activity
20162022
most citedUltra-Scalable Spectral Clustering and Ensemble Clustering

455 citations · 610 across the 5 of their papers we have counts for

collaborators

9 papers

cs.IR20222 cited

GSR: Global Graph Guided Session-based Recommendation

Zhi-Hong Deng, Chang-Dong Wang, Ling Huang +2

Session-based recommendation tries to make use of anonymous session data to deliver high-quality recommendation under the condition that user-profiles and the complete historical b…

cs.IR20211 cited

BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism

Zi-Yuan Hu, Jin Huang, Zhi-Hong Deng +4

Collaborative Filtering (CF) based recommendation methods have been widely studied, which can be generally categorized into two types, i.e., representation learning-based CF method…

cs.SI2019131 cited

EdMot: An Edge Enhancement Approach for Motif-aware Community Detection

Pei-Zhen Li, Ling Huang, Chang-Dong Wang +1

Network community detection is a hot research topic in network analysis. Although many methods have been proposed for community detection, most of them only take into consideration…

cs.LG2019455 cited

Ultra-Scalable Spectral Clustering and Ensemble Clustering

Dong Huang, Chang-Dong Wang, Jian-Sheng Wu +2

This paper focuses on scalability and robustness of spectral clustering for extremely large-scale datasets with limited resources. Two novel algorithms are proposed, namely, ultra-…

cs.LG201921 cited

DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System

Zhi-Hong Deng, Ling Huang, Chang-Dong Wang +2

In general, recommendation can be viewed as a matching problem, i.e., match proper items for proper users. However, due to the huge semantic gap between users and items, it's almos…

cs.LG2018

Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities

Dong Huang, Chang-Dong Wang, Hongxing Peng +2

Ensemble clustering has been a popular research topic in data mining and machine learning. Despite its significant progress in recent years, there are still two challenging issues…