Assistant Professor

Dr Abinash Pujahari

Department of Computer Science and Engineering

Interests

  1. Recommender Systems
  2. Information Retrieval
  3. Sentiment Analysis

Faculty Details

Education

2021

National Institute of Technology Raipur
Computer Science and Engineering
Ph.D.

2013

Sambalpur University
Computer Science
M.Tech.

2011

SOA University
Master’s in computer application

2008

Sambalpur University
Bachelor of Science

Experience

  • Aug 2021 – Feb 2022 – Assistant Professor – Bennett University, Greater Noida, India
  • Aug 2016 – Aug 2017 – Lecturer, Ravenshaw, University, Cuttack, Odisha
  • Aug 2013 – May 2014 – Assistant Professor, Sambalpur University Institute of Information Technology, Burla, Odisha

Research Interest

  • Personalized recommender systems, specifically focused on reducing sparsity and improving the ranking quality of recommender systems.
  • Modeling change in users’ behaviour over time in personalized recommender systems.

Awards & Fellowships

2019 – SIGCHI Gary Marsden Travel Award – ACM SIGCHI Gary Marsden- For attending RecSys Summer School 2019 at University of Gothenburg, Sweden.

Memberships

IEEE Member

ACM Professional Member

Publications

  • 1. Abinash Pujahari, and Dilip Singh Sisodia. "Item feature refinement using matrix factorization and boosted learning based user profile generation for content-based recommender systems." Expert Systems with Applications 206 (2022)
  • 2. Abinash Pujahari, and Dilip Singh Sisodia, “Handling Dynamic User Preferences using Integrated Point and Distribution Estimations in Collaborative Filtering,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, Early Access (Online) , SCI (IF:13.451)
  • 3. Abinash Pujahari, and Dilip Singh Sisodia. "Pair-wise preference relation based probabilistic matrix factorization for collaborative filtering in recommender system." Knowledge-Based Systems 196 (2020): 105798, SCI (IF: 8.038)
  • 4. Abinash Pujahari, and Dilip Singh Sisodia. "Aggregation of preference relations to enhance the ranking quality of collaborative filtering based group recommender system." Expert Systems with Applications 156 (2020): 113476. SCIE (IF: 6.954)
  • 5. Abinash Pujahari, and Dilip Singh Sisodia. "Modeling side information in preference relation based restricted boltzmann machine for recommender systems." Information Sciences 490 (2019): 126-145. SCI (IF: 6.795)
  • 6. Abinash Pujahari, and Dilip Singh Sisodia. "Preference relation based collaborative filtering with graph aggregation for group recommender system." Applied Intelligence 51.2 (2021): 658-672. SCI (IF: 5.086)
  • 7. Abinash Pujahari, and Dilip Singh Sisodia. "Clickbait detection using multiple categorisation techniques." Journal of Information Science 47.1 (2021): 118-128. SCIE (IF: 3.282)

Conferences

  • 1. Shrivastava, Rajesh, et al., "Efficient Question Answering in Chatbot Using TF-IDF and Cosine Similarity." Innovations in Information and Communication Technologies: Proceedings of ICIICT 2022. Singapore: Springer Nature Singapore, 2022. 25-31.
  • 2. Pujahari, A. and Padmanabhan, V., 2015, December. Group recommender systems: Combining user-user and item-item collaborative filtering techniques. In 2015 International Conference on Information Technology (ICIT) (pp. 148-152). IEEE.
  • 3. Pujahari, A. and Padmanabhan, V., 2014, December. An approach to content based recommender systems using decision list based classification with k-DNF rule set. In 2014 International Conference on Information Technology (pp. 260-263). IEEE.
  • 4. Pujahari, A. and Padmanabhan, V., 2015. A new grouping method based on social choice strategies for group recommender system. In Computational Intelligence in Data Mining-Volume 1 (pp. 325-332). Springer, New Delhi.
  • 5. Pujahari, A., Padmanabhan, V. and Patel, S., 2016. Nearest Neighbour with Priority Based Recommendation Approach to Group Recommender System. In Computational Intelligence in Data Mining—Volume 2 (pp. 347-354). Springer, New Delhi.
  • 6. Pujahari, Abinash, and Dilip Singh Sisodia. "Model-based collaborative filtering for recommender systems: An empirical survey." 2020 First International Conference on Power, Control and Computing Technologies (ICPC2T). IEEE, 2020.
  • 7. Sisodia, Dilip Singh, et al. "A comparative performance study of machine learning algorithms for sentiment analysis of movie viewers using open reviews." Performance Management of Integrated Systems and its Applications in Software Engineering. Springer, Singapore, 2020. 107-117.
  • 8. Sisodia, Dilip Singh, Somdutta Vishwakarma, and Abinash Pujahari., Evaluation of machine learning models for employee churn prediction." 2017 international conference on inventive computing and informatics (icici). IEEE, 2017.

Book Chapters

  • 1. Pujahari, Abinash, and Vineet Padmanabhan. "A new grouping method based on social choice strategies for group recommender system." Computational Intelligence in Data Mining-Volume 1: Proceedings of the International Conference on CIDM, 20-21 December 2014. Springer India, 2015.
  • 2. Pujahari, Abinash, Vineet Padmanabhan, and Soma Patel. "Nearest neighbour with priority based recommendation approach to group recommender system." Computational Intelligence in Data Mining—Volume 2: Proceedings of the International Conference on CIDM, 5-6 December 2015. Springer India, 2016.

Patents

  • 1. "Author: Kshira Sagar Sahoo, Tapas Kumar Mishra, Abinash Pujahari, Sambit Kumar Mishra; Title: A system and a method for controlling smart street lights, 2022"
  • 2. "Author: Tapas Kumar Mishra, Kshira Sagar Sahoo, Abinash Pujahari; Title: A SYSTEM AND A METHOD FOR NAVIGATING A VACUUM CLEANER, 2022"

Contact Details

  • E-mail id: abinash.p@srmap.edu.in
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