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   Articles with "graph partitioning" as a keyword



A fuzzy clustering based method for attributed graph partitioning

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recommendations! Published in 2019 at "Journal of Ambient Intelligence and Humanized Computing"

DOI: 10.1007/s12652-018-1054-2

Abstract: Graph partitioning methods in data mining have been widely used to discover protein complexes in protein–protein interaction (PPI) network. However, PPI networks with attributes need more effective attribute graph partitioning methods. Attribute graph partitioning aims… read more here.

Keywords: graph partitioning; attributed graph; fuzzy clustering; method attributed ... See more keywords

Revisiting the Isoperimetric Graph Partitioning Problem

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recommendations! Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2901094

Abstract: Isoperimetric graph partitioning, which is also known as the Cheeger cut, is NP-hard in its original form. In the literature, multiple modifications to this problem have been proposed to obtain approximation algorithms for clustering applications.… read more here.

Keywords: graph partitioning; problem; partitioning problem; graph ... See more keywords

Parallel Heuristics for Balanced Graph Partitioning Based on Richness of Implicit Knowledge

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recommendations! Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2926753

Abstract: Balanced graph partitioning (BGP) has a wide range of applications that involve many large-scale distributed data processing problems. However, most of the existing approaches to parallel graph partitioning neglect the problem of the richness of… read more here.

Keywords: graph partitioning; balanced graph; richness implicit; graph ... See more keywords

Hyper-Graph Partitioning for a Multi-Agent Reformulation of Large-Scale MILPs

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recommendations! Published in 2021 at "IEEE Control Systems Letters"

DOI: 10.1109/lcsys.2021.3093338

Abstract: This letter addresses the challenge of solving large-scale Mixed Integer Linear Programs (MILPs). A resolution scheme is proposed for the class of MILPs with a hidden constraint-coupled multi-agent structure. In particular, we focus on the… read more here.

Keywords: graph partitioning; multi agent; hyper graph; reformulation ... See more keywords

Lightweight Graph Partitioning Enhanced by Implicit Knowledge

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recommendations! Published in 2025 at "IEEE Transactions on Computers"

DOI: 10.1109/tc.2025.3612730

Abstract: Graph partitioning as a classic NP-complete problem, is the most fundamental procedure that needs to be performed before parallel computations. Partitioners can be divided into vertex- and edge-based approaches. Recently, both approaches are employing a… read more here.

Keywords: implicit knowledge; graph partitioning; lightweight graph; knowledge ... See more keywords

Structure-Attribute-Based Social Network Deanonymization With Spectral Graph Partitioning

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recommendations! Published in 2022 at "IEEE Transactions on Computational Social Systems"

DOI: 10.1109/tcss.2021.3082901

Abstract: Online social networks have gained tremendous popularity and have dramatically changed the way we communicate in recent years. However, the publishing of social network data raises more and more privacy concerns. To protect user privacy,… read more here.

Keywords: social network; network; graph partitioning; spectral graph ... See more keywords

Co-Clustering by Directly Solving Bipartite Spectral Graph Partitioning

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recommendations! Published in 2024 at "IEEE Transactions on Cybernetics"

DOI: 10.1109/tcyb.2024.3451292

Abstract: Bipartite spectral graph partitioning (BSGP) method as a co-clustering method, has been widely used in document clustering, which simultaneously clusters documents and words by making full use of the duality between documents and words. It… read more here.

Keywords: method; graph partitioning; spectral graph; bipartite spectral ... See more keywords

Cost-Aware Partitioning for Efficient Large Graph Processing in Geo-Distributed Datacenters

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recommendations! Published in 2020 at "IEEE Transactions on Parallel and Distributed Systems"

DOI: 10.1109/tpds.2019.2955494

Abstract: Graph processing is an emerging computation model for a wide range of applications and graph partitioning is important for optimizing the cost and performance of graph processing jobs. Recently, many graph applications store their data… read more here.

Keywords: graph partitioning; graph processing; graph; cost ... See more keywords

Dual Clustering-Based Method for Geospatial Knowledge Graph Partitioning

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recommendations! Published in 2024 at "Applied Sciences"

DOI: 10.3390/app142210704

Abstract: Geospatial knowledge graphs provide critical technology for integrating geographic information and semantic knowledge, which are very useful for geographic data analysis. As the scale of geospatial knowledge graphs continues to grow, the distributed management of… read more here.

Keywords: graph partitioning; knowledge; knowledge graphs; geospatial knowledge ... See more keywords