{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T06:17:39Z","timestamp":1772000259245,"version":"3.50.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T00:00:00Z","timestamp":1667952000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T00:00:00Z","timestamp":1667952000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci. China Inf. Sci."],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1007\/s11432-021-3370-4","type":"journal-article","created":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T12:03:01Z","timestamp":1668427381000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Cluster-preserving sampling algorithm for large-scale graphs"],"prefix":"10.1007","volume":"66","author":[{"given":"Jianpeng","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongchang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dingjiu","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yulong","family":"Pei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingjun","family":"Deng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,9]]},"reference":[{"key":"3370_CR1","doi-asserted-by":"crossref","unstructured":"Rozemberczki B, Kiss O, Sarkar R. Little ball of fur: a python library for graph sampling. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management (CIKM), 2020","DOI":"10.1145\/3340531.3412758"},{"key":"3370_CR2","doi-asserted-by":"publisher","first-page":"1333","DOI":"10.1109\/TKDE.2019.2904682","volume":"32","author":"J P Zhang","year":"2020","unstructured":"Zhang J P, Pei Y L, Fletcher G, et al. Evaluation of the sample clustering process on graphs. IEEE Trans Knowl Data Eng, 2020, 32: 1333\u20131347","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3370_CR3","doi-asserted-by":"crossref","unstructured":"Leskovec J, Faloutsos C. Sampling from large graphs. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006. 631\u2013636","DOI":"10.1145\/1150402.1150479"},{"key":"3370_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2601438","volume":"8","author":"N K Ahmed","year":"2014","unstructured":"Ahmed N K, Neville J, Kompella R. Network sampling: from static to streaming graphs. ACM Trans Knowl Discov Data, 2014, 8: 1\u201356","journal-title":"ACM Trans Knowl Discov Data"},{"key":"3370_CR5","doi-asserted-by":"crossref","unstructured":"Zhang J P, Pei Y L, Fletcher G H, et al. Structural measures of clustering quality on graph samples. In: Proceedings of IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining, 2016. 345\u2013348","DOI":"10.1109\/ASONAM.2016.7752256"},{"key":"3370_CR6","doi-asserted-by":"crossref","unstructured":"H\u00fcbler C, Kriegel H P, Borgwardt K, et al. Metropolis algorithms for representative subgraph sampling. In: Proceedings of the 8th IEEE International Conference on Data Mining, 2008. 283\u2013292","DOI":"10.1109\/ICDM.2008.124"},{"key":"3370_CR7","doi-asserted-by":"crossref","unstructured":"Maiya A S, Berger-Wolf T Y. Sampling community structure. In: Proceedings of the 19th International Conference on World Wide Web, 2010. 701\u2013710","DOI":"10.1145\/1772690.1772762"},{"key":"3370_CR8","doi-asserted-by":"publisher","first-page":"5511","DOI":"10.1109\/TSP.2019.2940129","volume":"67","author":"F Wang","year":"2019","unstructured":"Wang F, Cheung G N, Wang Y C. Low-complexity graph sampling with noise and signal reconstruction via neumann series. IEEE Trans Signal Process, 2019, 67: 5511\u20135526","journal-title":"IEEE Trans Signal Process"},{"key":"3370_CR9","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1016\/j.ins.2018.12.073","volume":"481","author":"B Jiao","year":"2019","unstructured":"Jiao B, Shi J M, Zhang W S, et al. Graph sampling for Internet topologies using normalized Laplacian spectral features. Inf Sci, 2019, 481: 574\u2013603","journal-title":"Inf Sci"},{"key":"3370_CR10","doi-asserted-by":"publisher","first-page":"1709","DOI":"10.1109\/TVCG.2020.3030440","volume":"27","author":"Z G Zhou","year":"2021","unstructured":"Zhou Z G, Shi C, Shen X L, et al. Context-aware sampling of large networks via graph representation learning. IEEE Trans Visual Comput Graph, 2021, 27: 1709\u20131719","journal-title":"IEEE Trans Visual Comput Graph"},{"key":"3370_CR11","doi-asserted-by":"crossref","unstructured":"Hu J, Dai G, Wang Y, et al. Graphsdh: a general graph sampling framework with distribution and hierarchy. In: Proceedings of IEEE High Performance Extreme Computing Conference (HPEC), 2020. 