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Detecting communities around seed nodes in complex networks

Christian L. Staudt, Yassine Marrakchi, Henning Meyerhenke
2014 2014 IEEE International Conference on Big Data (Big Data)  
The special task of selective community detection is concerned with finding high-quality communities locally around seed nodes.  ...  In particular we evaluate their performance on large complex networks, such as social networks.  ...  Acknowledgements: This work was partially supported by the project Parallel Analysis of Dynamic Networks -Algorithm Engineering of Efficient Combinatorial and Numerical Methods, funded by the Ministry  ... 
doi:10.1109/bigdata.2014.7004373 dblp:conf/bigdataconf/StaudtMM14 fatcat:c4kawewptrf6tlbebidd5zlzqm

YASCA: A collective intelligence approach for community detection in complex networks [article]

Rushed Kanawati
2014 arXiv   pre-print
In this paper we present an original approach for community detection in complex networks. The approach belongs to the family of seed-centric algorithms.  ...  However, instead of expanding communities around selected seeds as most of existing approaches do, we explore here applying an ensemble clustering approach to different network partitions derived from  ...  The basic idea of seed centric algorithms is to select a set of nodes (i.e. seeds) around which communities are constructed.  ... 
arXiv:1401.4472v1 fatcat:ivnivgtzazcgpfyfm3vgfwfmtu

HoSIM: Higher-order Structural Importance based Method for Multiple Local Community Detection [article]

Boyu Li, Meng Wang, John E. Hopcroft, Kun He
2022 arXiv   pre-print
However, nodes may belong to several communities in the network, and detecting all the communities for the query node set, termed as the multiple local community detection (MLCD), is more important as  ...  Accordingly, detecting multiple communities for such nodes by applying seed expansion methods is insufficient. In this work, we address the MLCD based on higher-order structural importance (HoSI).  ...  However, nodes may belong to multiple communities in the network, and detecting all communities for the query node set, termed as multiple local community detection (MLCD) [4] , [5] , [6] , is more  ... 
arXiv:2205.11812v1 fatcat:grjvkykouzfdzeb4nmhzhiekg4

A Local Extended Algorithm Combined with Degree and Clustering Coefficient to Optimize Overlapping Community Detection

Jing Liu, Junfang Guo, Qi Li, Siew Ann Cheong
2021 Complexity  
Community structure is one of the most important characteristics of complex networks, which has important applications in sociology, biology, and computer science.  ...  The community detection method based on local expansion is one of the most adaptable overlapping community detection algorithms.  ...  Seed Node Selection. In the existing overlapping community detection methods based on local expansion, the selection of seed nodes is random.  ... 
doi:10.1155/2021/7428927 fatcat:6igchjxnezgydho4jlgqzbegm4

A propagation-based seed-centric local community detection for multilayer environment: The case study of colon adenocarcinoma

Ehsan Pournoor, Zaynab Mousavian, Abbas Nowzari-Dalini, Ali Masoudi-Nejad, Leto Peel
2021 PLoS ONE  
Regardless of all efforts on community discovery algorithms, it is still an open and challenging subject in network science.  ...  Recognizing communities in a multilayer network, where there are several layers (types) of connections, is even more complicated.  ...  ,l k }, indicating different types of interactions (undirected networks), a local community around the seed node s is defined as a set of nodes having a considerable extent of information streamed from  ... 
doi:10.1371/journal.pone.0255718 pmid:34370784 pmcid:PMC8351981 fatcat:4bwkvgixvjdh3evcityzkipzea

Detecting Community Structure in Dynamic Social Networks Using the Concept of Leadership [chapter]

Saeed Haji Seyed Javadi, Pedram Gharani, Shahram Khadivi
2018 Studies in Systems, Decision and Control  
Detecting community structure in social networks is a fundamental problem empowering us to identify groups of actors with similar interests.  ...  In this paper, we devised an efficient method to incrementally detect communities in highly dynamic social networks using the intuitive idea of importance and persistence of community leaders over time  ...  Most of the seed-centric community detection solutions are sensitive to the position of initial source nodes. As forming local cluster around a low degree node usually results in poor quality.  ... 
doi:10.1007/978-3-319-74412-4_7 fatcat:xsrdajc7ezdardpaycgflkxfty

Local community detection based on network motifs

Yunlei Zhang, Bin Wu, Yu Liu, Jinna Lv
2019 Tsinghua Science and Technology  
Local community detection aims to find a cluster of nodes by exploring a small region of the network.  ...  In this paper, we develop a new Local Community Detection method based on network Motif (LCD-Motif) which incorporates the higher-order network information.  ...  In practice, the remaining members in the target community are more likely to be around the seed members.  ... 
doi:10.26599/tst.2018.9010106 fatcat:aot32ypqtzg6tgp6mkoecvh2vq

Streaming Local Community Detection through Approximate Conductance [article]

