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New Perspectives on Recommender Systems for Industries

Conference Paper
Publication Date:
2022
abstract:
Nowadays, recommender systems are increasingly being exploited in many industrial applications, including virtual museums and movie streaming platforms. In the last few years, some new perspectives provided by research paradigms such as deep learning or quantum computing, have arisen. As a result, this paper identifies four new perspectives on recommender systems: e-health, tourism, deep-learning-based, and recommender systems exploiting quantum computing. After discussing them, the paper provides the current state of the art and highlights the possible future directions for industries.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Recommender Systems; E-Health; Tourism; Deep Learning; Quantum Computing
List of contributors:
Pilato, Giovanni
Authors of the University:
PILATO GIOVANNI
Handle:
https://iris.cnr.it/handle/20.500.14243/463418
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