{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T05:50:31Z","timestamp":1759384231862,"version":"3.37.3"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"24","license":[{"start":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T00:00:00Z","timestamp":1561075200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T00:00:00Z","timestamp":1561075200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100015422","name":"National Radio Astronomy Observatory","doi-asserted-by":"crossref","award":["ALMA Study Project"],"award-info":[{"award-number":["ALMA Study Project"]}],"id":[{"id":"10.13039\/100015422","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2020,12]]},"DOI":"10.1007\/s00521-019-04198-6","type":"journal-article","created":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T13:06:35Z","timestamp":1561122395000},"page":"18161-18178","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Empowering graph segmentation methods with SOMs and CONN similarity for clustering large and complex data"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8705-6186","authenticated-orcid":false,"given":"Erzs\u00e9bet","family":"Mer\u00e9nyi","sequence":"first","affiliation":[]},{"given":"Joshua","family":"Taylor","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,6,21]]},"reference":[{"key":"4198_CR1","doi-asserted-by":"publisher","first-page":"P10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","volume":"10","author":"VD Blondel","year":"2008","unstructured":"Blondel VD, Guillaume JL, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. J Stat Mech Theory Exp 10:P10008","journal-title":"J Stat Mech Theory Exp"},{"issue":"3","key":"4198_CR2","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1109\/TNN.2007.909556","volume":"19","author":"D Brugger","year":"2008","unstructured":"Brugger D, Bogdan M, Rosenstiel W (2008) Automatic cluster detection in Kohonen\u2019s SOM. IEEE Trans Neural Netw 19(3):442\u2013459","journal-title":"IEEE Trans Neural Netw"},{"key":"4198_CR3","doi-asserted-by":"publisher","first-page":"066111","DOI":"10.1103\/PhysRevE.70.066111","volume":"70","author":"A Clauset","year":"2004","unstructured":"Clauset A, Newman MEJ, Moore C (2004) Finding community structure in very large networks. Phys Rev E 70:066111. https:\/\/doi.org\/10.1103\/PhysRevE.70.066111","journal-title":"Phys Rev E"},{"key":"4198_CR4","unstructured":"Cottrell M, de\u00a0Bodt E (1996) A Kohonen map representation to avoid misleading interpretations. In: Proceedings of the 4th European symposium on artificial neural networks (ESANN\u201996), D-Facto, Bruges, pp 103\u2013110"},{"key":"4198_CR5","doi-asserted-by":"crossref","unstructured":"Cottrell M, Rousset P (1997) The Kohonen algorithm: a powerful tool for analyzing and representing multidimensional quantitative and qualitative data. In: Proceedings of the international work-conference on artificial neural networks, pp 861\u2013871","DOI":"10.1007\/BFb0032546"},{"key":"4198_CR6","first-page":"1","volume":"1695","author":"G Csardi","year":"2006","unstructured":"Csardi G, Nepusz T (2006) The igraph software package for complex network research. InterJournal Complex Syst 1695:1\u20139","journal-title":"InterJournal Complex Syst"},{"key":"4198_CR7","first-page":"P09008","volume":"09","author":"L Danon","year":"2005","unstructured":"Danon L, Daz-Guilera A, Duch J, Arenas A (2005) Comparing community structure identification. J Stat Mech Theory Exp 09:P09008","journal-title":"J Stat Mech Theory Exp"},{"issue":"3\u20135","key":"4198_CR8","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. https:\/\/doi.org\/10.1016\/j.physrep.2009.11.002","journal-title":"Phys Rep"},{"issue":"29","key":"4198_CR9","doi-asserted-by":"publisher","first-page":"3171","DOI":"10.1080\/01431160701442146","volume":"11","author":"M Goncalves","year":"2008","unstructured":"Goncalves M, Netto M, Costa JAF (2008) A new method for unsupervised classification of remotely sensed images using Kohonen Self-Organizing Maps and agglomeration hierarchical clustering methods. Int J Remote Sens 11(29):3171\u20133207","journal-title":"Int J Remote Sens"},{"key":"4198_CR10","unstructured":"Hamel L, Brown C (2011) Improved interpretability of the unified distance matrix with connected components. In: Proceedings of the 7th international conference on data mining (DMIN\u201911). CSREA Press, Las Vegas, pp 338\u2013343"},{"issue":"1","key":"4198_CR11","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/BF01908075","volume":"2","author":"L Hubert","year":"1985","unstructured":"Hubert L, Arabie P (1985) Comparing partitions. J Classif 2(1):193\u2013218. https:\/\/doi.org\/10.1007\/BF01908075","journal-title":"J Classif"},{"key":"4198_CR12","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1117\/12.488706","volume":"5075","author":"E Ientilucci","year":"2003","unstructured":"Ientilucci E, Brown S (2003) Advances in wide-area