{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:39:37Z","timestamp":1740123577227,"version":"3.37.3"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,6,10]],"date-time":"2021-06-10T00:00:00Z","timestamp":1623283200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,6,10]],"date-time":"2021-06-10T00:00:00Z","timestamp":1623283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2022,1]]},"DOI":"10.1007\/s11227-021-03905-2","type":"journal-article","created":{"date-parts":[[2021,6,10]],"date-time":"2021-06-10T20:02:42Z","timestamp":1623355362000},"page":"1458-1478","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Sampling in weighted social networks using a levy flight-based learning automata"],"prefix":"10.1007","volume":"78","author":[{"given":"Saeed","family":"Roohollahi","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9640-498X","authenticated-orcid":false,"given":"Amid","family":"Khatibi Bardsiri","sequence":"additional","affiliation":[]},{"given":"Farshid","family":"Keynia","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,10]]},"reference":[{"key":"3905_CR1","doi-asserted-by":"crossref","unstructured":"Izenman, Julian A (2021) Sampling algorithms for discrete markov random fields and related graphical models. J Am Statist Association, 1\u201358.","DOI":"10.1080\/01621459.2021.1898410"},{"key":"3905_CR2","doi-asserted-by":"crossref","unstructured":"Yousuf, Irfan M, Anwer I, Anwar R. (2021) Empirical characterization of graph sampling algorithms.\u00a0arXiv preprint.","DOI":"10.21203\/rs.3.rs-1710509\/v1"},{"key":"3905_CR3","doi-asserted-by":"crossref","unstructured":"Ghavipour, Mina, Meybodi MR (2021) A dynamic sampling algorithm based on learning automata for stochastic trust networks.\u00a0Knowledge-Based Syst. 212: 106620.","DOI":"10.1016\/j.knosys.2020.106620"},{"key":"3905_CR4","unstructured":"Roohollahi S, Khatibi Bardsiri A, Keynia F (2020) Using an evaluator fixed structure learning automata in sampling of social networks. J AI Data Mining\u00a08(1): 127\u2013148."},{"key":"3905_CR5","doi-asserted-by":"crossref","unstructured":"Hens C, et al (2019) Spatiotemporal signal propagation in complex networks. Nat Phys 1.","DOI":"10.1038\/s41567-018-0409-0"},{"issue":"3","key":"3905_CR6","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1109\/TKDE.2011.254","volume":"25","author":"M Papagelis","year":"2013","unstructured":"Papagelis M, Das G, Koudas N (2013) Sampling online social networks. IEEE Trans Knowl Data Eng 25(3):662\u2013676","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"6","key":"3905_CR7","doi-asserted-by":"publisher","first-page":"1017","DOI":"10.1109\/JSAC.2013.130604","volume":"31","author":"F Murai","year":"2013","unstructured":"Murai F et al (2013) On set size distribution estimation and the characterization of large networks via sampling. IEEE J Sel Areas Commun 31(6):1017\u20131025","journal-title":"IEEE J Sel Areas Commun"},{"key":"3905_CR8","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1007\/978-3-030-10767-3_4","volume-title":"Learning Automata Approach for Social Networks","author":"A Rezvanian","year":"2019","unstructured":"Rezvanian A et al (2019) Social network sampling. Learning Automata Approach for Social Networks. Springer, pp 91\u2013149"},{"issue":"4","key":"3905_CR9","doi-asserted-by":"publisher","first-page":"046135","DOI":"10.1103\/PhysRevE.64.046135","volume":"64","author":"LA Adamic","year":"2001","unstructured":"Adamic LA et al (2001) Search in power-law networks. Phys Rev E 64(4):046135","journal-title":"Phys Rev E"},{"key":"3905_CR10","doi-asserted-by":"publisher","first-page":"1003","DOI":"10.1016\/j.swevo.2018.10.011","volume":"44","author":"R Wang","year":"2019","unstructured":"Wang R et al (2019) Optimising discrete dynamic berth allocations in seaports using a Levy Flight based meta-heuristic. Swarm Evol Comput 44:1003\u20131017","journal-title":"Swarm Evol Comput"},{"issue":"2","key":"3905_CR11","doi-asserted-by":"publisher","first-page":"1473","DOI":"10.1007\/s11042-018-6155-6","volume":"78","author":"Y Pathak","year":"2019","unstructured":"Pathak Y, Arya K, Tiwari S (2019) Feature selection for image steganalysis using levy flight-based grey wolf optimization. Multimedia Tools Appl 78(2):1473\u20131494","journal-title":"Multimedia Tools Appl"},{"key":"3905_CR12","unstructured":"T Niranjan, P Parthiban (2019) Modelling and analysing an integrated multi channel food supply chain distribution of an indian dairy firm using modified TLBO algorithm."