Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 6/2022

10.01.2022 | Original Article

Community discovery algorithm of complex network attention model

verfasst von: Jinghong Wang, Haokang Li, Lina Liang, Yi Zhou

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 6/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In terms of understanding the structure of complex networks or the functional characteristics of complex networks, community discovery is of great significance. This paper uses the attention model to combine the second-order neighbor similarity matrix with the modularity matrix, extracts relatively more comprehensive complex network feature information from multiple angles for network division. Firstly, perform complex network preprocessing, and perform division preprocessing according to the value of the attention similarity matrix. Secondly, complete the merger of the community game according to the connection strength between the two different communities. By comparing with other algorithms on computer-generated networks and real-world networks, it is proved that this algorithm has obtained good results in terms of the number of communities, running time, normalized mutual information and modularity.
Vorheriger Artikel Active partial label learning based on adaptive sample selection
Nächster Artikel Incremental sequential three-way decision based on continual learning network

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Weitere Produktempfehlungen anzeigen
Literatur
1.
Luo W, Nannan L, Ni L et al (2020) Local community detection by the nearest nodes with greater centrality. Inform Sci 517:377–392MathSciNetCrossRef
2.
Amagata D, Hara T (2021) Fast density-peaks clustering: multicore-based parallelization approach. Assoc Comput Mach 13:49–61
3.
Abduljabbar DA, Hashim SZM, Sallehuddin R (2020) Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends. Telecommun Syst 74:225–252CrossRef
4.
Moayedikia A (2018) Multi-objective community detection algorithm with node importance analysis in attributed networks. Appl Soft Comput 67:434–451CrossRef
5.
Zhu J, Liu Y, Hao W et al (2020) A no self-edge stochastic block model and a heuristic algorithm for balanced anti-community detection in networks. Inform Sci 518:95–112MathSciNetCrossRef
6.
7.
Vaswani A, Shazeer N, Parmar N et al. (2017) Attention Is All You Need. arXiv
8.
Li Z, Ming L, Bo W et al (2021) Discovering communities based on mention distance. Scientometrics 126(3):1945–1967CrossRef
9.
Wang X, Zhang T, Wang R (2019) Non-iterative deep learning: incorporating restricted Boltzmann machine into multilayer random weight neural networks. IEEE Trans Syst Man Cybernet 49(7):1299–1380CrossRef
10.
Meng X, Dong L, Li Y, Guo WW (2017) A genetic algorithm using K-path initialization for community detection in complex networks. Cluster Comput 20(1):311–320CrossRef
11.
Chen D, Huang X, Wang Y, Wang D (2019) Weighted-group-density based community discovery algorithm for dynamic weighted networks. J Internet Technol 21(5):1545–1552
12.
Li S, Jiang L, Xiaobo W, Han Weihong, Zhao Dawei, Wang Zhen (2021) A weighted network community detection algorithm based on deep learning. Appl Math Comput 401:126012MathSciNetMATH
13.
Wang X, Wang R, Xu C (2018) Discovering the Relationship Between Generalization and Uncertainty by Incorporating Complexity of Classification. IEEE Transactions on Cybernetics, February 48(2):703-715
14.
Li S, Zhao D, Wu X, Tian Z, Li A, Wang Z (2020) Functional immunization of networks based on message passing. Applied Mathematics and Computation 366
15.
Lusseau D, Newman MEJ (2004) Identifying the role that animals play in their social networks, Proceedings of the Royal Society of London Series B-biological Sciences 271:477–481
16.
Saeid A, Taghavi AS, Asgarali B, Babak A (2021) A three-stage algorithm for local community detection based on the high node importance ranking in social networks. Phys A 563:125420MathSciNetCrossRef
17.