1\u20137","DOI":"10.1109\/HPEC43674.2020.9286173"},{"key":"3370_CR12","doi-asserted-by":"publisher","first-page":"1075","DOI":"10.1007\/s13278-013-0144-6","volume":"3","author":"R Mall","year":"2013","unstructured":"Mall R, Langone R, Suykens J A K. FURS: fast and unique representative subset selection retaining large-scale community structure. Soc Netw Anal Min, 2013, 3: 1075\u20131095","journal-title":"Soc Netw Anal Min"},{"key":"3370_CR13","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1126\/science.286.5439.509","volume":"286","author":"A L Barab\u00e1si","year":"1999","unstructured":"Barab\u00e1si A L, Albert R. Emergence of scaling in random networks. Science, 1999, 286: 509\u2013512","journal-title":"Science"},{"key":"3370_CR14","unstructured":"Khorasgani R R, Chen J, Zaiane O R. Top leaders community detection approach in information networks. In: Proceedings of the 4th SNA-KDD Workshop on Social Network Mining and Analysis, 2010"},{"key":"3370_CR15","doi-asserted-by":"publisher","first-page":"023126","DOI":"10.1063\/1.4712602","volume":"22","author":"M Salehi","year":"2012","unstructured":"Salehi M, Rabiee H R, Rajabi A. Sampling from complex networks with high community structures. Chaos, 2012, 22: 023126","journal-title":"Chaos"},{"key":"3370_CR16","first-page":"1","volume":"2","author":"L Lov\u00e1sz","year":"1993","unstructured":"Lov\u00e1sz L. Random walks on graphs. Comb Paul Erdos Eighty, 1993, 2: 1\u201346","journal-title":"Comb Paul Erdos Eighty"},{"key":"3370_CR17","doi-asserted-by":"publisher","first-page":"046110","DOI":"10.1103\/PhysRevE.78.046110","volume":"78","author":"A Lancichinetti","year":"2008","unstructured":"Lancichinetti A, Fortunato S, Radicchi F. Benchmark graphs for testing community detection algorithms. Phys Rev E, 2008, 78: 046110","journal-title":"Phys Rev E"},{"key":"3370_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2594454","volume":"5","author":"J Yang","year":"2014","unstructured":"Yang J, Leskovec J. Structure and overlaps of ground-truth communities in networks. ACM Trans Intell Syst Technol, 2014, 5: 1\u201335","journal-title":"ACM Trans Intell Syst Technol"},{"key":"3370_CR19","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1007\/s10115-013-0693-z","volume":"42","author":"J Yang","year":"2015","unstructured":"Yang J, Leskovec J. Defining and evaluating network communities based on ground-truth. Knowl Inf Syst, 2015, 42: 181\u2013213","journal-title":"Knowl Inf Syst"},{"key":"3370_CR20","doi-asserted-by":"publisher","first-page":"0159161","DOI":"10.1371\/journal.pone.0159161","volume":"11","author":"S Emmons","year":"2016","unstructured":"Emmons S, Kobourov S, Gallant M, et al. Analysis of network clustering algorithms and cluster quality metrics at scale. PLoS ONE, 2016, 11: 0159161","journal-title":"PLoS ONE"},{"key":"3370_CR21","doi-asserted-by":"publisher","first-page":"1118","DOI":"10.1073\/pnas.0706851105","volume":"105","author":"M Rosvall","year":"2008","unstructured":"Rosvall M, Bergstrom C T. Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci USA, 2008, 105: 1118\u20131123","journal-title":"Proc Natl Acad Sci USA"},{"key":"3370_CR22","doi-asserted-by":"publisher","first-page":"10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","volume":"2008","author":"V D Blondel","year":"2008","unstructured":"Blondel V D, Guillaume J L, Lambiotte R, et al. Fast unfolding of communities in large networks. J Stat Mech, 2008, 2008: 10008","journal-title":"J Stat Mech"},{"key":"3370_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.physrep.2016.09.002","volume":"659","author":"S Fortunato","year":"2016","unstructured":"Fortunato S, Hric D. Community detection in networks: a user guide. Phys Rep, 2016, 659: 1\u201344","journal-title":"Phys Rep"},{"key":"3370_CR24","doi-asserted-by":"publisher","first-page":"8577","DOI":"10.1073\/pnas.0601602103","volume":"103","author":"M E J Newman","year":"2006","unstructured":"Newman M E J. From the cover: modularity and community structure in networks. Proc Natl Acad Sci USA, 2006, 103: 8577\u20138582","journal-title":"Proc Natl Acad Sci USA"},{"key":"3370_CR25","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1145\/990308.990313","volume":"51","author":"R Kannan","year":"2004","unstructured":"Kannan R, Vempala S, Vetta A. On clusterings: good, bad and spectral. J ACM, 2004, 51: 497\u2013515","journal-title":"J ACM"},{"key":"3370_CR26","doi-asserted-by":"publisher","first-page":"062805","DOI":"10.1103\/PhysRevE.90.062805","volume":"90","author":"D Hric","year":"2014","unstructured":"Hric D, Darst R K, Fortunato S. Community detection in networks: structural communities versus ground truth. Phys Rev E, 2014, 90: 062805","journal-title":"Phys Rev E"}],"container-title":["Science China Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-021-3370-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11432-021-3370-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-021-3370-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T01:12:22Z","timestamp":1708650742000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11432-021-3370-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,9]]},"references-count":26,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["3370"],"URL":"https:\/\/doi.org\/10.1007\/s11432-021-3370-4","relation":{},"ISSN":["1674-733X","1869-1919"],"issn-type":[{"value":"1674-733X","type":"print"},{"value":"1869-1919","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,9]]},"assertion":[{"value":"5 February 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 June 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 November 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"112103"}}