Knowledge graphs capture structured information and relations between a set of entities or
items. As such knowledge graphs represent an attractive source of information that could …

Recommender systems have shown great potential to solve the information explosion
problem and enhance user experience in various online applications. To tackle data sparsity …

To address the sparsity and cold start problem of collaborative filtering, researchers usually
make use of side information, such as social networks or item attributes, to improve …

Collaborative filtering often suffers from sparsity and cold start problems in real
recommendation scenarios, therefore, researchers and engineers usually use side …

Heterogeneous graph neural networks (HGNNs) have the powerful capability to embed rich
structural and semantic information of a heterogeneous graph into node representations …

Due to the flexibility in modelling data heterogeneity, heterogeneous information network
(HIN) has been adopted to characterize complex and heterogeneous auxiliary data in …

Heterogeneous information network (HIN) has been widely adopted in recommender
systems due to its excellence in modeling complex context information. Although existing …

Abstract Knowledge graphs, representation of information as a semantic graph, have
caused wide concern in both industrial and academic world. Their property of providing …

With the prevalence of mobile e-commerce nowadays, a new type of recommendation
services, called intent recommendation, is widely used in many mobile e-commerce Apps …

Recommender systems (RSs) have been the most important technology for increasing the
business in Taobao, the largest online consumer-to-consumer (C2C) platform in China …