Dingxian Wang

Click-Through Rate Prediction with Multi-Modal Hypergraphs

2021

Advertising is critical to many online e-commerce platforms such as e-Bay and Amazon. One of the important signals that these platforms rely upon is the click-through rate (CTR) prediction. The recent popularity of multi-modal sharing …

Explainable Reasoning over Knowledge Graphs for Recommendation

2018 · arXiv (Cornell University)

Incorporating knowledge graph into recommender systems has attracted increasing attention in recent years. By exploring the interlinks within a knowledge graph, the connectivity between users and items can be discovered as paths, which provide rich …

BiRank: Towards Ranking on Bipartite Graphs

2016 · IEEE Transactions on Knowledge and Data Engineering

The bipartite graph is a ubiquitous data structure that can model the relationship between two entity types: for instance, users and items, queries and webpages. In this paper, we study the problem of ranking vertices …

Learning Intents behind Interactions with Knowledge Graph for Recommendation

2021

Knowledge graph (KG) plays an increasingly important role in recommender systems. A recent technical trend is to develop end-to-end models founded on graph neural networks (GNNs). However, existing GNN-based models are coarse-grained in relational modeling, …