Since real-world objects and their interactions are often multi-modal and multi-typed,
heterogeneous networks have been widely used as a more powerful, realistic, and generic …

Recommender systems play a significant role in information filtering and have been utilized
in different scenarios, such as e-commerce and social media. With the prosperity of deep …

Reviews on online shopping websites affect the buying decisions of customers, meanwhile,
attract lots of spammers aiming at misleading buyers. Xianyu, the largest second-hand …

Explainability and effectiveness are two key aspects for building recommender systems.
Prior efforts mostly focus on incorporating side information to achieve better …

Collaborative filtering (CF) usually suffers from limited performance in recommendation
systems due to the sparsity of user–item interactions and cold start problems. To address …

Heterogeneous information network has been widely used to alleviate sparsity and cold start
problems in recommender systems since it can model rich context information in user-item …

Visualization recommendation or automatic visualization generation can significantly lower
the barriers for general users to rapidly create effective data visualizations, especially for …

Interactive recommender system (IRS) has drawn huge attention because of its flexible
recommendation strategy and the consideration of optimal long-term user experiences. To …

Reasoning on the knowledge graph (KG) aims to infer new facts from existing ones.
Methods based on the relational path have shown strong, interpretable, and transferable …

Incorporating Knowledge Graphs (KG) into recommeder system as side information has
attracted considerable attention. Recently, the technical trend of Knowledge-aware …