Related references
Note: Only part of the references are listed.Bayesian Additive Matrix Approximation for Social Recommendation
Huafeng Liu et al.
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA (2022)
A socially motivating and environmentally friendly tour recommendation framework for tourist groups
Mehdi Kargar et al.
EXPERT SYSTEMS WITH APPLICATIONS (2021)
HeteroGraphRec: A heterogeneous graph-based neural networks for social recommendations
Amirreza Salamat et al.
KNOWLEDGE-BASED SYSTEMS (2021)
Cross-platform dynamic goods recommendation system based on reinforcement learning and social networks
Gang Ke et al.
APPLIED SOFT COMPUTING (2021)
A social investing approach for portfolio recommendation
Yung-Ming Li et al.
INFORMATION & MANAGEMENT (2021)
Improving User Attribute Classification with Text and Social Network Attention
Yumeng Li et al.
COGNITIVE COMPUTATION (2019)
A new confidence-based recommendation approach: Combining trust and certainty
Faezeh Sadat Gohari et al.
INFORMATION SCIENCES (2018)
Algorithmic Glass Ceiling in Social Networks
Ana-Andreea Stoica et al.
WEB CONFERENCE 2018: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW2018) (2018)
Preference dynamics with multimodal user-item interactions in social media recommendation
D. Rafailidis et al.
EXPERT SYSTEMS WITH APPLICATIONS (2017)
A trust-aware recommendation method based on Pareto dominance and confidence concepts
Mohammad Mandi Azadjalal et al.
KNOWLEDGE-BASED SYSTEMS (2017)
Factored similarity models with social trust for top-N item recommendation
Guibing Guo et al.
KNOWLEDGE-BASED SYSTEMS (2017)
Context-aware probabilistic matrix factorization modeling for point-of-interest recommendation
Xingyi Ren et al.
NEUROCOMPUTING (2017)
FCT: a fully-distributed context-aware trust model for location based service recommendation
Zhiquan Liu et al.
SCIENCE CHINA-INFORMATION SCIENCES (2017)
On Deep Learning for Trust-Aware Recommendations in Social Networks
Shuiguang Deng et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2017)
Additive Co-Clustering with Social Influence for Recommendation
Xixi Du et al.
PROCEEDINGS OF THE ELEVENTH ACM CONFERENCE ON RECOMMENDER SYSTEMS (RECSYS'17) (2017)
Improving the Trustworthiness of Recommendations in Collaborative Filtering under the Belief Function Framework
Raoua Abdelkhalek
PROCEEDINGS OF THE ELEVENTH ACM CONFERENCE ON RECOMMENDER SYSTEMS (RECSYS'17) (2017)
Improving top-K recommendation with truster and trustee relationship in user trust network
Chanyoung Park et al.
INFORMATION SCIENCES (2016)
A non negative matrix factorization for collaborative filtering recommender systems based on a Bayesian probabilistic model
Antonio Hernando et al.
KNOWLEDGE-BASED SYSTEMS (2016)
MATRIX FACTORIZATION TECHNIQUES FOR RECOMMENDER SYSTEMS
Yehuda Koren et al.
COMPUTER (2009)
Cumulated gain-based evaluation of IR techniques
K Järvelin et al.
ACM TRANSACTIONS ON INFORMATION SYSTEMS (2002)
An empirical analysis of design choices in neighborhood-based collaborative filtering algorithms
J Herlocker et al.
INFORMATION RETRIEVAL (2002)
Share Paper