Ding X, Zhang J, Yang Jing (2018) A robust two-stage algorithm for local community detection. Knowl-Based Syst 152:188–199CrossRef
18.
Newman MEJ (2004) Fast algorithm for detecting community structure in networks. Phys Rev E 69(6):066133CrossRef
19.
Zhang W, Kong F, Yang L, Chen Yunfang, Zhang Mengyuan (2018) Hierarchical Community Detection Based on Partial Matrix Convergence Using Random Walks. Tsinghua Sci Technol 23(01):35–46CrossRef
20.
Newman MEJ, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69(2):026113CrossRef
21.
Yuan C, Rong C, Yao Qingshuang (2020) Boundary-connection deletion strategy based method for community detection in complex networks. Appl Intell 50(11):3570–3589CrossRef
22.
Wang P, BaoWen X, YuRong W, Zhou XiaoYu (2015) Link prediction in social networks: the state-of-the-art. Sci China Inform Sci 58:1–38
23.
Traag VA, Waltman L, van Eck NJ (2019) From Louvain to Leiden: guaranteeing well-connected communities. Springer Science and Business Media LLC Mar 9:2045-2322
24.
Chang B, Tong X, Liu Q, Chen E-H (2018) Study on information diffusion analysis in social networks and its applications. Int J Auto Comput 15(04):377–401CrossRef
25.
Qin Y, Zhengtao Y, Wang Y, Gao Shengxiang, Shi Linbin (2017) Detecting micro-blog user interest communities through the integration of explicit user relationship and implicit topic relations. Sci China (Information Sciences) 60(09):64–77
26.
Chen Y, Xiaoliang H, Fan W, Shen L, Zhang Zheng, Liu Xin, Jixiang Du, Li Haibo, Chen Yi, Li Hailin (2020) Fast density peak clustering for large scale data based on kNN. Knowl-Based Syst 187:104824CrossRef
27.
Dong Z, Wang S, Liu Qun (2020) Spectral based hypothesis testing for community detection in complex networks. Inform Sci 512:1360–1371MathSciNetCrossRef
28.
Yang H, Cheng J, Yang Z, Zhang H et al (2021) A Node Similarity and Community Link Strength-Based Community Discovery Algorithm. Complexity
29.
Zachary WW (1977) An information flow model for conflict and fission in small groups. J Anthropol Res 33:452–473CrossRef
30.
Lusseau D, Schneider K, Boisseau OJ, Haase P, Slooten E, Dawson SM (2003) The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations. Behav Ecol Sociobiol 54:396–405CrossRef
31.
Gavin M, Newman MEJ (2002) Community structure in social and biological networks. Proc Natl Acad Sci 99(12):7821–7826MathSciNetCrossRef
32.
Newman MEJ (2006) Modularity and community structure in networks. Proc Natl Acad Sci 103:8577–8582CrossRef
33.
Wang J, Yang J (2020) Yichao He (2020) Research on semisupervised community discovery algorithm based on new annealing. J Eng 12:1149–1154CrossRef
34.
Rossi RA, Ahmed NK (2015) The network data repository with interactive graph analytics and visualization. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence
35.
Newman MEJ (2006) Finding community structure in networks using the eigenvectors of matrices. Phys Rev E 74:036104MathSciNetCrossRef
Metadaten
Titel
Community discovery algorithm of complex network attention model
verfasst von
Jinghong Wang
Haokang Li
Lina Liang
Yi Zhou
Publikationsdatum
10.01.2022
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 6/2022
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-021-01471-w

Weitere Artikel der Ausgabe 6/2022

International Journal of Machine Learning and Cybernetics 6/2022 Zur Ausgabe

Original Article

Active partial label learning based on adaptive sample selection

Original Article

Deconfounded classification by an intervention approach

Original Article

The Interval probabilistic double hierarchy linguistic EDAS method based on natural language processing basic techniques and its application to hotel online reviews

Original Article

Relative measure-based approaches for ranking single-valued neutrosophic values and their applications

Original Article

Feature extraction and classification algorithm, which one is more essential? An experimental study on a specific task of vibration signal diagnosis

Original Article

Multi-granulation Multi-scale Relation Network for Abstract Reasoning