乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:19:54Z","timestamp":1740122394531,"version":"3.37.3"},"reference-count":69,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T00:00:00Z","timestamp":1603843200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T00:00:00Z","timestamp":1603843200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100000038win","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000038win","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Data Min Knowl Disc"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1007\/s10618-020-00720-w","type":"journal-article","created":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T22:02:41Z","timestamp":1603922561000},"page":"248-289","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An exemplar-based clustering using efficient variational message passing"],"prefix":"10.1007","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0604-2709","authenticated-orcid":false,"given":"Mohamed Hamza","family":"Ibrahim","sequence":"first","affiliation":[]},{"given":"Rokia","family":"Missaoui","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,28]]},"reference":[{"issue":"1","key":"720_CR1","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1007\/s10994-013-5385-0","volume":"92","author":"B Ahmadi","year":"2013","unstructured":"Ahmadi B, Kersting K, Mladenov M, Natarajan S (2013) Exploiting symmetries for scaling loopy belief propagation and relational training. Mach Learn 92(1):91\u2013132","journal-title":"Mach Learn"},{"key":"720_CR2","unstructured":"Anguita D, Ghio A, Oneto L, Parra X, Reyes-Ortiz JL (2013) A public domain dataset for human activity recognition using smartphones. In: 21th European symposium on artificial neural networks, computational intelligence and machine learning, ESANN"},{"key":"720_CR3","unstructured":"Arthur D, Vassilvitskii S (2007) k-means++: the advantages of careful seeding. In: Proceedings of the eighteenth annual ACM-SIAM symposium on discrete algorithms. Society for Industrial and Applied Mathematics, pp 1027\u20131035"},{"key":"720_CR4","first-page":"453","volume":"7","author":"MJ Beal","year":"2003","unstructured":"Beal MJ, Ghahramani Z (2003) The variational bayesian EM algorithm for incomplete data: with application to scoring graphical model structures. Bayesian Stat. 7:453\u2013464","journal-title":"Bayesian Stat."},{"key":"720_CR5","doi-asserted-by":"crossref","unstructured":"Berkhin P (2006) A survey of clustering data mining techniques. In: Grouping multidimensional data. Springer, Berlin, pp 25\u201371","DOI":"10.1007\/3-540-28349-8_2"},{"issue":"18","key":"720_CR6","doi-asserted-by":"publisher","first-page":"i531","DOI":"10.1093\/bioinformatics\/btq376","volume":"26","author":"CV Cannistraci","year":"2010","unstructured":"Cannistraci CV, Ravasi T, Montevecchi FM, Ideker T, Alessio M (2010) Nonlinear dimension reduction and clustering by minimum curvilinearity unfold neuropathic pain and tissue embryological classes. Bioinformatics 26(18):i531\u2013i539","journal-title":"Bioinformatics"},{"key":"720_CR7","unstructured":"Cheeseman PC, Stutz JC (1996) Bayesian classification (autoclass): theory and results. In: Advances in knowledge discovery and data mining, CA, USA, pp 153\u2013180"},{"issue":"5","key":"720_CR8","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1109\/34.1000236","volume":"24","author":"D Comaniciu","year":"2002","unstructured":"Comaniciu D, Meer P (2002) Mean shift: a robust approach toward feature space analysis. IEEE Trans Pattern Anal Mach Intell 24(5):603\u2013619","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"720_CR9","doi-asserted-by":"crossref","unstructured":"Dalli A (2003) Adaptation of the f-measure to cluster based lexicon quality