activity
20152021
most citedA Survey of Millimeter Wave (mmWave) Communications for 5G: Opportunities and Challenges

153 citations · 532 across the 12 of their papers we have counts for

collaborators

18 papers

cs.IR2022119 cited

Disentangling Long and Short-Term Interests for Recommendation

Yu Zheng, Chen Gao, Jianxin Chang +4

Modeling user's long-term and short-term interests is crucial for accurate recommendation. However, since there is no manually annotated label for user interests, existing approach…

cs.IR20219 cited

Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks

Zirui Zhu, Chen Gao, Xu Chen +3

Incorporating social relations into the recommendation system, i.e. social recommendation, has been widely studied in academic and industrial communities. While many promising resu…

cs.IR20215 cited

Improving Location Recommendation with Urban Knowledge Graph

Chang Liu, Chen Gao, Depeng Jin +1

Location recommendation is defined as to recommend locations (POIs) to users in location-based services. The existing data-driving approaches of location recommendation suffer from…

cs.IR2021132 cited

DGCN: Diversified Recommendation with Graph Convolutional Networks

Yu Zheng, Chen Gao, Liang Chen +2

These years much effort has been devoted to improving the accuracy or relevance of the recommendation system. Diversity, a crucial factor which measures the dissimilarity among the…

cs.IR2021

Efficient Data-specific Model Search for Collaborative Filtering

Chen Gao, Quanming Yao, Depeng Jin +1

Collaborative filtering (CF), as a fundamental approach for recommender systems, is usually built on the latent factor model with learnable parameters to predict users' preferences…

cs.LG2021

Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution

Fuxian Li, Jie Feng, Huan Yan +3

Traffic prediction is the cornerstone of an intelligent transportation system. Accurate traffic forecasting is essential for the applications of smart cities, i.e., intelligent tra…