Published on: April 2026
CLOUD-ENABLED AI FRAMEWORK FOR COGNITIVE PATTERN-BASED DECISION SUPPORT
I. Thanuja S. Abhinav D. Sindhuja
ABUL KALAM
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Abstract
The framework provides nonclinical, reflective insights that help users improve self-awareness and make informed decisions related to careers, interests, and personal development. Deployed on a cloud platform, the system ensures scalability, accessibility, and continuous learning. By emphasizing behavior driven analysis over traditional assessments, the proposed approach supports meaningful decision alignment in a dynamic and evolving environment.
Keywords: Cognitive Decision Support, Behavioral Analytics, Scenario Based Interaction, Human Centered AI.
How to Cite this Paper
Thanuja, I., Abhinav, S. & Sindhuja, D. (2026). Cloud-Enabled AI Framework for Cognitive Pattern-Based Decision Support. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.216
Thanuja, I., et al.. "Cloud-Enabled AI Framework for Cognitive Pattern-Based Decision Support." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.216.
Thanuja, I.,S. Abhinav, and D. Sindhuja. "Cloud-Enabled AI Framework for Cognitive Pattern-Based Decision Support." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.216.
References
- Russell, S. J., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson Education.
- Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
- Mitchell, T. M. (1997). Machine Learning. McGraw-Hill.
- Picard, R. W. (1997). Affective Computing. MIT Press.
- LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.
- Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamification. Proceedings of the 15th International Academic Mind Trek Conference, 9–15.
- Kapp, K. M. (2012). The Gamification of Learning and Instruction. Pfeiffer.
- Adomavicius , G., & Tuzhilin , A. (2005). Recommended systems: A survey. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734–749.
- Han, J., Kamber, M., & Pei, J. (2011). Data Mining: Concepts and Techniques (3rd ed.). Morgan Kaufmann.
- Turban, E., Sharda, R., & Delen, D. (2011). Decision Support and Business Intelligence Systems. Pearson.
- Brusilovsky, P., & Millán, E. (2007). Adaptive systems and user models. The Adaptive Web, 3–53.
- Shneiderman, B., Plaisant, C., Cohen, M., Jacobs, S., & Elmqvist, N. (2016). Designing the User Interface (6th ed.). Pearson.
- Dix, A., Finlay, J., Abowd, G., & Beale, R. (2004). Human-Computer Interaction (3rd ed.). Pearson Education.
- Ng, A. Y. (2017). Machine learning and AI techniques. Stanford Lecture Notes.
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- •Published on: Apr 10 2026
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