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Flow-Based Algorithms for Local Graph Clustering [chapter]

Lorenzo Orecchia, Zeyuan Allen Zhu
2013 Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms  
This yields the first flow-based algorithm.  ...  All previously known local algorithms for graph partitioning are random-walk based and can only guarantee an output conductance of O(√(OPT)) when the target set has conductance OPT ∈ [0,1].  ...  Acknowledgements We thank Jon Kelner, Silvio Lattanzi, Vahab Mirrokni, Satish Rao and Luca Trevisan for helpful conversations.  ... 
doi:10.1137/1.9781611973402.94 dblp:conf/soda/OrecchiaZ14 fatcat:3okjbqrkdnfuvgz4uhdefkjery

Fast Local Flow-based Method using Parallel Multi-core CPUs Architecture

Rashed Salem, Menoufia University, Wafaa Abdel-Moneim, Mohamed Hassan, Zagazig University, Zagazig University
2021 International Journal of Intelligent Engineering and Systems  
Traditional methods of clustering are not suitable to tackle the problem of clustering large graphs because the computation is very costly, which is solved by local graph clustering using a given vertex  ...  OpenMP parallel library is utilized to parallelize the first and second stages of 3StageFlow algorithm whereas the SL algorithm is used for enhancing the runtime.  ...  Multicore CPUs are utilized for applying parallel local flow-based method on these applications. The proposed algorithm improves a local flow-based method to reach the best runtime.  ... 
doi:10.22266/ijies2021.0831.01 fatcat:aekbnk5ssrakbacien6jq3gzke

Corrections to "Flow-Based Clustering on Directed Graphs: A Structural Entropy Minimization Approach"

Yicheng Pan, Wei Luo, Feng Zheng, Shaojiang Wang, Yuan Yao, Hongan Wang, Waqas Nazeer
2021 IEEE Access  
In this study, first, we propose the flow-based clustering problem on directed graphs for this kind of cluster.  ...  Second, we develop a local algorithm for detecting the flow-based community that contains a particularly given vertex.  ...  In this study, first, we propose the flow-based clustering problem on directed graphs for this kind of cluster.  ... 
doi:10.1109/access.2021.3055392 fatcat:graopfgjfvgdninthcs2u7x6gq

HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering [article]

Ali Aghdaei, Zhiqiang Zhao, Zhuo Feng
2021 arXiv   pre-print
Our approach leverages a recent strongly-local max-flow-based clustering algorithm for detecting the sets of hypergraph vertices that minimize ratio cut.  ...  To further improve the algorithm efficiency, we propose a divide-and-conquer scheme by leveraging spectral clustering of the bipartite graphs corresponding to the original hypergraphs.  ...  In Algorithm 2 we present the details of the flow based local clustering technique.  ... 
arXiv:2108.07901v3 fatcat:nd74hogturfubmlkubln543jai

An Optimization Approach to Locally-Biased Graph Algorithms

Kimon Fountoulakis, David F. Gleich, Michael W. Mahoney
2017 Proceedings of the IEEE  
However, we will see in subsections that it simplifies for local spectral and flow graph clustering algorithms which use specific settings for h, g and γ. B.  ...  To the best of our knowledge there are no local graph clustering algorithms which are based on LP or the SDP relaxations. A.  ... 
doi:10.1109/jproc.2016.2637349 fatcat:5wunqhfstzfsfgljle56r4rhp4

An optimization approach to locally-biased graph algorithms [article]

Kimon Fountoulakis, David Gleich, Michael Mahoney
2016 arXiv   pre-print
Locally-biased graph algorithms are algorithms that attempt to find local or small-scale structure in a large data graph.  ...  In some cases, this can be accomplished by adding some sort of locality constraint and calling a traditional graph algorithm; but more interesting are locally-biased graph algorithms that compute answers  ...  However, we will see in the following subsections that it simplifies for local spectral and flow graph clustering algorithms with specific settings for h, g and γ. B.  ... 
arXiv:1607.04940v3 fatcat:7jifluhe3zgjdcfyfpiq4tt6ya

Flow-Based Local Graph Clustering with Better Seed Set Inclusion [article]

Nate Veldt and Christine Klymko and David Gleich
2019 arXiv   pre-print
Flow-based methods for local graph clustering have received significant recent attention for their theoretical cut improvement and runtime guarantees.  ...  In this work we present two improvements for using flow-based methods in real-world semi-supervised clustering problems.  ...  Conclusions and Future Work Flow-based algorithms for local graph clustering exhibit very strong cut improvement and runtime guarantees.  ... 
arXiv:1811.12280v2 fatcat:qwfpsauegvfmbkp2ikhq3vr5ym

