{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T14:16:12Z","timestamp":1783606572633,"version":"3.55.0"},"reference-count":69,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"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":["Cluster Comput"],"published-print":{"date-parts":[[2022,4]]},"DOI":"10.1007\/s10586-021-03430-0","type":"journal-article","created":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T08:02:58Z","timestamp":1637136178000},"page":"869-888","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":90,"title":["A novel method of spectral clustering in attributed networks by constructing parameter-free affinity matrix"],"prefix":"10.1007","volume":"25","author":[{"given":"Kamal","family":"Berahmand","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mehrnoush","family":"Mohammadi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Azadeh","family":"Faroughi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2998-1562","authenticated-orcid":false,"given":"Rojiar Pir","family":"Mohammadiani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,11,17]]},"reference":[{"issue":"7043","key":"3430_CR1","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1038\/nature03607","volume":"435","author":"G Palla","year":"2005","unstructured":"Palla, G., et al.: Uncovering the overlapping community structure of complex networks in nature and society. Nature 435(7043), 814\u2013818 (2005)","journal-title":"Nature"},{"issue":"4","key":"3430_CR2","first-page":"041042","volume":"10","author":"X Wang","year":"2020","unstructured":"Wang, X., et al.: Public discourse and social network echo chambers driven by socio-cognitive biases. Phys. Rev. X 10(4), 041042 (2020)","journal-title":"Phys. Rev. X"},{"issue":"1","key":"3430_CR3","doi-asserted-by":"publisher","first-page":"013019","DOI":"10.1088\/1367-2630\/ab623c","volume":"22","author":"L Liu","year":"2020","unstructured":"Liu, L., et al.: Homogeneity trend on social networks changes evolutionary advantage in competitive information diffusion. N. J. Phys. 22(1), 013019 (2020)","journal-title":"N. J. Phys."},{"issue":"3\u20135","key":"3430_CR4","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.physrep.2009.11.002","volume":"486","author":"S Fortunato","year":"2010","unstructured":"Fortunato, S.: Community detection in graphs. Phys. Rep. 486(3\u20135), 75\u2013174 (2010)","journal-title":"Phys. Rep."},{"key":"3430_CR5","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1016\/j.future.2017.08.014","volume":"87","author":"J Cai","year":"2018","unstructured":"Cai, J., et al.: Enhancing network capacity by weakening community structure in scale-free network. Futur. Gener. Comput. Syst. 87, 765\u2013771 (2018)","journal-title":"Futur. Gener. Comput. Syst."},{"issue":"4","key":"3430_CR6","doi-asserted-by":"publisher","first-page":"1021","DOI":"10.1109\/TCSS.2018.2879494","volume":"5","author":"K Berahmand","year":"2018","unstructured":"Berahmand, K., Bouyer, A., Vasighi, M.: Community detection in complex networks by detecting and expanding core nodes through extended local similarity of nodes. IEEE Trans. Comput. Soc. Syst. 5(4), 1021\u20131033 (2018)","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"issue":"4","key":"3430_CR7","doi-asserted-by":"publisher","first-page":"042822","DOI":"10.1103\/PhysRevE.88.042822","volume":"88","author":"ME Newman","year":"2013","unstructured":"Newman, M.E.: Spectral methods for community detection and graph partitioning. Phys. Rev. E 88(4), 042822 (2013)","journal-title":"Phys. Rev. E"},{"issue":"24","key":"3430_CR8","doi-asserted-by":"publisher","first-page":"9634","DOI":"10.1016\/j.eswa.2015.07.023","volume":"42","author":"L Zhou","year":"2015","unstructured":"Zhou, L., et al.: An approach for overlapping and hierarchical community detection in social networks based on coalition formation game theory. Expert Syst. Appl. 42(24), 9634\u20139646 (2015)","journal-title":"Expert Syst. Appl."