Abstract
Recommendation systems have taken the turn of the new uses of the Internet, with the emergence of trust-based recommendation systems. These use trust relationships between users to predict ratings based on experiences and feedback. To obtain these ratings, many computational models have been developed to help users make decisions, and to improve interactions between different users within a system. Hence, choosing the appropriate model is challenging. To address this issue, we propose a two-step approach that, first, allows the user to define the requirements of his/her target system and, then, guides him/her to select the most appropriate computational model for his/her application according to the defined requirements.
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Sellami, C., Baron, M., Jean, S., Bechchi, M., Hadjali, A., Chabot, D. (2022). Trust Model Recommendation Driven by Application Requirements. In: Guizzardi, R., Ralyté, J., Franch, X. (eds) Research Challenges in Information Science. RCIS 2022. Lecture Notes in Business Information Processing, vol 446. Springer, Cham. https://doi.org/10.1007/978-3-031-05760-1_45
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