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Enhanced Community Structure Detection in Complex Networks with Partial Background Information [article]

Zhong-Yuan Zhang and Kai-Di Sun and Si-Qi Wang
2013 arXiv   pre-print
Community structure detection in complex networks is important since it can help better understand the network topology and how the network works.  ...  In this paper, different from the traditional methodologies, we design an enhanced semi-supervised learning framework for community detection, which can effectively incorporate the available prior information  ...  Enhanced semi-supervised learning for community structure detection In this section, we discuss our enhanced learning frameworks for community structure detection.  ... 
arXiv:1210.2473v2 fatcat:uizgu3qfxzcr5jftecukgg2jya

Active link selection for efficient semi-supervised community detection

Liang Yang, Di Jin, Xiao Wang, Xiaochun Cao
2015 Scientific Reports  
Several semi-supervised community detection algorithms have been proposed recently to improve the performance of traditional topology-based methods.  ...  Our main idea is that, by connecting uncertain nodes to their community hubs and disconnecting the inter-community edges, one can sharpen the block structure of adjacency matrix more efficiently than randomly  ...  demand for supervised information and obviously improves the efficiency of the semi-supervised community detection.  ... 
doi:10.1038/srep09039 pmid:25761385 pmcid:PMC4649850 fatcat:aqv7xfrk5rh3vdjxgyvk4cd25e

Semi-Supervised Overlapping Community Finding based on Label Propagation with Pairwise Constraints [article]

Elham Alghamdi, Derek Greene
2018 arXiv   pre-print
In this work, we explore the potential of semi-supervised strategies to improve algorithms for finding overlapping communities in networks.  ...  Algorithms for detecting communities in complex networks are generally unsupervised, relying solely on the structure of the network.  ...  The vast majority of semi-supervised algorithms in this area aim solely at detecting disjoint communities, whereas many real-world social networks contain overlapping structures [1] .  ... 
arXiv:1810.05511v2 fatcat:dh6fussdcvhjvif7x2ql4l645a

Community Detection-Based Feature Construction for Protein Sequence Classification [chapter]

Karthik Tangirala, Nic Herndon, Doina Caragea
2015 Lecture Notes in Computer Science  
Our approach uses the Hamming distance between short nucleotide subsequences, called k-mers, to construct a network, and subsequently uses community detection to identify groups of k-mers that appear frequently  ...  In prior work, we have proposed the use of a community detection approach to construct low dimensional feature sets for nucleotide sequence classification.  ...  Feature Construction Using Community Detection Community Detection Algorithm Complex network analysis has gained a lot of attention among researchers interested in identifying hidden structural and relational  ... 
doi:10.1007/978-3-319-19048-8_28 fatcat:skiszp5tonavvowsacjztxgzqq

Enhanced Community Structure Detection in Complex Networks with Partial Background Information

Zhong-Yuan Zhang, Kai-Di Sun, Si-Qi Wang
2013 Scientific Reports  
Community structure detection in complex networks is important since it can help better understand the network topology and how the network works.  ...  In this paper, different from the traditional methodologies, we design an enhanced semi-supervised learning framework for community detection, which can effectively incorporate the available prior information  ...  Methods Enhanced semi-supervised learning for community structure detection. In this section, we give our enhanced learning framework for community structure detection.  ... 
doi:10.1038/srep03241 pmid:24247657 pmcid:PMC4894381 fatcat:yz2rodv24za5tauzmxojanhgqm

The network representation learning algorithm based on semi-supervised random walk

Dong Liu, Qinpeng Li, Yan Ru, Jun Zhang
2020 IEEE Access  
Inspired by the semi-supervised community detection in complex networks, in this paper, a novel Semi-Supervised DeepWalk method(SSDW) is proposed for network representation learning, which successfully  ...  preserves the community structure of network in the embedding space.  ...  In the field of community detection, a lot of methods use pairwise constraints to improve the accuracy of community detection and design semi-supervised community detection algorithms.  ... 
doi:10.1109/access.2020.3044367 fatcat:6xajmaithvff7fqkzntrx34vua

A Signal-Strategy-Based Spectral Clustering Method for Community Detection in Complex Networks

Yutong Cui, Qiang Niu, Zhixiao Wang, Changjiang Du
2017 International Journal of Hybrid Information Technology  
This paper presents a semi-supervised spectral approach for community detection, the proposed method uses signal strategy to generate the Laplacian matrix, and utilizes prior knowledge to further guarantee  ...  The community detection has been one of the core subjects in complex networks. Spectral clustering is an efficient method widely used in this field.  ...  After the computation of Laplacian matrix semi L , use classic spectral strategy for community detection.  ... 
doi:10.14257/ijhit.2017.10.11.02 fatcat:d5v5njbhzfhajkzkrjbp6hwwmi

Community structure detection in complex networks with partial background information

