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Recent developments in recommender systems: A survey
In this technical survey, the latest advancements in the field of recommender systems are
comprehensively summarized. The objective of this study is to provide an overview of the …
comprehensively summarized. The objective of this study is to provide an overview of the …
Federated learning-based personalized recommendation systems: An overview on security and privacy challenges
The recent advancement in next-generation Consumer Electronics (CE) has created the
problems of information overload and information loss. The significance of Personalized …
problems of information overload and information loss. The significance of Personalized …
[HTML][HTML] How do context-aware artificial intelligence algorithms used in fitness recommender systems? A literature review and research agenda
Recommender Systems (RS) help the user in the decision-making process when there is a
problem of plenty or lack of information. The context-aware recommender systems (CARS) …
problem of plenty or lack of information. The context-aware recommender systems (CARS) …
Beyond AI-powered context-aware services: the role of human–AI collaboration
Purpose Artificial intelligence (AI) has gained significant momentum in recent years. Among
AI-infused systems, one prominent application is context-aware systems. Although the fusion …
AI-infused systems, one prominent application is context-aware systems. Although the fusion …
[HTML][HTML] Context-aware recommender systems in the music domain: A systematic literature review
The design of recommendation algorithms aware of the user's context has been the subject
of great interest in the scientific community, especially in the music domain where contextual …
of great interest in the scientific community, especially in the music domain where contextual …
Differentially private recommender system with variational autoencoders
To provide precise recommendations, traditional recommender systems (RS) collect
personal data, user preference and feedback, which are sensitive to each user if such …
personal data, user preference and feedback, which are sensitive to each user if such …
Eliciting auxiliary information for cold start user recommendation: A survey
Recommender systems suggest items of interest to users based on their preferences. These
preferences are typically generated from user ratings of the items. If there are no ratings for a …
preferences are typically generated from user ratings of the items. If there are no ratings for a …
Towards convergence of AI and IoT for smart policing: A case of a mobile edge computing-based context-aware system
With the fast growth of IoT and AI techniques, AIoT's potential in creating and capturing
business value is being increasingly acknowledged. AIoT is the practice of combining AI …
business value is being increasingly acknowledged. AIoT is the practice of combining AI …
Heterogeneous and clustering-enhanced personalized preference transfer for cross-domain recommendation
As a promising solution to alleviate the critical cold-start problem in recommendation
systems, Cross-Domain Recommendation (CDR) aims to transfer users' preferences from …
systems, Cross-Domain Recommendation (CDR) aims to transfer users' preferences from …
Personalized knowledge distillation for recommender system
Abstract Nowadays, Knowledge Distillation (KD) has been widely studied for recommender
system. KD is a model-independent strategy that generates a small but powerful student …
system. KD is a model-independent strategy that generates a small but powerful student …