{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T10:03:09Z","timestamp":1760608989581},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"S1","license":[{"start":{"date-parts":[[2017,5,2]],"date-time":"2017-05-02T00:00:00Z","timestamp":1493683200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2019,1]]},"DOI":"10.1007\/s00521-017-3024-6","type":"journal-article","created":{"date-parts":[[2017,5,2]],"date-time":"2017-05-02T08:01:27Z","timestamp":1493712087000},"page":"435-445","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Adaptive density distribution inspired affinity propagation clustering"],"prefix":"10.1007","volume":"31","author":[{"given":"Zheyi","family":"Fan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiao","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuqin","family":"Weng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhonghang","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiwen","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,5,2]]},"reference":[{"key":"3024_CR1","volume-title":"Mining of massive datasets","author":"A Rajaraman","year":"2012","unstructured":"Rajaraman A, Ullman JD (2012) Mining of massive datasets. Cambridge University Press, New York"},{"issue":"1","key":"3024_CR2","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/34.824819","volume":"22","author":"AK Jain","year":"2000","unstructured":"Jain AK, Duin RPW, Mao J (2000) Statistical pattern recognition: a review. IEEE Trans Pattern Anal Mach Intell 22(1):4\u201337","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"3024_CR3","doi-asserted-by":"publisher","first-page":"677","DOI":"10.1364\/JOSAA.31.000677","volume":"31","author":"R Liu","year":"2014","unstructured":"Liu R, Anand A, Dey DK et al (2014) Entropy-based clustering of embryonic stem cells using digital holographic microscopy. J Opt Soc Am A Opt Image Sci Vis 31(4):677\u2013684","journal-title":"J Opt Soc Am A Opt Image Sci Vis"},{"key":"3024_CR4","doi-asserted-by":"crossref","unstructured":"Jain AK (2008) Data clustering: 50 years beyond K-means. In: Proceedings of the 2008 European conference on machine learning and knowledge discovery in databases, Belgium, pp 3\u20134","DOI":"10.1007\/978-3-540-87479-9_3"},{"key":"3024_CR5","unstructured":"MacQueen J (1967) Some methods for classification and analysis of multivariate observations. In: Proceedings of the 5th Berkeley symposium on mathematical statistics and probability, California, p 281C297"},{"issue":"10","key":"3024_CR6","doi-asserted-by":"publisher","first-page":"1027C1040","DOI":"10.1016\/S0167-8655(99)00069-0","volume":"20","author":"JM Pena","year":"1999","unstructured":"Pena JM, Lozano JA, Larranaga P (1999) An empirical comparison of four initialization methods for the K-means algorithm. Pattern Recogn Lett 20(10):1027C1040","journal-title":"Pattern Recogn Lett"},{"issue":"5814","key":"3024_CR7","doi-asserted-by":"publisher","first-page":"972","DOI":"10.1126\/science.1136800","volume":"315","author":"BJ Frey","year":"2007","unstructured":"Frey BJ, Dueck D (2007) Clustering by passing messages between data points. Science 315(5814):972\u2013976","journal-title":"Science"},{"issue":"9","key":"3024_CR8","doi-asserted-by":"publisher","first-page":"22646","DOI":"10.3390\/s150922646","volume":"15","author":"T Zhang","year":"2015","unstructured":"Zhang T, Wu RB (2015) Affinity propagation clustering of measurements for multiple extended target tracking. Sensors 15(9):22646\u201322659","journal-title":"Sensors"},{"key":"3024_CR9","unstructured":"Frey BJ, Dueck D (2005) Mixture modeling by affinity propagation. In: Proceedings of the 18th advances in neural information processing systems, Columbia, p 379C386"},{"key":"3024_CR10","doi-asserted-by":"crossref","unstructured":"Zha ZJ, Yang LJ, Mei T et al (2009) Visual query suggestion. In: Proceedings of the 17th ACM international conference on multimedia, Beijing, pp 15\u201324","DOI":"10.1145\/1631272.1631278"},{"key":"3024_CR11","doi-asserted-by":"publisher","first-page":"938","DOI":"10.1016\/j.procs.2013.09.183","volume":"22","author":"Y Kokawa","year":"2013","unstructured":"Kokawa Y, Wu HY, Chen Q (2013) Improved affinity propagation for gesture recognition. Procedia Computer Science 22:938\u2013990","journal-title":"Procedia Computer Science"},{"issue":"7-8","key":"3024_CR12","doi-asserted-by":"publisher","first-page":"1809","DOI":"10.1007\/s00521-014-1671-4","volume":"25","author":"DW Chen","year":"2014","unstructured":"Chen DW, Sheng JQ, Chen JJ et al (2014) Stability-based preference selection in affinity propagation. Neural Comput & Applic 25(7-8):1809\u20131822","journal-title":"Neural Comput & Applic"},{"issue":"12","key":"3024_CR13","doi-asserted-by":"publisher","first-page":"3884","DOI":"10.1016\/j.apm.2010.03.027","volume":"34","author":"ZQ Zhao","year":"2010","unstructured":"Zhao ZQ, Gao J, Glotin H et al (2010) A matrix modular neural network based on task decomposition with subspace division by adaptive affinity propagation clustering. Appl