Abstract Proceedings of Seventh International Congress on Information and Communication Technology
In the Information Age, the ability to analyze data plays a crucial role. In this field, recommendation systems, which can provide users with suggestions by analyzing the information supplied to the system, are central. Furthermore, the use of contextual information makes recommendation systems more reliable.
This work is included in the proceedings of the Seventh International Congress on Information and Communication Technology, held in London in 2022. The article aims to describe a new approach for context-aware recommendation systems that leverages the properties of the CANDECOMP tensor decomposition to provide rating predictions. The proposed approach is tested on the DePaulMovie dataset to evaluate its accuracy, and the numerical results are promising.
      Read the article here: A Novel Context-Aware Recommendation Approach Based on Tensor Decomposition | SpringerLink Autori: F Colace, D Conte, B Gupta, D Santaniello, A Troiano