IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v396y2014icp224-234.html
   My bibliography  Save this article

Sampling from complex networks using distributed learning automata

Author

Listed:
  • Rezvanian, Alireza
  • Rahmati, Mohammad
  • Meybodi, Mohammad Reza

Abstract

A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

Suggested Citation

  • Rezvanian, Alireza & Rahmati, Mohammad & Meybodi, Mohammad Reza, 2014. "Sampling from complex networks using distributed learning automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 224-234.
    • Handle: RePEc:eee:phsmap:v:396:y:2014:i:c:p:224-234
    DOI: 10.1016/j.physa.2013.11.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437113010571
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2013.11.015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. M. Goldstein & S. Morris & G. Yen, 2004. "Problems with fitting to the power-law distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 41(2), pages 255-258, September.
    2. James Ma & Daniel Zeng & Huimin Zhao, 2012. "Modeling the growth of complex software function dependency networks," Information Systems Frontiers, Springer, vol. 14(2), pages 301-315, April.
    3. Zhang, Guidong & Li, Zhong & Zhang, Bo & Halang, Wolfgang A., 2013. "Understanding the cascading failures in Indian power grids with complex networks theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3273-3280.
    4. Tang, Jinjun & Wang, Yinhai & Liu, Fang, 2013. "Characterizing traffic time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4192-4201.
    5. Ibrahim Sorkhoh & Khaled A. Mahdi & Maytham Safar, 2013. "Estimation algorithm for counting periodic orbits in complex social networks," Information Systems Frontiers, Springer, vol. 15(2), pages 193-202, April.
    6. Hu, Sen & Yang, Hualei & Cai, Boliang & Yang, Chunxia, 2013. "Research on spatial economic structure for different economic sectors from a perspective of a complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3682-3697.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huang, Yubo & Dong, Hongli & Zhang, Weidong & Lu, Junguo, 2019. "Stability analysis of nonlinear oscillator networks based on the mechanism of cascading failures," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 5-15.
    2. Rezvanian, Alireza & Meybodi, Mohammad Reza, 2015. "Sampling social networks using shortest paths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 254-268.
    3. Zeinab Shariat & Ali Movaghar & Mehdi Hoseinzadeh, 2017. "A learning automata and clustering-based routing protocol for named data networking," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 65(1), pages 9-29, May.
    4. Liu, Nairong & An, Haizhong & Gao, Xiangyun & Li, Huajiao & Hao, Xiaoqing, 2016. "Breaking news dissemination in the media via propagation behavior based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 44-54.
    5. Moradabadi, Behnaz & Meybodi, Mohammad Reza, 2017. "A novel time series link prediction method: Learning automata approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 422-432.
    6. Moradabadi, Behnaz & Meybodi, Mohammad Reza, 2016. "Link prediction based on temporal similarity metrics using continuous action set learning automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 361-373.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mary Han & Bill McKelvey, 2016. "How to Grow Successful Social Entrepreneurship Firms? Key Ideas from Complexity Theory," Journal of Enterprising Culture (JEC), World Scientific Publishing Co. Pte. Ltd., vol. 24(03), pages 243-280, September.
    2. Fenner, Trevor & Levene, Mark & Loizou, George, 2010. "Predicting the long tail of book sales: Unearthing the power-law exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2416-2421.
    3. Rezvanian, Alireza & Meybodi, Mohammad Reza, 2015. "Sampling social networks using shortest paths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 254-268.
    4. Rafael González-Val, 2012. "A Nonparametric Estimation of the Local Zipf Exponent for all US Cities," Environment and Planning B, , vol. 39(6), pages 1119-1130, December.
    5. Rafael González-Val, 2021. "The Probability Distribution of Worldwide Forest Areas," Sustainability, MDPI, vol. 13(3), pages 1-19, January.
    6. Rafael González‐Val, 2019. "Historical urban growth in Europe (1300–1800)," Papers in Regional Science, Wiley Blackwell, vol. 98(2), pages 1115-1136, April.
    7. Marcus Berliant & Hiroki Watanabe, 2015. "Explaining the size distribution of cities: Extreme economies," Quantitative Economics, Econometric Society, vol. 6(1), pages 153-187, March.
    8. Klabunde, Anna, 2014. "Computational Economic Modeling of Migration," Ruhr Economic Papers 471, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    9. Fenner, Trevor & Levene, Mark & Loizou, George, 2005. "A stochastic evolutionary model exhibiting power-law behaviour with an exponential cutoff," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(2), pages 641-656.
    10. Behfar, Stefan Kambiz & Turkina, Ekaterina & Cohendet, Patrick & Burger-Helmchen, Thierry, 2016. "Directed networks’ different link formation mechanisms causing degree distribution distinction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 479-491.
    11. Yichi Zhang & Zhiliang Dong & Sen Liu & Peixiang Jiang & Cuizhi Zhang & Chao Ding, 2021. "Forecast of International Trade of Lithium Carbonate Products in Importing Countries and Small-Scale Exporting Countries," Sustainability, MDPI, vol. 13(3), pages 1-23, January.
    12. Peltonen, Tuomas A. & Scheicher, Martin & Vuillemey, Guillaume, 2014. "The network structure of the CDS market and its determinants," Journal of Financial Stability, Elsevier, vol. 13(C), pages 118-133.
    13. Mike, Szabolcs & Farmer, J. Doyne, 2008. "An empirical behavioral model of liquidity and volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 200-234, January.
    14. Politi, Mauro & Scalas, Enrico, 2008. "Fitting the empirical distribution of intertrade durations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2025-2034.
    15. Fan Jiang & Niancai Liu, 2018. "The hierarchical status of international academic awards in social sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 2091-2115, December.
    16. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    17. Davide Provenzano, 2014. "Power laws and the market structure of tourism industry," Empirical Economics, Springer, vol. 47(3), pages 1055-1066, November.
    18. Aaron Clauset & Maxwell Young & Kristian Skrede Gleditsch, 2007. "On the Frequency of Severe Terrorist Events," Journal of Conflict Resolution, Peace Science Society (International), vol. 51(1), pages 58-87, February.
    19. Tian, Hu & Zheng, Xiaolong & Zeng, Daniel Danjun, 2019. "Analyzing the dynamic sectoral influence in Chinese and American stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    20. Morales, R.V. & da Cunha, C.R. & Rambo, C.R., 2014. "A complex network approach for the growth of aerogels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 131-138.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:396:y:2014:i:c:p:224-234. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.