{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:21:33Z","timestamp":1740108093904,"version":"3.37.3"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"22","license":[{"start":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T00:00:00Z","timestamp":1714608000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T00:00:00Z","timestamp":1714608000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Industrial Support Project of Gansu Colleges","award":["2022CYZC-11"],"award-info":[{"award-number":["2022CYZC-11"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62276073","61762078"],"award-info":[{"award-number":["62276073","61762078"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100017943","name":"Gansu Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["21JR7RA114"],"award-info":[{"award-number":["21JR7RA114"]}],"id":[{"id":"10.13039\/100017943","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NWNU Teachers Research Capacity Promotion Plan","award":["NWNU-LKQN2019-2"],"award-info":[{"award-number":["NWNU-LKQN2019-2"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1007\/s00521-024-09751-6","type":"journal-article","created":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T07:02:08Z","timestamp":1714633328000},"page":"13975-13988","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Attribute subspace-guided multi-scale community detection"],"prefix":"10.1007","volume":"36","author":[{"given":"Cairui","family":"Yan","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5104-8982","authenticated-orcid":false,"given":"Huifang","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Yuechen","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Zhixin","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,5,2]]},"reference":[{"issue":"1","key":"9751_CR1","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1007\/s10142-021-00821-9","volume":"22","author":"F Almeida-Silva","year":"2022","unstructured":"Almeida-Silva F, Venancio TM (2022) Bionero: an all-in-one r\/bioconductor package for comprehensive and easy biological network reconstruction. Funct Integr Genom 22(1):131\u2013136","journal-title":"Funct Integr Genom"},{"key":"9751_CR2","doi-asserted-by":"publisher","first-page":"971552","DOI":"10.3389\/fpsyg.2023.971552","volume":"14","author":"H Li","year":"2023","unstructured":"Li H, Zhang X, Khaliq U, Rehman FU (2023) Emergency engineering reconstruction mode based on the perspective of professional donations. Front Psychol 14:971552","journal-title":"Front Psychol"},{"key":"9751_CR3","doi-asserted-by":"publisher","first-page":"107622","DOI":"10.1016\/j.knosys.2021.107622","volume":"235","author":"Q Li","year":"2022","unstructured":"Li Q, Ma H, Li J, Li Z, Jiang Y (2022) Searching target communities with outliers in attributed graph. Knowl-Based Syst 235:107622","journal-title":"Knowl-Based Syst"},{"key":"9751_CR4","doi-asserted-by":"publisher","first-page":"110077","DOI":"10.1016\/j.knosys.2022.110077","volume":"259","author":"H Liu","year":"2023","unstructured":"Liu H, Ma H, Li Z, Chang L (2023) Adaptive target community search with sample expansion. Knowl-Based Syst 259:110077","journal-title":"Knowl-Based Syst"},{"issue":"1","key":"9751_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3624580","volume":"18","author":"Q Li","year":"2023","unstructured":"Li Q, Ma H, Li Z, Chang L (2023) Multiresolution local spectral attributed community search. ACM Trans Web 18(1):1\u201328","journal-title":"ACM Trans Web"},{"issue":"4","key":"9751_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3613449","volume":"23","author":"F Yang","year":"2023","unstructured":"Yang F, Ma H, Yan C, Li Z, Chang L (2023) Polarized communities search via co-guided random walk in attributed signed networks. ACM Trans Internet Technol 23(4):1\u201322","journal-title":"ACM Trans Internet Technol"},{"issue":"3\u20135","key":"9751_CR7","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 (2010) Community detection in graphs. Phys Rep 486(3\u20135):75\u2013174","journal-title":"Phys Rep"},{"key":"9751_CR8","unstructured":"Maekawa S, Takeuch K, Onizuka M (2018) Non-linear attributed graph clustering by symmetric NMF with PU learning, arXiv preprint arXiv:1810.00946"},{"key":"9751_CR9","doi-asserted-by":"crossref","unstructured":"Zhe C, Sun A, Xiao X (2019) Community detection on large complex attribute network. In: Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining, pp. 2041\u20132049","DOI":"10.1145\/3292500.3330721"},{"issue":"12","key":"9751_CR10","doi-asserted-by":"publisher","first-page":"3463","DOI":"10.1007\/s13042-021-01384-8","volume":"12","author":"Q Zhao","year":"2021","unstructured":"Zhao Q, Ma H, Li X, Li Z (2021) Is the simple assignment enough? exploring the interpretability for community detection. Int J Mach Learn Cybern 12(12):3463\u20133474","journal-title":"Int J Mach Learn Cybern"},{"issue":"538","key":"9751_CR11","doi-asserted-by":"publisher","first-page":"951","DOI":"10.1080\/01621459.2020.1833888","volume":"117","author":"T Li","year":"2022","unstructured":"Li T, Lei L, Bhattacharyya S, Van den Berge K, Sarkar P, Bickel PJ, Levina E (2022) Hierarchical community detection by recursive partitioning. J Am Stat Assoc 117(538):951\u2013968","journal-title":"J Am Stat Assoc"},{"key":"9751_CR12","doi-asserted-by":"crossref","unstructured":"Zhao H, Yang X, Wang Z, Yang E, Deng C (2021) Graph debiased contrastive learning with joint representation clustering. In: IJCAI, pp. 3434\u20133440","DOI":"10.24963\/ijcai.2021\/473"},{"key":"9751_CR13","first-page":"1","volume":"2020","author":"S Ren","year":"2020","unstructured":"Ren S, Zhang S, Wu T (2020) An improved spectral clustering community detection algorithm based on probability matrix. Discret Dyn Nat Soc 2020:1\u20136","journal-title":"Discret Dyn Nat Soc"},{"key":"9751_CR14","doi-asserted-by":"publisher","first-page":"123633","DOI":"10.1016\/j.physa.2019.123633","volume":"545","author":"F Hu","year":"2020","unstructured":"Hu F, Liu J, Li L, Liang J (2020) Community detection in complex networks using node2vec with spectral clustering. Phys A 545:123633","journal-title":"Phys A"},{"key":"9751_CR15","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 (2021) Sag cluster: an unsupervised graph clustering based on collaborative similarity for community detection in complex networks. Physica A 563:125459","journal-title":"Physica A"},{"key":"9751_CR16","doi-asserted-by":"publisher","first-page":"107169","DOI":"10.1016\/j.knosys.2021.107169","volume":"227","author":"H Ma","year":"2021","unstructured":"Ma H, Liu Z, Zhang X, Zhang L, Jiang H (2021) Balancing topology structure and node attribute in evolutionary multi-objective community detection for attributed networks. Knowl-Based Syst 227:107169","journal-title":"Knowl-Based Syst"},{"key":"9751_CR17","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.ins.2022.04.047","volume":"602","author":"H Chen","year":"2022","unstructured":"Chen H, Yu Z, Yang Q, Shao J (2022) Community detection in subspace of attribute. Inf Sci 602:220\u2013235","journal-title":"Inf Sci"},{"issue":"2","key":"9751_CR18","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.acha.2010.04.005","volume":"30","author":"DK Hammond","year":"2011","unstructured":"Hammond DK, Vandergheynst P, Gribonval R (2011) Wavelets on graphs via spectral graph theory. Appl Comput Harmon Anal 30(2):129\u2013150","journal-title":"Appl Comput Harmon Anal"},{"issue":"15","key":"9751_CR19","doi-asserted-by":"publisher","first-page":"11073","DOI":"10.1007\/s00521-023-08284-8","volume":"35","author":"F \u00d6ztemiz","year":"2023","unstructured":"\u00d6ztemiz F, Karc\u0131 A (2023) Ko: modularity optimization in community detection. Neural Comput Appl 35(15):11073\u201311087","journal-title":"Neural Comput Appl"},{"key":"9751_CR20","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.ins.2019.10.076","volume":"513","author":"J