},{"key":"3430_CR9","doi-asserted-by":"crossref","unstructured":"G\u00fcnnemann, S., Boden, B., Seidl, T.: DB-CSC: a density-based approach for subspace clustering in graphs with feature vectors. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, New York (2011)","DOI":"10.1007\/978-3-642-23780-5_46"},{"key":"3430_CR10","doi-asserted-by":"publisher","first-page":"100286","DOI":"10.1016\/j.cosrev.2020.100286","volume":"37","author":"P Chunaev","year":"2020","unstructured":"Chunaev, P.: Community detection in node-attributed social networks: a survey. Comput. Sci. Rev. 37, 100286 (2020)","journal-title":"Comput. Sci. Rev."},{"key":"3430_CR11","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1017\/nws.2015.9","volume":"3","author":"C Bothorel","year":"2015","unstructured":"Bothorel, C., et al.: Clustering attributed graphs: models, measures and methods. Netw. Sci. 3, 408\u2013444 (2015)","journal-title":"Netw. Sci."},{"key":"3430_CR12","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Cheng, H., Yu, J.X.: Clustering large attributed graphs: an efficient incremental approach. In: 2010 IEEE International Conference on Data Mining. IEEE (2010)","DOI":"10.1109\/ICDM.2010.41"},{"key":"3430_CR13","doi-asserted-by":"crossref","unstructured":"White, S., Smyth, P.: A spectral clustering approach to finding communities in graphs. In: Proceedings of the 2005 SIAM international conference on data mining. SIAM (2005)","DOI":"10.1137\/1.9781611972757.25"},{"issue":"1","key":"3430_CR14","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1016\/j.physa.2006.07.023","volume":"374","author":"S Zhang","year":"2007","unstructured":"Zhang, S., Wang, R.-S., Zhang, X.-S.: Identification of overlapping community structure in complex networks using fuzzy c-means clustering. Physica A 374(1), 483\u2013490 (2007)","journal-title":"Physica A"},{"key":"3430_CR15","unstructured":"Peng, R., Sun, H., Zanetti, L.: Partitioning well-clustered graphs: spectral clustering works! In: Conference on learning theory. PMLR (2015)"},{"issue":"2","key":"3430_CR16","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/j.ejor.2010.08.012","volume":"211","author":"MC Nascimento","year":"2011","unstructured":"Nascimento, M.C., De Carvalho, A.C.: Spectral methods for graph clustering\u2013a survey. Eur. J. Oper. Res. 211(2), 221\u2013231 (2011)","journal-title":"Eur. J. Oper. Res."},{"issue":"3","key":"3430_CR17","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1214\/08-STS266","volume":"23","author":"Z Zhang","year":"2008","unstructured":"Zhang, Z., Jordan, M.I.: Multiway spectral clustering: a margin-based perspective. Stat. Sci. 23(3), 383\u2013403 (2008)","journal-title":"Stat. Sci."},{"key":"3430_CR18","doi-asserted-by":"crossref","unstructured":"Zass, R., Shashua, A.: A unifying approach to hard and probabilistic clustering. In: Tenth IEEE International Conference on Computer Vision (ICCV'05) vol. 1. IEEE (2005)","DOI":"10.1109\/ICCV.2005.27"},{"issue":"13\u201315","key":"3430_CR19","doi-asserted-by":"publisher","first-page":"3203","DOI":"10.1016\/j.neucom.2009.03.012","volume":"72","author":"T Xia","year":"2009","unstructured":"Xia, T., et al.: On defining affinity graph for spectral clustering through ranking on manifolds. Neurocomputing 72(13\u201315), 3203\u20133211 (2009)","journal-title":"Neurocomputing"},{"issue":"5","key":"3430_CR20","doi-asserted-by":"publisher","first-page":"056114","DOI":"10.1103\/PhysRevE.80.056114","volume":"80","author":"S Chauhan","year":"2009","unstructured":"Chauhan, S., Girvan, M., Ott, E.: Spectral properties of networks with community structure. Phys. Rev. E 80(5), 056114 (2009)","journal-title":"Phys. Rev. E"},{"issue":"11","key":"3430_CR21","doi-asserted-by":"publisher","first-page":"114102","DOI":"10.1103\/PhysRevLett.96.114102","volume":"96","author":"A Arenas","year":"2006","unstructured":"Arenas, A., Diaz-Guilera, A., P\u00e9rez-Vicente, C.J.: Synchronization reveals topological scales in complex networks. Phys. Rev. Lett. 96(11), 114102 (2006)","journal-title":"Phys. Rev. Lett."