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Do Logarithmic Proximity Measures Outperform Plain Ones in Graph Clustering?
Springer Proceedings in Mathematics & Statistics - Models, Algorithms, and Technologies for Network Analysis
◽
10.1007/978-3-319-56829-4_8
◽
2017
◽
pp. 87-105
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Cited By ~ 5
Author(s):
Vladimir Ivashkin
◽
Pavel Chebotarev
Keyword(s):
Graph Clustering
◽
Proximity Measures
Download Full-text
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Efficiency of Transformations of Proximity Measures for Graph Clustering
Lecture Notes in Computer Science - Algorithms and Models for the Web Graph
◽
10.1007/978-3-030-25070-6_2
◽
2019
◽
pp. 16-29
◽
Cited By ~ 2
Author(s):
Rinat Aynulin
Keyword(s):
Graph Clustering
◽
Proximity Measures
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The cluster algorithms for solving problems with asymmetric proximity measures
Сибирский журнал вычислительной математики
◽
10.15372/sjnm20180201
◽
2018
◽
Keyword(s):
Cluster Algorithms
◽
Proximity Measures
◽
Asymmetric Proximity
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An Efficient Method for Attributed Graph Clustering
Chinese Journal of Computers
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10.3724/sp.j.1016.2013.01704
◽
2014
◽
Vol 36
(8)
◽
pp. 1704-1713
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Cited By ~ 1
Author(s):
Ye WU
◽
Zhi-Nong ZHONG
◽
Wei XIONG
◽
Luo CHEN
◽
Ning JING
Keyword(s):
Efficient Method
◽
Graph Clustering
◽
Attributed Graph
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An unsupervised classification approach for hyperspectral images based adaptive spatial and spectral neighborhood selection and graph clustering
Procedia Computer Science
◽
10.1016/j.procs.2018.08.008
◽
2018
◽
Vol 126
◽
pp. 743-750
◽
Cited By ~ 2
Author(s):
Manel Ben Salem
◽
Karim Saheb Ettabaa
◽
Med Salim Bouhlel
Keyword(s):
Unsupervised Classification
◽
Graph Clustering
◽
Hyperspectral Images
◽
Classification Approach
◽
Neighborhood Selection
◽
Spectral Neighborhood
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Asymmetric Semi-Nonnegative Matrix Factorization for Directed Graph Clustering
2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)
◽
10.1109/iccke50421.2020.9303649
◽
2020
◽
Author(s):
Reyhaneh Abdollahi
◽
Seyed Amjad Seyedi
◽
Mohamad Reza Noorimehr
Keyword(s):
Directed Graph
◽
Matrix Factorization
◽
Nonnegative Matrix Factorization
◽
Nonnegative Matrix
◽
Graph Clustering
Download Full-text
Improving Accuracy of Differentially Private Kronecker Social Networks via Graph Clustering
2020 International Symposium on Networks, Computers and Communications (ISNCC)
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10.1109/isncc49221.2020.9297349
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2020
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Author(s):
Arinjita Paul
◽
Vorapong Suppakitpaisarn
◽
Mitali Bafna
◽
C. Pandu Rangan
Keyword(s):
Social Networks
◽
Graph Clustering
◽
Improving Accuracy
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Fuzzy graph clustering
Information Sciences
◽
10.1016/j.ins.2021.04.058
◽
2021
◽
Author(s):
Yong Peng
◽
Xin Zhu
◽
Feiping Nie
◽
Wanzeng Kong
◽
Yuan Ge
Keyword(s):
Graph Clustering
◽
Fuzzy Graph
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Local Graph Clustering with Network Lasso
IEEE Signal Processing Letters
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10.1109/lsp.2020.3045832
◽
2020
◽
pp. 1-1
Author(s):
Alexander Jung
◽
Yasmin Sarcheshmehpour
Keyword(s):
Graph Clustering
◽
Local Graph
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Image Co-saliency Detection and Instance Co-segmentation using Attention Graph Clustering based Graph Convolutional Network
IEEE Transactions on Multimedia
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10.1109/tmm.2021.3054526
◽
2021
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pp. 1-1
Author(s):
Tengpeng Li
◽
Kaihua Zhang
◽
Shiwen Shen
◽
Bo Liu
◽
Qingshan Liu
◽
...
Keyword(s):
Saliency Detection
◽
Graph Clustering
◽
Convolutional Network
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Effectively Explaining Missing Nodes on Structural Graph Clustering
2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)
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10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00089
◽
2020
◽
Author(s):
Xiufeng Xia
◽
Jida Min
◽
Chuanyu Zong
◽
Jiajia Li
◽
Xiangyu Liu
◽
...
Keyword(s):
Graph Clustering
◽
Structural Graph
Download Full-text
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