Math Model 34(12):3884\u20133895","journal-title":"Appl Math Model"},{"issue":"12","key":"3024_CR14","first-page":"1242","volume":"33","author":"KJ Wang","year":"2007","unstructured":"Wang KJ, Zhang JY, Li D et al (2007) Adaptive affinity propagation clustering. ACTA Automatica Sinica 33(12):1242\u20131246","journal-title":"ACTA Automatica Sinica"},{"issue":"1","key":"3024_CR15","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1016\/j.patcog.2011.04.032","volume":"45","author":"FH Shang","year":"2012","unstructured":"Shang FH, Jiao LC, Shi JR et al (2012) Fast affinity propagation clustering: a multilevel approach. Pattern Recogn 45(1):474\u2013486","journal-title":"Pattern Recogn"},{"key":"3024_CR16","unstructured":"Qiu T, Li YJ (2015) A generalized affinity propagation clustering algorithm for nonspherical cluster discovery. arXiv: 1501.04318 . http:\/\/sciencewise.info\/articles\/1501.04318 . Accessed 13 August 2015"},{"key":"3024_CR17","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1016\/j.asoc.2016.01.034","volume":"41","author":"GJ Gana","year":"2016","unstructured":"Gana GJ, Zhang YP, Deyc DK (2016) Clustering by propagating probabilities between data points. Appl Soft Comput 41:390\u2013399","journal-title":"Appl Soft Comput"},{"issue":"3","key":"3024_CR18","doi-asserted-by":"publisher","first-page":"509","DOI":"10.3724\/SP.J.1146.2009.01066","volume":"32","author":"D Jun","year":"2010","unstructured":"Jun D, Ping WS, Lun XF (2010) Affinity propagation clustering based on variable-similarity measure. J Electron Inf Technol 32(3):509\u2013514","journal-title":"J Electron Inf Technol"},{"issue":"5552","key":"3024_CR19","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1126\/science.295.5552.7a","volume":"295","author":"M Balasubramanian","year":"2002","unstructured":"Balasubramanian M, Schwartz EL (2002) The isomap algorithm and topological stability. Science 295(5552):7\u20137","journal-title":"Science"},{"key":"3024_CR20","unstructured":"Dueck D (2009) Affinity propagation: clustering data by passing messages. Dissertation, University of Toronto"},{"issue":"6191","key":"3024_CR21","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1126\/science.1242072","volume":"344","author":"A Rodriguez","year":"2014","unstructured":"Rodriguez A, Laio A (2014) Clustering by fast search and find of density peaks. Science 344(6191):1492\u20131496","journal-title":"Science"},{"issue":"7-8","key":"3024_CR22","doi-asserted-by":"publisher","first-page":"1557","DOI":"10.1007\/s00521-014-1628-7","volume":"25","author":"HJ Jia","year":"2014","unstructured":"Jia HJ, Ding SF, Meng LH et al (2014) A density-adaptive affinity propagation clustering algorithm based on spectral dimension reduction. Neural Comput & Applic 25(7-8):1557\u20131567","journal-title":"Neural Comput & Applic"},{"key":"3024_CR23","doi-asserted-by":"publisher","first-page":"994","DOI":"10.4028\/www.scientific.net\/AMR.219-220.994","volume":"219-220","author":"XL Zou","year":"2011","unstructured":"Zou XL, Zhu QS, Yang RL (2011) Natural nearest neighbor for isomap algorithm without free-parameter. Adv Mater Res 219-220:994\u2013998","journal-title":"Adv Mater Res"},{"issue":"1","key":"3024_CR24","doi-asserted-by":"crossref","first-page":"94","DOI":"10.5539\/cis.v7n1p94","volume":"7","author":"S Zhang","year":"2014","unstructured":"Zhang S, Mouhoub M, Sadaoui S (2014) 3N-Q: natural nearest neighbor with quality. Comput Inform Sci 7(1):94\u2013102","journal-title":"Comput Inform Sci"},{"issue":"3","key":"3024_CR25","first-page":"583","volume":"3","author":"A Strehl","year":"2003","unstructured":"Strehl A, Ghosh J (2003) Cluster ensembles: a knowledge reuse framework for combining multiple partitions. J Mach Learn Res 3(3):583\u2013617","journal-title":"J Mach Learn Res"},{"issue":"1","key":"3024_CR26","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","journal-title":"J Classif"},{"key":"3024_CR27","unstructured":"Frank A, Asuncion A (2010) UCI Machine learning repository. http:\/\/archive.ics.uci.edu\/ml\/ . Accessed 1 July 1991"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-017-3024-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3024-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3024-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,22]],"date-time":"2019-09-22T19:19:59Z","timestamp":1569179999000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-017-3024-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,2]]},"references-count":27,"journal-issue":{"issue":"S1","published-print":{"date-parts":[[2019,1]]}},"alternative-id":["3024"],"URL":"https:\/\/doi.org\/10.1007\/s00521-017-3024-6","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,2]]},"assertion":[{"value":"17 August 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 April 2017","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 May 2017","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with Ethical Standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interests"}}]}}