},{"issue":"04","key":"3430_CR22","doi-asserted-by":"publisher","first-page":"P04024","DOI":"10.1088\/1742-5468\/2010\/04\/P04024","volume":"2010","author":"X-Q Cheng","year":"2010","unstructured":"Cheng, X.-Q., Shen, H.-W.: Uncovering the community structure associated with the diffusion dynamics on networks. J. Stat. Mech. Theory Exp. 2010(04), P04024 (2010)","journal-title":"J. Stat. Mech. Theory Exp."},{"issue":"23","key":"3430_CR23","doi-asserted-by":"publisher","first-page":"8577","DOI":"10.1073\/pnas.0601602103","volume":"103","author":"ME Newman","year":"2006","unstructured":"Newman, M.E.: Modularity and community structure in networks. Proc. Natl. Acad. Sci. 103(23), 8577\u20138582 (2006)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"1","key":"3430_CR24","doi-asserted-by":"publisher","first-page":"016114","DOI":"10.1103\/PhysRevE.82.016114","volume":"82","author":"H-W Shen","year":"2010","unstructured":"Shen, H.-W., Cheng, X.-Q., Fang, B.-X.: Covariance, correlation matrix, and the multiscale community structure of networks. Phys. Rev. E 82(1), 016114 (2010)","journal-title":"Phys. Rev. E"},{"issue":"3","key":"3430_CR25","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1007\/s11704-011-0023-0","volume":"5","author":"X Zhang","year":"2011","unstructured":"Zhang, X., You, Q.: An improved spectral clustering algorithm based on random walk. Frontiers of Computer Science in China 5(3), 268 (2011)","journal-title":"Frontiers of Computer Science in China"},{"key":"3430_CR26","first-page":"1","volume":"8","author":"S Ren","year":"2020","unstructured":"Ren, S., Zhang, S., Wu, T.: An improved spectral clustering community detection algorithm based on probability matrix. Discret. Dyn. Nat. Soc. 8, 1\u20136 (2020)","journal-title":"Discret. Dyn. Nat. Soc."},{"key":"3430_CR27","doi-asserted-by":"publisher","first-page":"123633","DOI":"10.1016\/j.physa.2019.123633","volume":"545","author":"F Hu","year":"2020","unstructured":"Hu, F., et al.: Community detection in complex networks using Node2vec with spectral clustering. Physica A 545, 123633 (2020)","journal-title":"Physica A"},{"key":"3430_CR28","doi-asserted-by":"publisher","unstructured":"Wang, Z., et al., A community detection algorithm based on topology potential and spectral clustering. Sci. World J. (2014). https:\/\/doi.org\/10.1155\/2014\/329325","DOI":"10.1155\/2014\/329325"},{"issue":"3","key":"3430_CR29","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1109\/TKDE.2015.2496345","volume":"28","author":"A Mahmood","year":"2015","unstructured":"Mahmood, A., Small, M.: Subspace based network community detection using sparse linear coding. IEEE Trans. Knowl. Data Eng. 28(3), 801\u2013812 (2015)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"5","key":"3430_CR30","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1016\/j.patrec.2009.11.001","volume":"31","author":"K Steinhaeuser","year":"2010","unstructured":"Steinhaeuser, K., Chawla, N.V.: Identifying and evaluating community structure in complex networks. Pattern Recogn. Lett. 31(5), 413\u2013421 (2010)","journal-title":"Pattern Recogn. Lett."},{"issue":"4","key":"3430_CR31","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1007\/s10619-014-7170-x","volume":"33","author":"W Nawaz","year":"2015","unstructured":"Nawaz, W., et al.: Intra graph clustering using collaborative similarity measure. Distrib. Parallel Datab. 33(4), 583\u2013603 (2015)","journal-title":"Distrib. Parallel Datab."