjana Tiwari and Ashok Behra in International Journal for research trends & innovation 2019 Vol 4 Issue 12 Page 20
7. "An analytical insight to hybrid recommender system" with Dr. Arpana Rawal in International Journal of advanced in management technology & Engg. Sciences march 2018 vol 8 issue 3 page 331
8. Verma, M., & Rawal, A. (2021). Feasibility Study of Hybridization Schemes in Recommender Systems. Design Engineering, 483-498.
9. An Approach towards a Bilingual Keyboard Application. Recent Trends in Computer Graphics and Multimedia Technology, Volume 4 Issue, DOI: https://doi.org/10.5281/zenodo.6634977 

International Conference:

1. “An Enhanced Item-based Collaborative Filtering Approach for Book Recommender System Design” , ECS Transactions. Apr(2022)

Scopus Indexed:

1. Smart Health Monitoring System Using Internet of Things in India. Journal of Information Technology and Sciences, Volume-8, Issue-2
2. Detecting Different Thoracic Disease Using CNN-Model. IEEE Explore 2022

SCI Indexed: 

1. Verma, M. and Patnaik, P. K. (2024) ‘An automatic college library book recommendation system using optimized Hidden Markov based weighted fuzzy ranking model’, Engineering Applications of Artificial Intelligence, 130, p. 107664. doi: https://doi.org/10.1016/j.engappai.2023.107664.