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A survey of collaborative filtering techniques
As one of the most successful approaches to building recommender systems, collaborative
filtering (CF) uses the known preferences of a group of users to make recommendations or …
filtering (CF) uses the known preferences of a group of users to make recommendations or …
Recommender systems, cultural heritage applications, and the way forward
G Pavlidis - Journal of Cultural Heritage, 2019 - Elsevier
Modern recommender systems appeared during the last decade of the 20th century and
have already proven their importance in tackling with information overload and content or …
have already proven their importance in tackling with information overload and content or …
A survey of collaborative filtering based social recommender systems
Recommendation plays an increasingly important role in our daily lives. Recommender
systems automatically suggest to a user items that might be of interest to her. Recent studies …
systems automatically suggest to a user items that might be of interest to her. Recent studies …
Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
This paper presents an overview of the field of recommender systems and describes the
current generation of recommendation methods that are usually classified into the following …
current generation of recommendation methods that are usually classified into the following …
Collaborative-prediction-based recursive filtering for nonlinear systems with sensor saturation under duty cycle scheduling
H Gao, Y Li, L Yu, H Yu - Systems Science & Control Engineering, 2023 - Taylor & Francis
In this paper, a recursive filtering problem is analyzed for nonlinear systems with sensor
saturation under duty cycle scheduling (DCS). The sensor saturation is taken into account to …
saturation under duty cycle scheduling (DCS). The sensor saturation is taken into account to …
A reliability-based recommendation method to improve trust-aware recommender systems
Recommender systems (RSs) are programs that apply knowledge discovery techniques to
make personalized recommendations for user's information on the web. In online sharing …
make personalized recommendations for user's information on the web. In online sharing …
Bayesian-inference-based recommendation in online social networks
In this paper, we propose a Bayesian-inference-based recommendation system for online
social networks. In our system, users share their content ratings with friends. The rating …
social networks. In our system, users share their content ratings with friends. The rating …
A new similarity function for selecting neighbors for each target item in collaborative filtering
K Choi, Y Suh - Knowledge-Based Systems, 2013 - Elsevier
As one of the collaborative filtering (CF) techniques, memory-based CF technique which
recommends items to users based on rating information of like-minded users (called …
recommends items to users based on rating information of like-minded users (called …