A Max-Flow-Based Similarity Measure for Spectral Clustering

Jiangzhong Cao, Pei Chen, Yun Zheng, Qingyun Dai
2013 ETRI Journal  
The maximum flow between data points is computed as the new similarity, which can satisfy the requirement for similarity in the clustering method.  ...  The experiment results show the superiority of the new similarity: 1) The max-flow-based similarity measure can significantly improve the performance of spectral clustering; 2) It is robust and not sensitive  ...  In this graph, every vertex corresponds to a point in the D and each edge is weighted by the local similarity (4) between the connected points. 2) Construct the new similarity graph by the max-flow-based  ... 
doi:10.4218/etrij.13.0112.0520 fatcat:i5jvyqmoknfsbpvrhrf26adxbq

A Max-Flow-Based Similarity Measure for Spectral Clustering

Jiangzhong Cao
2013 ETRI Journal  
The maximum flow between data points is computed as the new similarity, which can satisfy the requirement for similarity in the clustering method.  ...  The experiment results show the superiority of the new similarity: 1) The max-flow-based similarity measure can significantly improve the performance of spectral clustering; 2) It is robust and not sensitive  ...  In this graph, every vertex corresponds to a point in the D and each edge is weighted by the local similarity (4) between the connected points. 2) Construct the new similarity graph by the max-flow-based  ... 
doi:10.4218/etrij.12.0112.0520 fatcat:v45toouoxfh7zevslpu7saxz2y

An Efficient Graph Cut Algorithm for Computer Vision Problems [chapter]

Chetan Arora, Subhashis Banerjee, Prem Kalra, S. N. Maheshwari
2010 Lecture Notes in Computer Science  
It has been shown that graph cut algorithms designed keeping the structure of vision based flow graphs in mind are more efficient than known strongly polynomial time max-flow algorithms based on preflow  ...  We present here a new algorithm for graph cuts which not only exploits the structural properties inherent in image based grid graphs but also combines the basic paradigms of max-flow theory in a novel  ...  The authors would like to thank Niloy Mitra and the referees for their comments, inputs and careful reading of the manuscript.  ... 
doi:10.1007/978-3-642-15558-1_40 fatcat:mvken5cm7bhwnggn4zvlx2h2ga

Flow-based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance [article]

K. Fountoulakis, M. Liu, D. F. Gleich, M. W. Mahoney
2022 arXiv   pre-print
These cluster improvement algorithms are powerful, both in theory and in practice, but they have not been widely adopted for problems such as community detection, local graph clustering, semi-supervised  ...  Many such cluster improvement algorithms are flow-based methods, by which we mean that operationally they require the solution of a sequence of maximum flow problems on a (typically implicitly) modified  ...  of flow algorithms, and finally Kent Quanrud for many helpful pointers.  ... 
arXiv:2004.09608v3 fatcat:f3ma3k4dsbgjherlsie2jtzc34

Rough Set Flow Graphs and Ant Based Clustering in Classification of Disturbed Periodic Biosignals

Krzysztof Pancerz, Arkadiusz Lewicki, Ryszard Tadeusiewicz, Jan Warchol
2012 International Workshop on Concurrency, Specification and Programming  
A local function in the applied clustering algorithm is calculated on the basis of temporal rough set flow graphs representing an information flow distribution for episodes.  ...  An ant based clustering algorithm is used to group episodes into which examined biosignals are divided.  ...  Temporal rough set flow graphs representing an information flow distribution for episodes are used in the clustering algorithm for calculation of the local function.  ... 
dblp:conf/csp/PancerzLTW12 fatcat:wixz7lslzvgpjamcb3jdnvxpbu

Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning [article]

Meng Liu, Nate Veldt, Haoyu Song, Pan Li, David F. Gleich
2021 arXiv   pre-print
Although many methods for local clustering exist for graphs, there are relatively few for localized clustering in hypergraphs.  ...  personalized PageRank clustering for graphs.  ...  for flow-based hypergraph clustering [33] .  ... 
arXiv:2011.07752v2 fatcat:fek5cjwoonbwpnbud7atwpw4nu

flow-based clustering and spectral clustering: a comparison [article]

Y. SarcheshmehPour, Y. Tian, L. Zhang, A. Jung
2022 arXiv   pre-print
We propose and study a novel graph clustering method for data with an intrinsic network structure.  ...  Our results indicate that our clustering methods can cope with certain graph structures that are challenging for spectral clustering methods.  ...  FLOW-BASED GRAPH CLUSTERING We are now in the position to formulate our flow-based graph clustering method as Algorithm 2.  ... 
arXiv:2206.10019v1 fatcat:thwfh5jkmnghzis577vtqao7re

Local hypergraph clustering using capacity releasing diffusion

Rania Ibrahim, David F. Gleich, Irene Sendiña-Nadal
2020 PLoS ONE  
However, an alternative perspective on local graph clustering arises from using max-flow and min-cut on the objectives, which offer distinctly different guarantees.  ...  Local graph clustering is an important machine learning task that aims to find a well-connected cluster near a set of seed nodes.  ...  For more about the trade-offs of local clustering and local graph analysis, we defer to the surveys [3] .  ... 
doi:10.1371/journal.pone.0243485 pmid:33362247 fatcat:jgdezoj52rd4pjwjj7u5czyov4
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