Attributed Graph Mining
Attributed Graph Mining is a subfield of graph mining that focuses on extracting patterns, relationships, and knowledge from graphs whose vertices and/or edges are associated with attribute data, thereby enabling richer analysis by integrating structural and attribute information.
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3.4K
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186
Authors
98
Institutions
Publications per year
2017–2026
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A model-based approach to attributed graph clustering
Zhiqiang Xu, Yiping Ke, Yi Wang et al. · 2012 · 338 citations
Computing, Data Science, Data Mining +11
Effective community search for large attributed graphs
Yixiang Fang, Reynold Cheng, Siqiang Luo et al. · Proceedings of the VLDB Endowment · 2016 · 315 citations
Attributed Graph Clustering via Adaptive Graph Convolution
Xiaotong Zhang, Han Liu, Qimai Li et al. · 2019 · 287 citations · Full text
Fast best-effort pattern matching in large attributed graphs
Hanghang Tong, Christos Faloutsos, Brian Gallagher et al. · 2007 · 255 citations
Focused clustering and outlier detection in large attributed graphs
Bryan Perozzi, Leman Akoglu, Patricia Iglesias Sánchez et al. · 2014 · 233 citations
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Centre National de la Recherche Scientifique
Paris, France
4 h-index
6 publications
105 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
3 h-index
7 publications
509 citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
3 h-index
11 publications
1.2K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
3 h-index
10 publications
1.3K citations

Queensland University of Technology
Brisbane, Australia
2 h-index
2 publications
210 citations
Ontario Tech University
Oshawa, Canada
2 h-index
4 publications
102 citations
Technische Universität Berlin
Berlin, Germany
2 h-index
3 publications
189 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
7 publications
411 citations
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3 publications · 87 citations
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Repository · 3 publications · 73 citations
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2 publications · 27 citations
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2 publications · 57 citations
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2 publications · 34 citations
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