An Ensemble Hypergraph Learning Framework for Recommendation

[1]  Alireza Gharahighehi,et al.  Personalizing Diversity Versus Accuracy in Session-Based Recommender Systems , 2021, SN Computer Science.

[2]  Charu C. Aggarwal,et al.  Ensemble-Based and Hybrid Recommender Systems , 2016 .

[3]  Chun Chen,et al.  Music recommendation by unified hypergraph: combining social media information and music content , 2010, ACM Multimedia.

[4]  Robin D. Burke,et al.  Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.

[5]  Jie Lu,et al.  Multiobjective e-commerce recommendations based on hypergraph ranking , 2019, Inf. Sci..

[6]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[7]  Tao Li,et al.  News recommendation via hypergraph learning: encapsulation of user behavior and news content , 2013, WSDM.

[8]  Konstantinos Pliakos,et al.  Fair Multi-Stakeholder News Recommender System with Hypergraph ranking , 2021, Inf. Process. Manag..

[9]  Pasquale Lops,et al.  Content-based Recommender Systems: State of the Art and Trends , 2011, Recommender Systems Handbook.

[10]  Celine Vens,et al.  Diversification in session-based news recommender systems , 2021, Personal and Ubiquitous Computing.

[11]  Yi-Hsuan Yang,et al.  Modeling Multi-way Relations with Hypergraph Embedding , 2018, CIKM.

[12]  James Caverlee,et al.  Next-item Recommendation with Sequential Hypergraphs , 2020, SIGIR.

[13]  Tsvi Kuflik,et al.  Second workshop on information heterogeneity and fusion in recommender systems (HetRec2011) , 2011, RecSys '11.

[14]  Ji Zhang,et al.  A novel social network hybrid recommender system based on hypergraph topologic structure , 2018, World Wide Web.