Residential College | false |
Status | 已發表Published |
Zero-shot Node Classification with Decomposed Graph Prototype Network | |
Zheng Wang1,2; Jialong Wang1; Yuchen Guo3; Zhiguo Gong1 | |
2021-08-14 | |
Conference Name | 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021 |
Source Publication | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining |
Pages | 1769-1779 |
Conference Date | 14-18 August 2021 |
Conference Place | Virtual, Online |
Abstract | Node classification is a central task in graph data analysis. Scarce or even no labeled data of emerging classes is a big challenge for existing methods. A natural question arises: can we classify the nodes from those classes that have never been seen? In this paper, we study this zero-shot node classification (ZNC) problem which has a two-stage nature: (1) acquiring high-quality class semantic descriptions (CSDs) for knowledge transfer, and (2) designing a well generalized graph-based learning model. For the first stage, we give a novel quantitative CSDs evaluation strategy based on estimating the real class relationships, to get the "best"CSDs in a completely automatic way. For the second stage, we propose a novel Decomposed Graph Prototype Network (DGPN) method, following the principles of locality and compositionality for zero-shot model generalization. Finally, we conduct extensive experiments to demonstrate the effectiveness of our solutions. |
Keyword | Node Classification Graph Convolutional Networks Graph Data Analysis |
DOI | 10.1145/3447548.3467230 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science |
WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods |
WOS ID | WOS:000749556801079 |
Scopus ID | 2-s2.0-85114954302 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) Faculty of Science and Technology DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
Corresponding Author | Zhiguo Gong |
Affiliation | 1.State Key Laboratory of Internet of Things for Smart City, University of Macau, China 2.Department of Computer Science and Technology, University of Science and Technology, Beijing, China 3.Institute for Brain and Cognitive Sciences, BNRist, Tsinghua University, China |
First Author Affilication | University of Macau |
Corresponding Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Zheng Wang,Jialong Wang,Yuchen Guo,et al. Zero-shot Node Classification with Decomposed Graph Prototype Network[C], 2021, 1769-1779. |
APA | Zheng Wang., Jialong Wang., Yuchen Guo., & Zhiguo Gong (2021). Zero-shot Node Classification with Decomposed Graph Prototype Network. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1769-1779. |
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