Yanhao Yang, Meng Wang, David Bindel, Kun He
2021 arXiv   pre-print
Community is a universal structure in various complex networks, and community detection is a fundamental task for network analysis.  ...  In this work, we consider the problem of uncovering the local community containing a few query nodes in graph streams, termed streaming local community detection.  ...  Considering that nodes within the same community are closely connected, we adopt seed-set expansion strategy using the query nodes in T as the seed-set.  ... 
arXiv:2110.14972v1 fatcat:7jwtd7ilczdo7cp4he4uryauy4

Parallel seed selection method for overlapping community detection in social network

Belfin R V, Grace Mary Kanaga E
2018 Scalable Computing : Practice and Experience  
The algorithm in parallel finds out the superior seed set in the network and expands it in parallel to find out the community.  ...  Earlier, the investigation was in finding out algorithms to detect communities in the network sequentially. There are many distinguished findings toward overlapping community detection.  ...  Secondly, the selection of seed nodes will be done and the local communities will be centered around these seeds.  ... 
doi:10.12694/scpe.v19i4.1429 fatcat:zevumh6txve5fgrzl7www7gezq

Multiple Local Community Detection via High-Quality Seed Identification over Both Static and Dynamic Networks

Jiaxu Liu, Yingxia Shao, Sen Su
2021 Data Science and Engineering  
In this paper, we first introduce a novel algorithm, HqsMLCD, that can detect multiple communities for a given seed node over static networks.  ...  AbstractLocal community detection aims to find the communities that a given seed node belongs to.  ...  The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material.  ... 
doi:10.1007/s41019-021-00160-6 fatcat:6drxrrmgcvb6tltyrrfyjnyqmy

Sparse Nonnegative Matrix Factorization for Multiple Local Community Detection [article]

Dany Kamuhanda, Meng Wang, Kun He
2020 arXiv   pre-print
Local community detection consists of finding a group of nodes closely related to the seeds, a small set of nodes of interest.  ...  Existing local community detection methods focus on finding either one local community that all seeds are most likely to be in or finding a single community for each of the seeds.  ...  We start with a seed s (node 46), sampling nodes around s, then estimate the number of communities in the sampled subgraph and detect each of them based on the learned structure.  ... 
arXiv:2001.06951v2 fatcat:wdk34fbz5bhpxmgfzep6jty2jm

Overlapping Community Detection Based on Node Importance and Adjacency Information

Ping Wang, Yonghong Huang, Fei Tang, Hongtao Liu, Yangyang Lu, Jian Su
2021 Security and Communication Networks  
Detecting the community structure and predicting the change of community structure is an important research topic in social network research.  ...  The experimental results show that our algorithm is feasible and capable of discovering overlapping communities in complex social network efficiently.  ...  Acknowledgments is work was supported in part by the National Natural Science Foundation of China (nos. 61 772 096, 61 876 201, and 61 876 027) and in part by the National Natural Science Foundation of  ... 
doi:10.1155/2021/8690662 fatcat:ob27mlvcu5bdxhnszpgocfqdmi

Sink Node Elimination to Enhance the Performance of Overlapping Detection Algorithms along with Comparison of Existing Algorithm

Er. Rohit Kumar, Er. Harpreet Arora
2017 Indian Journal of Science and Technology  
The proposed algorithm (MKC) does eliminate these nodes and hence consider only those nodes which are connected in nature. To detect the Sink nodes adjacency matrix is used.  ...  Objectives: To eliminate Sink nodes so that rate of detection can improve within the community overlapping detection and this also increases the modularity. It also consumes less time.  ...  for detection of overlapping community. 3 Complexity of the network greatly depends upon the factor that graph is strongly connected or node.  ... 
doi:10.17485/ijst/2017/v10i19/113208 fatcat:5ddj7y4ppvae7nlqosqsuz5oaa

Fast Multi-Scale Community Detection based on Local Criteria within a Multi-Threaded Algorithm [article]

Erwan Le Martelot, Chris Hankin
2013 arXiv   pre-print
Yet this detection is a complex task and a large amount of work was dedicated to it in the past decade.  ...  Many systems can be described using graphs, or networks. Detecting communities in these networks can provide information about the underlying structure and functioning of the original systems.  ...  Complexity Analysis: The seeds initialisation run in O(n · d) where n is the number of nodes and d the average degree of a node. Using the second seed rule it runs in O(n · d 2 ).  ... 
arXiv:1301.0955v2 fatcat:kxyxm6pjdnfcbby7yrr5goreom

Research on Community Center-metric and Community Detection Algorithm for Complex Networks

Gui-shan WANG, Xue-Zao REN, Xue-ying LIU
2019 DEStech Transactions on Computer Science and Engineering  
To resolved the present-existing problem that local community detection is great sensitive to the initial node position in large-scale network, a new community detection algorithm CCMA (Community Central  ...  Experiments on existing real networks and artificial networks show that our community central metric algorithm can detect local community structures more efficiently and accurately by comparing the method  ...  And starting from different seed nodes, local communities may be explored in the sub-network where the seed resides.  ... 
doi:10.12783/dtcse/ammso2019/30107 fatcat:kldwyujm25dm3knbll6s4musji
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