evaluation. In: Proceedings of the EACL 2003 Workshop on Evaluation Initiatives in Natural Language Processing: are evaluation methods, metrics and resources reusable? Association for Computational Linguistics, pp 51\u201356","DOI":"10.3115\/1641396.1641404"},{"key":"720_CR10","doi-asserted-by":"publisher","DOI":"10.1088\/1742-5468\/2005\/09\/P09008","author":"L Danon","year":"2005","unstructured":"Danon L, Diaz-Guilera A, Duch J, Arenas A (2005) Comparing community structure identification. J Stat Mech Theory Exp. https:\/\/doi.org\/10.1088\/1742-5468\/2005\/09\/P09008","journal-title":"J Stat Mech Theory Exp"},{"issue":"1","key":"720_CR11","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1007\/BF01890115","volume":"1","author":"WH Day","year":"1984","unstructured":"Day WH, Edelsbrunner H (1984) Efficient algorithms for agglomerative hierarchical clustering methods. J Classif 1(1):7\u201324","journal-title":"J Classif"},{"key":"720_CR12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","volume":"39","author":"AP Dempster","year":"1977","unstructured":"Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B (Methodological) 39:1\u201338","journal-title":"J R Stat Soc Ser B (Methodological)"},{"key":"720_CR13","unstructured":"Elidan G, McGraw I, Koller D (2006) Residual belief propagation: informed scheduling for asynchronous message passing. In: Proceedings of the twenty-second conference annual conference on uncertainty in artificial intelligence (UAI-06). AUAI Press, Arlington, Virginia, pp 165\u2013173"},{"key":"720_CR14","unstructured":"Ester M, Kriegel HP, Sander J, Xu X et al (1996) A density-based algorithm for discovering clusters in large spatial databases with noise. In: The second international conference on knowledge discovery and data mining, vol 96, pp 226\u2013231"},{"issue":"8","key":"720_CR15","doi-asserted-by":"publisher","first-page":"578","DOI":"10.1093\/comjnl\/41.8.578","volume":"41","author":"C Fraley","year":"1998","unstructured":"Fraley C, Raftery AE (1998) How many clusters? which clustering method? Answers via model-based cluster analysis. Comput J 41(8):578\u2013588","journal-title":"Comput J"},{"issue":"5814","key":"720_CR16","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"},{"key":"720_CR17","unstructured":"Fujiwara Y, Irie G, Kitahara T et\u00a0al (2011) Fast algorithm for affinity propagation. In: IJCAI proceedings-international joint conference on artificial intelligence, vol 22:3, p 2238"},{"key":"720_CR18","unstructured":"Givoni IE (2012) Beyond affinity propagation: message passing algorithms for clustering. Citeseer"},{"key":"720_CR19","unstructured":"Givoni I, Frey B (2009a) Semi-supervised affinity propagation with instance-level constraints. In: Artificial intelligence and statistics, pp 161\u2013168"},{"issue":"6","key":"720_CR20","doi-asserted-by":"publisher","first-page":"1589","DOI":"10.1162\/neco.2009.05-08-785","volume":"21","author":"IE Givoni","year":"2009","unstructured":"Givoni IE, Frey BJ (2009b) A binary variable model for affinity propagation. Neural Comput 21(6):1589\u20131600","journal-title":"Neural Comput"},{"key":"720_CR21","unstructured":"Givoni IE, Chung C, Frey BJ (2011) Hierarchical affinity propagation. In: Proceedings of the twenty-seventh conference on uncertainty in artificial intelligence. AUAI Press, Cambridge, pp 238\u2013246"},{"issue":"2\u20133","key":"720_CR22","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1023\/A:1012801612483","volume":"17","author":"M Halkidi","year":"2001","unstructured":"Halkidi M, Batistakis Y, Vazirgiannis M (2001) On clustering validation techniques. J. Intell. Inf. Syst. 17(2\u20133):107\u2013145","journal-title":"J. Intell. Inf. Syst."