},{"key":"3430_CR32","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1016\/j.physa.2016.11.015","volume":"469","author":"H Zhou","year":"2017","unstructured":"Zhou, H., et al.: A graph clustering method for community detection in complex networks. Physica A 469, 551\u2013562 (2017)","journal-title":"Physica A"},{"key":"3430_CR33","doi-asserted-by":"publisher","first-page":"125459","DOI":"10.1016\/j.physa.2020.125459","volume":"563","author":"S Agrawal","year":"2021","unstructured":"Agrawal, S., Patel, A.: SAG Cluster: An unsupervised graph clustering based on collaborative similarity for community detection in complex networks. Physica A 563, 125459 (2021)","journal-title":"Physica A"},{"issue":"10","key":"3430_CR34","doi-asserted-by":"publisher","first-page":"1067","DOI":"10.1080\/00029890.1974.11993738","volume":"81","author":"R Ayoub","year":"1974","unstructured":"Ayoub, R.: Euler and the zeta function. Am. Math. Mon. 81(10), 1067\u20131086 (1974)","journal-title":"Am. Math. Mon."},{"key":"3430_CR35","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1016\/j.future.2017.08.028","volume":"79","author":"W Li","year":"2018","unstructured":"Li, W., Jiang, S., Jin, Q.: Overlap community detection using spectral algorithm based on node convergence degree. Futur. Gener. Comput. Syst. 79, 408\u2013416 (2018)","journal-title":"Futur. Gener. Comput. Syst."},{"issue":"8","key":"3430_CR36","doi-asserted-by":"publisher","first-page":"3203","DOI":"10.1007\/s00521-019-04064-5","volume":"32","author":"E Alinezhad","year":"2020","unstructured":"Alinezhad, E., et al.: Community detection in attributed networks considering both structural and attribute similarities: two mathematical programming approaches. Neural Comput. Appl. 32(8), 3203\u20133220 (2020)","journal-title":"Neural Comput. Appl."},{"issue":"1","key":"3430_CR37","doi-asserted-by":"publisher","first-page":"718","DOI":"10.14778\/1687627.1687709","volume":"2","author":"Y Zhou","year":"2009","unstructured":"Zhou, Y., Cheng, H., Yu, J.X.: Graph clustering based on structural\/attribute similarities. Proc. VLDB Endow. 2(1), 718\u2013729 (2009)","journal-title":"Proc. VLDB Endow."},{"issue":"6","key":"3430_CR38","doi-asserted-by":"publisher","first-page":"471","DOI":"10.3390\/e20060471","volume":"20","author":"F Meng","year":"2018","unstructured":"Meng, F., et al.: Coupled node similarity learning for community detection in attributed networks. Entropy 20(6), 471 (2018)","journal-title":"Entropy"},{"issue":"1","key":"3430_CR39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-016-0028-x","volume":"7","author":"C Jia","year":"2017","unstructured":"Jia, C., et al.: Node attribute-enhanced community detection in complex networks. Sci. Rep. 7(1), 1\u201315 (2017)","journal-title":"Sci. Rep."},{"key":"3430_CR40","doi-asserted-by":"crossref","unstructured":"Pizzuti, C., Socievole, A.: A genetic algorithm for community detection in attributed graphs. In: International Conference on the Applications of Evolutionary Computation. Springer (2018)","DOI":"10.1007\/978-3-319-77538-8_12"},{"key":"3430_CR41","doi-asserted-by":"publisher","unstructured":"Berahmand, K., et al., A new attributed graph clustering by using label propagation in complex networks. J. King Saud Univ. Comput. Inf. Sci. (2020). https:\/\/doi.org\/10.1016\/j.jksuci.2020.08.013","DOI":"10.1016\/j.jksuci.2020.08.013"},{"issue":"3","key":"3430_CR42","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1007\/s10618-012-0263-0","volume":"25","author":"H Cheng","year":"2012","unstructured":"Cheng, H., et al.: Clustering large attributed information networks: an efficient incremental computing approach. Data Min. Knowl. Disc. 25(3), 450\u2013477 (2012)","journal-title":"Data Min. Knowl. Disc."},{"key":"3430_CR43","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.ins.2015.03.075","volume":"314","author":"X Huang","year":"2015","unstructured":"Huang, X., Cheng, H., Yu, J.X.: Dense community detection in multi-valued attributed networks. Inf. Sci. 314, 77\u201399 (2015)","journal-title":"Inf. Sci."