Zhu","year":"2020","unstructured":"Zhu J, Chen B, Zeng Y (2020) Community detection based on modularity and k-plexes. Inf Sci 513:127\u2013142","journal-title":"Inf Sci"},{"issue":"5","key":"9751_CR21","doi-asserted-by":"publisher","first-page":"175335","DOI":"10.1007\/s11704-022-2220-4","volume":"17","author":"C Yan","year":"2023","unstructured":"Yan C, Ma H, Li Q, Yang F, Li Z (2023) Efficient multi-scale community search method based on spectral graph wavelet. Front Comp Sci 17(5):175335","journal-title":"Front Comp Sci"},{"issue":"1","key":"9751_CR22","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1073\/pnas.0605965104","volume":"104","author":"S Fortunato","year":"2007","unstructured":"Fortunato S, Barthelemy M (2007) Resolution limit in community detection. Proc Natl Acad Sci 104(1):36\u201341","journal-title":"Proc Natl Acad Sci"},{"key":"9751_CR23","unstructured":"Leskovec J, Mcauley J (2012) Learning to discover social circles in ego networks, Advances in neural information processing systems 25"},{"key":"9751_CR24","doi-asserted-by":"crossref","unstructured":"Peng Z, Luo M, Li J, Liu H, Zheng Q et al (2018) Anomalous: a joint modeling approach for anomaly detection on attributed networks. In: IJCAI, pp. 3513\u20133519","DOI":"10.24963\/ijcai.2018\/488"},{"key":"9751_CR25","doi-asserted-by":"crossref","unstructured":"G\u00fcnnemann S, F\u00e4rber I, Raubach S, Seidl T (2013) Spectral subspace clustering for graphs with feature vectors. In: 2013 IEEE 13th international conference on data mining, IEEE, pp. 231\u2013240","DOI":"10.1109\/ICDM.2013.110"},{"issue":"2","key":"9751_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3442390","volume":"12","author":"S Ali","year":"2021","unstructured":"Ali S, Shakeel MH, Khan I, Faizullah S, Khan MA (2021) Predicting attributes of nodes using network structure. ACM Trans Intell Syst Technol 12(2):1\u201323","journal-title":"ACM Trans Intell Syst Technol"},{"issue":"39","key":"9751_CR27","doi-asserted-by":"publisher","first-page":"15224","DOI":"10.1073\/pnas.0703740104","volume":"104","author":"M Sales-Pardo","year":"2007","unstructured":"Sales-Pardo M, Guimera R, Moreira AA, Amaral LAN (2007) Extracting the hierarchical organization of complex systems. Proc Natl Acad Sci 104(39):15224\u201315229","journal-title":"Proc Natl Acad Sci"},{"key":"9751_CR28","doi-asserted-by":"crossref","unstructured":"Ruan Y, Fuhry D, Parthasarathy S (2013) Efficient community detection in large networks using content and links. In: Proceedings of the 22nd international conference on World Wide Web, pp. 1089\u20131098","DOI":"10.1145\/2488388.2488483"},{"key":"9751_CR29","doi-asserted-by":"crossref","unstructured":"Cavallari S, Zheng VW, Cai H, Chang KC-C, Cambria E (2017) Learning community embedding with community detection and node embedding on graphs. In: Proceedings of the 2017 ACM on conference on information and knowledge management, pp. 377\u2013386","DOI":"10.1145\/3132847.3132925"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09751-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-09751-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09751-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T18:14:09Z","timestamp":1723227249000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-09751-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,2]]},"references-count":29,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["9751"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-09751-6","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2024,5,2]]},"assertion":[{"value":"3 September 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 March 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 May 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Written informed consent for publication of this paper was obtained from all authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical and informed consent for data used"}}]}}