Zhong-Yuan Zhang
2013 Europhysics letters  
In this paper, we propose a semi-supervised learning framework for community structure detection.  ...  However, how to encode constraints into community structure detection, within complex networks, remains a challenging problem.  ...  Semi-supervised learning for community structure detection In this section, we formulate our semi-supervised framework for community structure detection.  ... 
doi:10.1209/0295-5075/101/48005 fatcat:fk2r57snqfd3zmgbmlx7tsygca

An efficient semi-supervised community detection framework in social networks

Zhen Li, Yong Gong, Zhisong Pan, Guyu Hu, Sergio Gómez
2017 PLoS ONE  
In this paper, we propose a semi-supervised community detection framework which can effectively incorporate two types of pairwise constraints into the detection process.  ...  In the real world, topology information alone is often inadequate to accurately find out community structure due to its sparsity and noise.  ...  widely used real-world networks, and compare it with three existing semi-supervised community detection methods.  ... 
doi:10.1371/journal.pone.0178046 pmid:28542520 pmcid:PMC5441628 fatcat:mtqddf5jyrgltnkmm5upskayeq

Semi-supervised Community Detection via Constraint Matrix Construction and Active Node Selection

Suqi Zhang, Junyan Wu, Jianxin Li, Junhua Gu, Xianchao Tang, Xinyun Xu
2019 IEEE Access  
INDEX TERMS Community detection, non-negative matrix factorization, semi-supervised learning, active learning.  ...  Here, we present a novel semi-supervised and active learning method for community detection to integrate these two types of information of a network so as to increase the accuracy of community identification  ...  This is an enhanced semi-supervised community detection method.  ... 
doi:10.1109/access.2019.2962634 fatcat:pl2ba7l5qra5zbps4jfsq3jpfi

DETECTING DISEASED IMAGES BY USING SEMI – SUPERVISED LEARNING

DINESH KUMAR A, SHAHUL HAMMED, HANAH AYISHA V HYDER ALI, NIDHYA R
2015 International journal of computer and communication technology  
And for classification of diseases, a manifold learning method, called parameter-free semi-supervised local Fisher discriminant analysis is used.  ...  We are detecting diseased images by the process of segmentation and classification. The segmentation used in this paper has two advantages.  ...  and Communication Technology (IJCCT), ISSN: 2231-0371, Vol-6, Iss-3 Detecting Diseased images by using Semi -Supervised Learning International Journal of Computer and Communication Technology (IJCCT  ... 
doi:10.47893/ijcct.2015.1305 fatcat:joum2j57uvdc7bodwvtbvw6qte

Community-Detection via Hashtag-Graphs for Semi-Supervised NMF Topic Models [article]

Mattias Luber and Anton Thielmann and Christoph Weisser and Benjamin Säfken
2021 arXiv   pre-print
Therefore, this paper outlines a novel approach on how to integrate topic structures of hashtag graphs into the estimation of topic models by connecting graph-based community detection and semi-supervised  ...  This ultimately completely neglects the fact that a lot of topical-information can be actually retrieved from so-called hashtag-graphs by applying common community detection algorithms.  ...  The semi-supervised approach on the other hand can make use of the topic information derived by the community detection and leads to more consistent and intuitive results.  ... 
arXiv:2111.10401v1 fatcat:je63bxjf3vevrpzw7vzwdcd4u4

SELP: Semi-supervised evidential label propagation algorithm for graph data clustering

Kuang Zhou, Arnaud Martin, Quan Pan, Zhunga Liu
2018 International Journal of Approximate Reasoning  
Abstract With the increasing size of social networks in the real world, community detection approaches should be fast and accurate.  ...  The main advantage of SELP is that it can effectively use limited supervised information to guide the detection process.  ...  The original LPA [4] and the semi-supervised community detection approach SLP [5] were used for comparison.  ... 
doi:10.1016/j.ijar.2017.09.008 fatcat:5efrisyntvbn7ezb3fhrwu5sfy

Semi-supervised evidential label propagation algorithm for graph data [article]

Kuang Zhou
2016 arXiv   pre-print
In this paper, a Semi-supervised clustering approach using a new Evidential Label Propagation strategy (SELP) is proposed to incorporate the domain knowledge into the community detection model.  ...  In the task of community detection, there often exists some useful prior information.  ...  The original LPA [5] and the semi-supervised community detection approach SLP [4] were used to compare.  ... 
arXiv:1607.08695v1 fatcat:iuxhkelabrdzjhl3fwbuidd5qa

Semi-supervised Evidential Label Propagation Algorithm for Graph Data [chapter]

Kuang Zhou, Arnaud Martin, Quan Pan
2016 Lecture Notes in Computer Science  
In this paper, a Semi-supervised clustering approach using a new Evidential Label Propagation strategy (SELP) is proposed to incorporate the domain knowledge into the community detection model.  ...  In the task of community detection, there often exists some useful prior information.  ...  The original LPA [5] and the semi-supervised community detection approach SLP [4] were used to compare.  ... 
doi:10.1007/978-3-319-45559-4_13 fatcat:h5anknz62rfvnnc2ftbtjollue
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