},{"key":"3430_CR44","doi-asserted-by":"crossref","unstructured":"Gao, H., Huang, H.: Deep attributed network embedding. In: Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI) (2018)","DOI":"10.24963\/ijcai.2018\/467"},{"key":"3430_CR45","doi-asserted-by":"crossref","unstructured":"Cao, S., Lu, W., Xu, Q.: Grarep: learning graph representations with global structural information. In: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (2015)","DOI":"10.1145\/2806416.2806512"},{"key":"3430_CR46","doi-asserted-by":"crossref","unstructured":"Tang, J., et al.: Line: Large-scale information network embedding. In Proceedings of the 24th International Conference on World Wide Web (2015)","DOI":"10.1145\/2736277.2741093"},{"key":"3430_CR47","doi-asserted-by":"crossref","unstructured":"Le, T.M., Lauw, H.W.: Probabilistic latent document network embedding. In: 2014 IEEE International Conference on Data Mining. IEEE (2014)","DOI":"10.1109\/ICDM.2014.119"},{"key":"3430_CR48","doi-asserted-by":"crossref","unstructured":"Zhang, Z., et al.: ANRL: attributed network representation learning via deep neural networks. In: IJCAI (2018)","DOI":"10.24963\/ijcai.2018\/438"},{"key":"3430_CR49","doi-asserted-by":"crossref","unstructured":"Wang, C., et al.: Attributed graph clustering: a deep attentional embedding approach. (2019). http:\/\/arxiv.org\/abs\/1906.06532","DOI":"10.24963\/ijcai.2019\/509"},{"key":"3430_CR50","doi-asserted-by":"crossref","unstructured":"Zhang, X., et al.: Attributed graph clustering via adaptive graph convolution. (2019). http:\/\/arxiv.org\/abs\/1906.01210","DOI":"10.24963\/ijcai.2019\/601"},{"key":"3430_CR51","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. (2016). http:\/\/arxiv.org\/abs\/1609.02907"},{"key":"3430_CR52","unstructured":"Henaff, M., Bruna, J., LeCun, Y.: Deep convolutional networks on graph-structured data. (2015). http:\/\/arxiv.org\/abs\/1506.05163."},{"key":"3430_CR53","doi-asserted-by":"crossref","unstructured":"Wang, C., et al.: Mgae: marginalized graph autoencoder for graph clustering. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. (2017)","DOI":"10.1145\/3132847.3132967"},{"issue":"3","key":"3430_CR54","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3385415","volume":"14","author":"H Sun","year":"2020","unstructured":"Sun, H., et al.: Network embedding for community detection in attributed networks. ACM Trans. Knowl. Discov. Data (TKDD) 14(3), 1\u201325 (2020)","journal-title":"ACM Trans. Knowl. Discov. Data (TKDD)"},{"key":"3430_CR55","doi-asserted-by":"crossref","unstructured":"Luo, M., Yan, H.: Adaptive attributed network embedding for community detection. In: Chinese Conference on Pattern Recognition and Computer Vision (PRCV). Springer (2020)","DOI":"10.1007\/978-3-030-60636-7_14"},{"issue":"47","key":"3430_CR56","first-page":"1","volume":"20","author":"Z Zhou","year":"2019","unstructured":"Zhou, Z., Amini, A.A.: Analysis of spectral clustering algorithms for community detection: the general bipartite setting. J. Mach. Learn. Res. 20(47), 1\u201347 (2019)","journal-title":"J. Mach. Learn. Res."},{"key":"3430_CR57","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1017\/apr.2017.18","volume":"49","author":"L Gulikers","year":"2017","unstructured":"Gulikers, L., Lelarge, M., Massouli\u00e9, L.: A spectral method for community detection in moderately sparse degree-corrected stochastic block models. Adv. Appl. Probab. 49, 686\u2013721 (2017)","journal-title":"Adv. Appl. Probab."},{"issue":"2","key":"3430_CR58","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3106370","volume":"12","author":"Y Li","year":"2018","unstructured":"Li, Y., et al.: Local spectral clustering for overlapping community detection. ACM Trans. Knowl. Discov. Data (TKDD) 12(2), 1\u201327 (2018)","journal-title":"ACM Trans. Knowl. Discov. Data (TKDD)"},{"issue":"5","key":"3430_CR59","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1073\/pnas.1718449115","volume":"115","author":"F Liu","year":"2018","unstructured":"Liu, F., et al.: Global spectral clustering in dynamic networks. Proc. Natl. Acad. Sci. 115(5), 927\u2013932 (2018)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"8","key":"3430_CR60","doi-asserted-by":"publisher","first-page":"2903","DOI":"10.1109\/TNNLS.2019.2933850","volume":"31","author":"F Ye","year":"2019","unstructured":"Ye, F., et al.: Homophily preserving community detection. IEEE Trans. Neural Netw. Learn. Syst. 31(8), 2903\u20132915 (2019)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"3430_CR61","doi-asserted-by":"publisher","first-page":"111230","DOI":"10.1016\/j.chaos.2021.111230","volume":"151","author":"E Nasiri","year":"2021","unstructured":"Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. J. Chaos Solit. Fract. 