articleApr 20, 2020GOLD OA

Structural Deep Clustering Network

DBDeyu BoXWXiao WangCSChuan ShiMZMeiqi ZhuELEmiao Lu

Beijing University of Posts and Telecommunications · Tencent (China) · +1 more institution

Indexed inarxivcrossref

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

484
total citations
FWCI
30.86
Percentile
100%
References
12
Citations per year

Authors

6
  • DB
    Deyu BoCorresponding

    Beijing University of Posts and Telecommunications

  • XW
    Xiao Wang

    Beijing University of Posts and Telecommunications

  • CS
    Chuan Shi

    Beijing University of Posts and Telecommunications

  • MZ
    Meiqi Zhu

    Beijing University of Posts and Telecommunications

  • EL
    Emiao Lu

    Tencent (China)

Topics & keywords

Keywords
  • Autoencoder
  • Cluster analysis
  • Deep learning
  • Graph
  • Feature learning
  • Convolutional neural network
  • Representation (politics)
  • External Data Representation
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