hyperspectral image simulation. Proc SPIE 5075:110\u2013121","journal-title":"Proc SPIE"},{"key":"4198_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-00784-6","volume-title":"Self-organization and associative memory","author":"T Kohonen","year":"1988","unstructured":"Kohonen T (1988) Self-organization and associative memory. Springer, New York"},{"key":"4198_CR14","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.neucom.2012.11.045","volume":"112","author":"J Lachmair","year":"2013","unstructured":"Lachmair J, Mer\u00e9nyi E, Porrmann M, R\u00fcckert U (2013) A reconfigurable neuroprocessor for self-organizing feature maps. Neurocomputing 112:189\u2013199","journal-title":"Neurocomputing"},{"issue":"10","key":"4198_CR15","doi-asserted-by":"publisher","first-page":"1472","DOI":"10.1109\/TMI.2008.923987","volume":"27","author":"W Liao","year":"2008","unstructured":"Liao W, Chen H, Yang Q, Lei X (2008) Analysis of fMRI data using improved self-organizing mapping and spatio-temporal metric hierarchical clustering. IEEE Trans Med Imaging 27(10):1472\u20131482","journal-title":"IEEE Trans Med Imaging"},{"issue":"3","key":"4198_CR16","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1016\/0893-6080(94)90109-0","volume":"7","author":"T Martinetz","year":"1994","unstructured":"Martinetz T, Schulten K (1994) Topology representing networks. Neural Netw 7(3):507\u2013522","journal-title":"Neural Netw"},{"key":"4198_CR17","doi-asserted-by":"crossref","unstructured":"Mendenhall M, Mer\u00e9nyi E (2009) On the evaluation of synthetic hyperspectral imagery. In: Proceedings of the first workshop on hyperspectral image and signal processing: evolution in remote sensing (WHISPERS 2009), Grenoble. http:\/\/www.ece.rice.edu\/~erzsebet\/papers\/. ISBN 978-1-4244-4687-2","DOI":"10.1109\/WHISPERS.2009.5289077"},{"issue":"3","key":"4198_CR18","doi-asserted-by":"publisher","first-page":"786","DOI":"10.1109\/TNN.2007.895833","volume":"18","author":"E Mer\u00e9nyi","year":"2007","unstructured":"Mer\u00e9nyi E, Jain A, Villmann T (2007) Explicit magnification control of self-organizing maps for \u201cforbidden\u201d data. IEEE Trans Neural Netw 18(3):786\u2013797","journal-title":"IEEE Trans Neural Netw"},{"key":"4198_CR19","doi-asserted-by":"crossref","unstructured":"Mer\u00e9nyi E, Ta\u015fdemir K, Farrand W (2008) Intelligent information extraction to aid science decision making in autonomous space exploration. In: Fink W (ed) Proceedings of the DSS08 SPIE defense and security symposium, space exploration technologies, vol 6960. SPIE, Orlando, p 69600M. http:\/\/scitation.aip.org\/dbt\/dbt.jsp?KEY=PSISDG&Volume=6960&Issue=1.","DOI":"10.1117\/12.782248"},{"key":"4198_CR20","series-title":"Lecture notes in computer science","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1007\/978-3-642-01805-3_8","volume-title":"Similarity-based clustering","author":"E Mer\u00e9nyi","year":"2009","unstructured":"Mer\u00e9nyi E, Ta\u015fdemir K, Zhang L (2009) Learning highly structured manifolds: harnessing the power of SOMs. In: Biehl M, Hammer B, Verleysen M, Villmann T (eds) Similarity-based clustering, vol 5400. Lecture notes in computer science. Springer, Berlin, Heidelberg, pp 138\u2013168"},{"key":"4198_CR21","doi-asserted-by":"crossref","unstructured":"Mer\u00e9nyi E, Taylor J (2017) SOM-empowered graph segmentation for fast automatic clustering of large and complex data. In: 12th International workshop on self-organizing maps and learning vector quantization, clustering and data visualization (WSOM+ 2017), pp 1\u20139","DOI":"10.1109\/WSOM.2017.8020004"},{"issue":"S325","key":"4198_CR22","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1017\/S1743921317000175","volume":"12","author":"E Mer\u00e9nyi","year":"2016","unstructured":"Mer\u00e9nyi E, Taylor J, Isella A (2016) Deep data: discovery and visualization. Application to hyperspectral ALMA imagery. Proc Int Astron Union 12(S325):281\u2013290. https:\/\/doi.org\/10.1017\/S1743921317000175","journal-title":"Proc Int Astron Union"},{"key":"4198_CR23","doi-asserted-by":"publisher","unstructured":"Mer\u00e9nyi E, Taylor J, Isella A (2016) Mining complex hyperspectral ALMA cubes for structure with neural machine learning. In: 2016 IEEE symposium series on computational intelligence (SSCI), pp 1\u20139. https:\/\/doi.org\/10.1109\/SSCI.2016.7849952","DOI":"10.1109\/SSCI.2016.7849952"},{"issue":"4","key":"4198_CR24","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1016\/0167-8655(94)00113-H","volume":"16","author":"F Murtagh","year":"1995","unstructured":"Murtagh F (1995) Interpreting the Kohonen self-organizing feature map using contiguity-constrained clustering. Pattern Recognit Lett 16(4):399\u2013408","journal-title":"Pattern Recognit Lett"},{"key":"4198_CR25","doi-asserted-by":"publisher","first-page":"066133","DOI":"10.1103\/PhysRevE.69.066133","volume":"69","author":"MEJ Newman","year":"2004","unstructured":"Newman