151, 111230 (2021)","journal-title":"J. Chaos Solit. Fract."},{"key":"3430_CR62","doi-asserted-by":"publisher","first-page":"104325","DOI":"10.1016\/j.engappai.2021.104325","volume":"104","author":"S Forouzandeh","year":"2021","unstructured":"Forouzandeh, S., Rostami, M., Berahmand, K.: Presentation a trust walker for rating prediction in recommender system with biased random walk: effects of H-index centrality, similarity in items and friends. Eng. Appl. Artif. Intell. 104, 104325 (2021)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"3430_CR63","doi-asserted-by":"publisher","unstructured":"Berahmand, K., et al., A preference random walk algorithm for link prediction through mutual influence nodes in complex networks. J. King Saud Univ. Comput. Inf. Sci. (2021). https:\/\/doi.org\/10.1016\/j.jksuci.2021.05.006","DOI":"10.1016\/j.jksuci.2021.05.006"},{"issue":"5","key":"3430_CR64","doi-asserted-by":"publisher","first-page":"58007","DOI":"10.1209\/0295-5075\/89\/58007","volume":"89","author":"W Liu","year":"2010","unstructured":"Liu, W., L\u00fc, L.: Link prediction based on local random walk. EPL (Europhysics Letters) 89(5), 58007 (2010)","journal-title":"EPL (Europhysics Letters)"},{"key":"3430_CR65","unstructured":"Kuncheva, L.I., Hadjitodorov, S.T.: Using diversity in cluster ensembles. In: 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No. 04CH37583). IEEE (2004)"},{"issue":"336","key":"3430_CR66","doi-asserted-by":"publisher","first-page":"846","DOI":"10.1080\/01621459.1971.10482356","volume":"66","author":"WM Rand","year":"1971","unstructured":"Rand, W.M.: Objective criteria for the evaluation of clustering methods. J. Am. Stat. Assoc. 66(336), 846\u2013850 (1971)","journal-title":"J. Am. Stat. Assoc."},{"issue":"1","key":"3430_CR67","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1109\/TCSS.2014.2307458","volume":"1","author":"M Chen","year":"2014","unstructured":"Chen, M., Kuzmin, K., Szymanski, B.K.: Community detection via maximization of modularity and its variants. IEEE Trans. Comput. Soc. Syst. 1(1), 46\u201365 (2014)","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"issue":"12","key":"3430_CR68","doi-asserted-by":"publisher","first-page":"4997","DOI":"10.1109\/TCYB.2018.2889413","volume":"50","author":"C Pizzuti","year":"2019","unstructured":"Pizzuti, C., Socievole, A.: Multiobjective optimization and local merge for clustering attributed graphs. IEEE Trans. Cybernet. 50(12), 4997\u20135009 (2019)","journal-title":"IEEE Trans. Cybernet."},{"issue":"4","key":"3430_CR69","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 78(4), 046110 (2008)","journal-title":"Phys. Rev. E"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-021-03430-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-021-03430-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-021-03430-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T06:09:34Z","timestamp":1666764574000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-021-03430-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,17]]},"references-count":69,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,4]]}},"alternative-id":["3430"],"URL":"https:\/\/doi.org\/10.1007\/s10586-021-03430-0","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,17]]},"assertion":[{"value":"10 April 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 August 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 November 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}