Structural Deep Clustering Network
Beijing University of Posts and Telecommunications · Tencent (China) · +1 more institution
Abstract
Clustering is a fundamental task in data analysis. Recently, deep clustering, which derives inspiration primarily from deep learning approaches, achieves state-of-the-art performance and has attracted considerable attention. Current deep clustering methods usually boost the clustering results by means of the powerful representation ability of deep learning, e.g., autoencoder, suggesting that learning an effective representation for clustering is a crucial requirement. The strength of deep clustering methods is to extract the useful representations from the data itself, rather than the structure of data, which receives scarce attention in representation learning. Motivated by the great success of Graph…
Citation impact
- FWCI
- 30.86
- Percentile
- 100%
- References
- 12
Authors
6- DBDeyu BoCorresponding
Beijing University of Posts and Telecommunications
- XWXiao Wang
Beijing University of Posts and Telecommunications
- CSChuan Shi
Beijing University of Posts and Telecommunications
- MZMeiqi Zhu
Beijing University of Posts and Telecommunications
- ELEmiao Lu
Tencent (China)
Topics & keywords
- Autoencoder
- Cluster analysis
- Deep learning
- Graph
- Feature learning
- Convolutional neural network
- Representation (politics)
- External Data Representation