Titlebook: Database Systems for Advanced Applications; 27th International C Arnab Bhattacharya,Janice Lee Mong Li,Rage Uday Ki Conference proceedings

Hay-Fever

高歌

Joint Locality Preservation and Adaptive Combination for Graph Collaborative Filtering-items as a bipartite graph, has become the upstart in recommender systems. Nevertheless, existing GCNs based recommendation model only compromisingly exploits the shallow relationship (generally less than 4 layers) to represent the user and item with different number of interactions, which limits t

immunity

Gated Hypergraph Neural Network for Scene-Aware Recommendationisting methods only explore one or some certain components of the entire interactions. In fact, the entire interaction process is much richer and more complex, including but not limited to “who purchases what items in which merchant under what interaction environments”. Furthermore, many interaction

南极

Hyperbolic Personalized Tag Recommendationg to users’ tagging preferences. The main challenge of PTR is to learn representations of involved entities (i.e., users, items, and tags) from interaction data without loss of structural properties in original data. To this end, various PTR models have been developed to conduct representation learn

Daily-Value

DIS

addict

黄油没有

巧办法

Arnab Bhattacharya,Janice Lee Mong Li,Rage Uday Ki

COMMA