Multiple Structure-View Learning for Graph Classification

Many applications involve objects containing structure and rich content information, each describing different feature aspects of the object. Graph learning and classification is a common tool for handling such objects. To date, existing graph classification has been limited to the single-graph sett...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 29; H. 7; S. 3236 - 3251
Hauptverfasser:	Wu, Jia, Pan, Shirui, Zhu, Xingquan, Zhang, Chengqi, Yu, Philip S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.07.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Chemical compounds Classification Correlation Graph graph classification Graphical representations Graphs Image color analysis Labels Learning Learning systems Machine learning multiview learning Periodic structures Proteins Regularization subgraph mining Visualization
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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