3 papers
cs.IR2018
GEMRank: Global Entity Embedding For Collaborative Filtering
Arash Khoeini, Bita Shams, Saman Haratizadeh
Recently, word embedding algorithms have been applied to map the entities of recommender systems, such as users and items, to new feature spaces using textual element-context relat…
cs.IR2018
IteRank: An iterative network-oriented approach to neighbor-based collaborative ranking
Bita Shams, Saman Haratizadeh
Neighbor-based collaborative ranking (NCR) techniques follow three consecutive steps to recommend items to each target user: first they calculate the similarities among users, then…
cs.SI2018
Reliable graph-based collaborative ranking
Bita Shams, Saman Haratizadeh
GRank is a recent graph-based recommendation approach the uses a novel heterogeneous information network to model users' priorities and analyze it to directly infer a recommendatio…