MEJ (2004) Fast algorithm for detecting community structure in networks. Phys Rev E 69:066133. https:\/\/doi.org\/10.1103\/PhysRevE.69.066133","journal-title":"Phys Rev E"},{"key":"4198_CR26","doi-asserted-by":"publisher","first-page":"036104","DOI":"10.1103\/PhysRevE.74.036104","volume":"74","author":"MEJ Newman","year":"2006","unstructured":"Newman MEJ (2006) Finding community structure in networks using the eigenvectors of matrices. Phys Rev E 74:036104. https:\/\/doi.org\/10.1103\/PhysRevE.74.036104","journal-title":"Phys Rev E"},{"key":"4198_CR27","doi-asserted-by":"publisher","unstructured":"Pons P, Latapy M (2005) Computing communities in large networks using random walks. In: Proceedings of the 20th international conference on computer and information sciences, ISCIS\u201905. Springer, Berlin, Heidelberg, pp 284\u2013293. https:\/\/doi.org\/10.1007\/11569596_31","DOI":"10.1007\/11569596_31"},{"issue":"4","key":"4198_CR28","doi-asserted-by":"publisher","first-page":"1118","DOI":"10.1073\/pnas.0706851105","volume":"105","author":"M Rosvall","year":"2008","unstructured":"Rosvall M, Bergstrom CT (2008) Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci 105(4):1118\u20131123. https:\/\/doi.org\/10.1073\/pnas.0706851105","journal-title":"Proc Natl Acad Sci"},{"issue":"2","key":"4198_CR29","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1080\/07038992.1999.10874709","volume":"25","author":"J Schott","year":"1999","unstructured":"Schott J, Brown S, Raqueo R, Gross H, Robinson G (1999) An advanced synthetic image generation model and its application to multi\/hyperspectral algorithm development. Can J Remote Sens 25(2):99\u2013111","journal-title":"Can J Remote Sens"},{"key":"4198_CR30","doi-asserted-by":"crossref","unstructured":"Ta\u015fdemir K (2011) Spectral clustering as an automated SOM segmentation Tool. In: Proceedings of the workshop on self-organizing maps (WSOM 2011), pp 71\u201378","DOI":"10.1007\/978-3-642-21566-7_7"},{"issue":"4","key":"4198_CR31","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1109\/TNN.2008.2005409","volume":"20","author":"K Ta\u015fdemir","year":"2009","unstructured":"Ta\u015fdemir K, Mer\u00e9nyi E (2009) Exploiting data topology in visualization and clustering of Self-Organizing Maps. IEEE Trans Neural Netw 20(4):549\u2013562","journal-title":"IEEE Trans Neural Netw"},{"issue":"4","key":"4198_CR32","doi-asserted-by":"publisher","first-page":"1039","DOI":"10.1109\/TSMCB.2010.2104319","volume":"41","author":"K Ta\u015fdemir","year":"2011","unstructured":"Ta\u015fdemir K, Mer\u00e9nyi E (2011) A validity index for prototype based clustering of data sets with complex structures. IEEE Trans Syst Man Cybern Part B 41(4):1039\u20131053. https:\/\/doi.org\/10.1109\/TSMCB.2010.2104319","journal-title":"IEEE Trans Syst Man Cybern Part B"},{"issue":"3","key":"4198_CR33","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1109\/TNN.2011.2107527","volume":"22","author":"K Ta\u015fdemir","year":"2011","unstructured":"Ta\u015fdemir K, Milenov P, Tapsall B (2011) Topology-based hierarchical clustering of self-organizing maps. IEEE Trans Neural Netw 22(3):474\u2013485","journal-title":"IEEE Trans Neural Netw"},{"key":"4198_CR34","unstructured":"Ultsch A (2005) Clustering with SOM: U*c. In: Proceedings of the 5th workshop on self-organizing maps (WSOM 2005), Paris, pp 75\u201382"},{"issue":"3","key":"4198_CR35","doi-asserted-by":"publisher","first-page":"586","DOI":"10.1109\/72.846731","volume":"11","author":"J Vesanto","year":"2000","unstructured":"Vesanto J, Alhoniemi E (2000) Clustering of the self-organizing map. IEEE Trans Neural Netw 11(3):586\u2013600","journal-title":"IEEE Trans Neural Netw"},{"issue":"301","key":"4198_CR36","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1080\/01621459.1963.10500845","volume":"58","author":"JH Ward","year":"1963","unstructured":"Ward JH (1963) Hierarchical grouping to optimize an objective function. J Am Stat Assoc 58(301):236\u2013244. https:\/\/doi.org\/10.1080\/01621459.1963.10500845","journal-title":"J Am Stat Assoc"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04198-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04198-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04198-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,3]],"date-time":"2020-12-03T11:20:48Z","timestamp":1606994448000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04198-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,21]]},"references-count":36,"journal-issue":{"issue":"24","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["4198"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04198-6","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2019,6,21]]},"assertion":[{"value":"2 May 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 April 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 June 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}