Open Access
| Issue |
ITM Web Conf.
Volume 78, 2025
International Conference on Computer Science and Electronic Information Technology (CSEIT 2025)
|
|
|---|---|---|
| Article Number | 01027 | |
| Number of page(s) | 11 | |
| Section | Deep Learning and Reinforcement Learning – Theories and Applications | |
| DOI | https://doi.org/10.1051/itmconf/20257801027 | |
| Published online | 08 September 2025 | |
- Karthikeyan P., Tejasvini C.: 'Review of movie recommendation system'. Proc. 8th Int. Conf. Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2022, pp. 1538–1543 [Google Scholar]
- P. D S., S. A, P. M, C. S, L. S.K.: 'Personalized movie recommendations: A comprehensive review and analysis'. Proc. 10th Int. Conf. Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2024, pp. 2042–2045 [Google Scholar]
- Mambou E.N., Woungang I.: 'Bandit algorithms applied in online advertisement to evaluate click-through rates'. Proc. IEEE AFRICON, Nairobi, Kenya, 2023, pp. 1–5 [Google Scholar]
- Taj N., Varun M.H., Navya V.: 'Advanced content-based movie recommendation system'. Proc. 5th Int. Conf. Smart Electronics and Communication (ICOSEC), Trichy, India, 2024, pp. 1693–1698 [Google Scholar]
- Li H., Wang M., Zhang J., Shi T., Khamis A.: 'A contextual multi-armed bandit approach to personalized trip itinerary planning'. Proc. IEEE Int. Conf. Smart Mobility (SM), Niagara Falls, ON, Canada, 2024, pp. 55–60 [Google Scholar]
- Dixit K.K., Verma D., Muthuvel S.K., Laxminarayanamma K., Kumar M., Srivastava A.: 'Thompson sampling algorithm for personalized treatment recommendations in healthcare'. Proc. Int. Conf. Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), Raipur, India, 2023, pp. 1–6 [Google Scholar]
- Subhedar A., Bhutada P., Khanna A.A., Gupta R.K., Diddigi R.B.: 'Personalized diet recommendation system using bandits'. Proc. IEEE Int. Conf. Future Machine Learning and Data Science (FMLDS), Sydney, Australia, 2024, pp. 481–486 [Google Scholar]
- Manickam I., Lan A.S., Baraniuk R.G.: 'Contextual multi-armed bandit algorithms for personalized learning action selection'. Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA, 2017, pp. 6344–6348 [Google Scholar]
- S. G. S., et al.: 'Dynamic personalized ads recommendation system using contextual bandits'. Proc. Int. Conf. Intelligent Systems for Communication, IoT and Security (ICISCoIS), Coimbatore, India, 2023, pp. 339–344 [Google Scholar]
- 'MovieLens Beliefs Dataset 2024 | GroupLens', https://grouplens.org/datasets/movielens/ml_belief_2024/, accessed 25 April 2025 [Google Scholar]
- Gutowski N., Amghar T., Camp O., Chhel F.: 'Context enhancement for linear contextual multi-armed bandits'. Proc. IEEE 30th Int. Conf. Tools with Artificial Intelligence (ICTAI), Volos, Greece, 2018, pp. 1048–1055 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