},{"key":"720_CR23","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1111\/j.2517-6161.1996.tb02073.x","volume":"58","author":"T Hastie","year":"1996","unstructured":"Hastie T, Tibshirani R (1996) Discriminant analysis by Gaussian mixtures. J R Stat Soc Ser B (Methodological) 58:155\u2013176","journal-title":"J R Stat Soc Ser B (Methodological)"},{"issue":"11","key":"720_CR24","doi-asserted-by":"publisher","first-page":"2379","DOI":"10.1162\/0899766041941943","volume":"16","author":"T Heskes","year":"2004","unstructured":"Heskes T (2004) On the uniqueness of loopy belief propagation fixed points. Neural Comput 16(11):2379\u20132413","journal-title":"Neural Comput"},{"key":"720_CR25","unstructured":"Horsch MC, Havens WS (2000) Probabilistic arc consistency: a connection between constraint reasoning and probabilistic reasoning. In: Proceedings of the sixteenth conference on uncertainty in artificial intelligence, San Francisco, CA, USA. Morgan Kaufmann Publishers Inc, pp 282\u2013290"},{"issue":"1","key":"720_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10994-016-5585-5","volume":"106","author":"MH Ibrahim","year":"2017","unstructured":"Ibrahim MH, Pal C, Pesant G (2017) Improving probabilistic inference in graphical models with determinism and cycles. Mach Learn 106(1):1\u201354","journal-title":"Mach Learn"},{"issue":"3","key":"720_CR27","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1111\/1467-9868.00083","volume":"59","author":"M Jamshidian","year":"1997","unstructured":"Jamshidian M, Jennrich RI (1997) Acceleration of the EM algorithm by using quasi-Newton methods. J R Stat Soc Ser B (Stat Methodol) 59(3):569\u2013587","journal-title":"J R Stat Soc Ser B (Stat Methodol)"},{"issue":"4","key":"720_CR28","doi-asserted-by":"publisher","first-page":"751","DOI":"10.1109\/TKDE.2011.221","volume":"25","author":"B Jiang","year":"2013","unstructured":"Jiang B, Pei J, Tao Y, Lin X (2013) Clustering uncertain data based on probability distribution similarity. IEEE Trans Knowl Data Eng 25(4):751\u2013763","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"3","key":"720_CR29","doi-asserted-by":"publisher","first-page":"46","DOI":"10.3390\/a9030046","volume":"9","author":"Y Jiang","year":"2016","unstructured":"Jiang Y, Liao Y, Yu G (2016) Affinity propagation clustering using path based similarity. Algorithms 9(3):46","journal-title":"Algorithms"},{"key":"720_CR30","volume-title":"Probabilistic graphical models: principles and techniques","author":"D Koller","year":"2009","unstructured":"Koller D, Friedman N (2009) Probabilistic graphical models: principles and techniques. MIT Press, Cambridge"},{"key":"720_CR31","doi-asserted-by":"crossref","unstructured":"Lam D, Wunsch DC (2014) Clustering. In: Academic Press library in signal processing, vol\u00a01, pp 1115\u20131149. Elsevier, Amsterdam","DOI":"10.1016\/B978-0-12-396502-8.00020-6"},{"key":"720_CR32","unstructured":"Lashkari D, Golland P (2008) Convex clustering with exemplar-based models. In: Advances in neural information processing systems, pp 825\u2013832"},{"issue":"20","key":"720_CR33","doi-asserted-by":"publisher","first-page":"2708","DOI":"10.1093\/bioinformatics\/btm414","volume":"23","author":"M Leone","year":"2007","unstructured":"Leone M, Weigt M (2007) Clustering by soft-constraint affinity propagation: applications to gene-expression data. Bioinformatics 23(20):2708\u20132715","journal-title":"Bioinformatics"},{"key":"720_CR34","unstructured":"Lichman M (2013) UCI machine learning repository. http:\/\/archive.ics.uci.edu\/ml"},{"key":"720_CR35","doi-asserted-by":"crossref","unstructured":"Mai ST, Assent I, Jacobsen J, Dieu MS (2018) Anytime parallel density-based clustering. In: Data mining and knowledge discovery pp 1\u201356","DOI":"10.1007\/s10618-018-0562-1"},{"key":"720_CR36","volume-title":"The