},{"key":"3905_CR13","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1016\/j.asoc.2018.11.033","volume":"75","author":"E Emary","year":"2019","unstructured":"Emary E, Zawbaa HM, Sharawi M (2019) Impact of L\u00e8vy flight on modern meta-heuristic optimizers. Appl Soft Comput 75:775\u2013789","journal-title":"Appl Soft Comput"},{"key":"3905_CR14","doi-asserted-by":"crossref","unstructured":"Butt AA, et al (2019) Optimization of response and processing time for smart societies using particle swarm optimization and levy walk. in International Conference on Advanced Information Networking and Applications. Springer.","DOI":"10.1007\/978-3-030-15032-7_2"},{"key":"3905_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-019-00820-4","author":"S Chattopadhyay","year":"2019","unstructured":"Chattopadhyay S, Das AK, Ghosh K (2019) Finding patterns in the degree distribution of real-world complex networks: going beyond power law. Pattern Analy Appl. https:\/\/doi.org\/10.1007\/s10044-019-00820-4","journal-title":"Pattern Analy Appl"},{"key":"3905_CR16","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.physa.2018.08.073","volume":"513","author":"HS Kwong","year":"2019","unstructured":"Kwong HS, Nadarajah S (2019) A note on \u201cPareto tails and lognormal body of US cities size distribution.\u201d Phys A 513:55\u201362","journal-title":"Phys A"},{"issue":"8","key":"3905_CR17","doi-asserted-by":"publisher","first-page":"1650042","DOI":"10.1142\/S0217979216500429","volume":"30","author":"MMD Khomami","year":"2016","unstructured":"Khomami MMD, Rezvanian A, Meybodi MR (2016) Distributed learning automata-based algorithm for community detection in complex networks. Int J Mod Phys B 30(8):1650042","journal-title":"Int J Mod Phys B"},{"issue":"6","key":"3905_CR18","doi-asserted-by":"publisher","first-page":"1095","DOI":"10.1109\/TSMC.1987.6499323","volume":"17","author":"M Thathachar","year":"1987","unstructured":"Thathachar M, Harita BR (1987) Learning automata with changing number of actions. IEEE Trans Syst Man Cybern 17(6):1095\u20131100","journal-title":"IEEE Trans Syst Man Cybern"},{"issue":"1","key":"3905_CR19","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1016\/j.jtbi.2010.11.033","volume":"271","author":"L Isella","year":"2011","unstructured":"Isella L et al (2011) What\u2019s in a crowd? Analysis of face-to-face behavioral networks. J Theor Biol 271(1):166\u2013180","journal-title":"J Theor Biol"},{"issue":"1","key":"3905_CR20","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1145\/1217299.1217301","volume":"1","author":"J Leskovec","year":"2007","unstructured":"Leskovec J, Kleinberg J, Faloutsos C (2007) Graph evolution: densification and shrinking diameters. ACM Transac Knowled Discovery from Data (TKDD) 1(1):2","journal-title":"ACM Transac Knowled Discovery from Data (TKDD)"},{"key":"3905_CR21","first-page":"17","volume":"5","author":"P Erdos","year":"1960","unstructured":"Erdos P (1960) On the evolution of random graphs. Publ Math Institute Hungarian Academy Sci 5:17\u201361","journal-title":"Publ Math Institute Hungarian Academy Sci"},{"key":"3905_CR22","doi-asserted-by":"publisher","DOI":"10.1126\/science.286.5439.509","author":"DJ Watts","year":"1998","unstructured":"Watts DJ, Strogatz SH (1998) Collective dynamics of \u2018small-world\u2019networks. Nature. https:\/\/doi.org\/10.1126\/science.286.5439.509","journal-title":"Nature"},{"issue":"5439","key":"3905_CR23","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1126\/science.286.5439.509","volume":"286","author":"AL