A literature review and classification of recommender systems research
DH Park, HK Kim, IY Choi, JK Kim - Expert systems with applications, 2012 - Elsevier
Recommender systems have become an important research field since the emergence of
the first paper on collaborative filtering in the mid-1990s. Although academic research on …
the first paper on collaborative filtering in the mid-1990s. Although academic research on …
Recommender systems for online and mobile social networks: A survey
MG Campana, F Delmastro - Online Social Networks and Media, 2017 - Elsevier
Recommender Systems (RS) currently represent a fundamental tool in online services,
especially with the advent of Online Social Networks (OSN). In this case, users generate …
especially with the advent of Online Social Networks (OSN). In this case, users generate …
A hybrid online-product recommendation system: Combining implicit rating-based collaborative filtering and sequential pattern analysis
K Choi, D Yoo, G Kim, Y Suh - electronic commerce research and …, 2012 - Elsevier
Many online shopping malls in which explicit rating information is not available still have
difficulty in providing recommendation services using collaborative filtering (CF) techniques …
difficulty in providing recommendation services using collaborative filtering (CF) techniques …
Use of social network information to enhance collaborative filtering performance
When people make decisions, they usually rely on recommendations from friends and
acquaintances. Although collaborative filtering (CF), the most popular recommendation …
acquaintances. Although collaborative filtering (CF), the most popular recommendation …
A reliability-based recommendation method to improve trust-aware recommender systems
P Moradi, S Ahmadian - Expert Systems with Applications, 2015 - Elsevier
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 …
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 …
Distvae: distributed variational autoencoder for sequential recommendation
L Li, J Xiahou, F Lin, S Su - Knowledge-Based Systems, 2023 - Elsevier
Recommender systems (RS) play a vital role in daily life due to their practical significance.
As a branch of RS, the sequential recommendation has attracted much attention because of …
As a branch of RS, the sequential recommendation has attracted much attention because of …
Pepper: Empowering user-centric recommender systems over gossip learning
Recommender systems are proving to be an invaluable tool for extracting user-relevant
content helping users in their daily activities (eg, finding relevant places to visit, content to …
content helping users in their daily activities (eg, finding relevant places to visit, content to …
The recommender canvas: A model for developing and documenting recommender system design
The task of designing a recommender system is a complex process. Because of the many
technological advancements that may be included in a recommender system, engineers are …
technological advancements that may be included in a recommender system, engineers are …
Building and evaluating a location-based service recommendation system with a preference adjustment mechanism
MH Kuo, LC Chen, CW Liang - Expert Systems with Applications, 2009 - Elsevier
The location-based service (LBS) of mobile communication and the personalization of
information recommendation are two important trends in the development of electric …
information recommendation are two important trends in the development of electric …