activity
20182026
most citedMetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation

110 citations · 489 across the 29 of their papers we have counts for

collaborators
Showing 2022Show all

7 papers · 1 filter

cs.LG2022★ 1 cited

Estimator: An Effective and Scalable Framework for Transportation Mode Classification over Trajectories

Danlei Hu, Ziquan Fang, Hanxi Fang +4

Transportation mode classification, the process of predicting the class labels of moving objects transportation modes, has been widely applied to a variety of real world applicatio…

cs.DB2022★ 5 cited

PromptEM: Prompt-tuning for Low-resource Generalized Entity Matching

Pengfei Wang, Xiaocan Zeng, Lu Chen +4

Entity Matching (EM), which aims to identify whether two entity records from two relational tables refer to the same real-world entity, is one of the fundamental problems in data m…

cs.DB2022★ 40 cited

ClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similarities

Yunjun Gao, Xiaoze Liu, Junyang Wu +3

Entity alignment (EA) aims at finding equivalent entities in different knowledge graphs (KGs). Embedding-based approaches have dominated the EA task in recent years. Those methods…

cs.IR2022★ 78 cited

Self-Guided Learning to Denoise for Robust Recommendation

Yunjun Gao, Yuntao Du, Yujia Hu +4

The ubiquity of implicit feedback makes them the default choice to build modern recommender systems. Generally speaking, observed interactions are considered as positive samples, w…

cs.DB2022

Maximizing the Influence of Bichromatic Reverse k Nearest Neighbors in Geo-Social Networks

Pengfei Jin, Lu Chen, Yunjun Gao +3

Geo-social networks offer opportunities for the marketing and promotion of geo-located services. In this setting, we explore a new problem, called Maximizing the Influence of Bichr…

cs.IR2022★ 5 cited

HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation

Yuntao Du, Xinjun Zhu, Lu Chen +2

Knowledge graph (KG) plays an increasingly important role to improve the recommendation performance and interpretability. A recent technical trend is to design end-to-end models ba…

cs.IR2022★ 110 cited

MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation

Yuntao Du, Xinjun Zhu, Lu Chen +2

A knowledge graph (KG) consists of a set of interconnected typed entities and their attributes. Recently, KGs are popularly used as the auxiliary information to enable more accurat…