Barab\u00e1si","year":"1999","unstructured":"Barab\u00e1si AL, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509\u2013512","journal-title":"Science"},{"key":"3905_CR24","doi-asserted-by":"publisher","first-page":"e3091","DOI":"10.1002\/dac.3091","volume":"30","author":"A Rezvanian","year":"2017","unstructured":"Rezvanian A, Meybodi MR (2017) A new learning automata-based sampling algorithm for social networks. Int J Commun Syst 30:e3091","journal-title":"Int J Commun Syst"},{"key":"3905_CR25","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1016\/j.physa.2015.01.030","volume":"424","author":"A Rezvanian","year":"2015","unstructured":"Rezvanian A, Meybodi MR (2015) Sampling social networks using shortest paths. Phys A 424:254\u2013268","journal-title":"Phys A"},{"key":"3905_CR26","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1016\/j.physa.2013.11.015","volume":"396","author":"A Rezvanian","year":"2014","unstructured":"Rezvanian A, Rahmati M, Meybodi MR (2014) Sampling from complex networks using distributed learning automata. Phys A 396:224\u2013234","journal-title":"Phys A"},{"key":"3905_CR27","doi-asserted-by":"publisher","first-page":"1650052","DOI":"10.1142\/S0129183116500522","volume":"27","author":"ZS Jalali","year":"2016","unstructured":"Jalali ZS, Rezvanian A, Meybodi MR (2016) Social network sampling using spanning trees. Int J Mod Phys C 27:1650052","journal-title":"Int J Mod Phys C"},{"key":"3905_CR28","doi-asserted-by":"publisher","first-page":"046114","DOI":"10.1103\/PhysRevE.75.046114","volume":"75","author":"S Yoon","year":"2007","unstructured":"Yoon S, Lee S, Yook SH, Kim Y (2007) Statistical properties of sampled networks by random walks. Phys Rev E 75:046114","journal-title":"Phys Rev E"},{"key":"3905_CR29","doi-asserted-by":"crossref","unstructured":"Kurant M, Markopoulou A, Thiran P (2010) On the bias of BFS (Breadth First Search), In: 2010 22nd International Teletraffic Congress (ITC), pp. 1\u20138.","DOI":"10.1109\/ITC.2010.5608727"},{"key":"3905_CR30","unstructured":"Frank O (2011) Survey sampling in networks, in: The SAGE Handbook of Social Network Analysis, SAGE publications, pp. 370\u2013388."},{"key":"3905_CR31","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.ins.2015.02.014","volume":"306","author":"S-H Yoon","year":"2015","unstructured":"Yoon S-H, Kim K-N, Hong J, Kim S-W, Park S (2015) A community-based sampling method using DPL for online social networks. Inf Sci 306:53\u201369","journal-title":"Inf Sci"},{"key":"3905_CR32","doi-asserted-by":"publisher","first-page":"1550050","DOI":"10.1142\/S0129183115500503","volume":"26","author":"P Luo","year":"2015","unstructured":"Luo P, Li Y, Wu C, Zhang G (2015) Toward cost-efficient sampling methods. Int J Mod Phys C 26:1550050","journal-title":"Int J Mod Phys C"},{"key":"3905_CR33","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.physa.2015.03.048","volume":"432","author":"N Blagus","year":"2015","unstructured":"Blagus N, \u0160ubelj L, Weiss G, Bajec M (2015) Sampling promotes community structure in social and information networks. Phys A 432:206\u2013215","journal-title":"Phys A"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-021-03905-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-021-03905-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-021-03905-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T17:11:16Z","timestamp":1672420276000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-021-03905-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,10]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,1]]}},"alternative-id":["3905"],"URL":"https:\/\/doi.org\/10.1007\/s11227-021-03905-2","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"type":"print","value":"0920-8542"},{"type":"electronic","value":"1573-0484"}],"subject":[],"published":{"date-parts":[[2021,6,10]]},"assertion":[{"value":"20 May 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 June 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}