EM algorithm and extensions","author":"G McLachlan","year":"2007","unstructured":"McLachlan G, Krishnan T (2007) The EM algorithm and extensions, vol 382. Wiley, New York"},{"key":"720_CR37","unstructured":"Mooij JM, Kappen HJ (2005) Sufficient conditions for convergence of loopy belief propagation. In: Proceedings of the twenty-first conference on uncertainty in artificial intelligence, UAI\u201905, pp. 396\u2013403. AUAI Press, Arlington, Virginia, USA. http:\/\/dl.acm.org\/citation.cfm?id=3020336.3020386"},{"key":"720_CR38","unstructured":"Murphy K, Weiss Y, Jordan M (1999) Loopy belief propagation for approximate inference: an empirical study. In: Proceedings of the fifteenth conference annual conference on uncertainty in artificial intelligence (UAI-99), Stockholm, Sweden. Morgan Kaufmann, pp 467\u2013476"},{"key":"720_CR39","unstructured":"Neal RM, Hinton GE (1999) Learning in graphical models. chap. In: A view of the EM algorithm that justifies incremental, sparse, and other variants, MIT Press, Cambridge, pp 355\u2013368"},{"key":"720_CR40","unstructured":"Ng AY, Jordan MI, Weiss Y (2002) On spectral clustering: analysis and an algorithm. In: Advances in neural information processing systems. MIT Press, Cambridge, pp 849\u2013856"},{"issue":"6","key":"720_CR41","doi-asserted-by":"publisher","first-page":"988","DOI":"10.1109\/TKDE.2011.86","volume":"24","author":"DT Nguyen","year":"2012","unstructured":"Nguyen DT, Chen L, Chan CK (2012) Clustering with multiviewpoint-based similarity measure. IEEE Trans Knowl Data Eng 24(6):988\u20131001","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"720_CR42","volume-title":"Probabilistic reasoning in intelligent systems: networks of plausible inference","author":"J Pearl","year":"1988","unstructured":"Pearl J (1988) Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, Burlington"},{"key":"720_CR43","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V et al (2011) Scikit-learn: machine learning in python. J Mach Learn Res 12:2825\u20132830","journal-title":"J Mach Learn Res"},{"issue":"9","key":"720_CR44","doi-asserted-by":"publisher","first-page":"1921","DOI":"10.1162\/0899766054322991","volume":"17","author":"KB Petersen","year":"2005","unstructured":"Petersen KB, Winther O, Hansen LK (2005) On the slow convergence of EM and VBEM in low-noise linear models. Neural Comput 17(9):1921\u20131926","journal-title":"Neural Comput"},{"key":"720_CR45","doi-asserted-by":"crossref","unstructured":"Potetz B (2007) Efficient belief propagation for vision using linear constraint nodes. In: Proceeding of IEEE conference on computer vision and pattern recognition (CVPR\u201907), IEEE computer society, Minneapolis, MN, USA, pp 1\u20138","DOI":"10.1109\/CVPR.2007.383094"},{"key":"720_CR46","unstructured":"Rasmussen CE (2000) The infinite Gaussian mixture model. In: Advances in neural information processing systems, pp. 554\u2013560"},{"key":"720_CR47","unstructured":"Rawashdeh A, Ralescu AL (2015) Similarity measure for social networks\u2014A brief survey. In: Proceedings of the 26th modern AI and cognitive science conference 2015, Greensboro, NC, USA, 25\u201326 April 2015, pp 153\u2013159"},{"issue":"9","key":"720_CR48","doi-asserted-by":"publisher","first-page":"4293","DOI":"10.1109\/TSP.2008.924136","volume":"56","author":"T Roosta","year":"2008","unstructured":"Roosta T, Wainwright MJ, Sastry SS (2008) Convergence analysis of reweighted sum-product algorithms. IEEE Trans Signal Process 56(9):4293\u20134305","journal-title":"IEEE Trans Signal Process"},{"key":"720_CR49","volume-title":"Handbook of constraint programming","author":"F Rossi","year":"2006","unstructured":"Rossi F, Van Beek P, Walsh T (2006) Handbook of constraint programming. Elsevier, Amsterdam"},{"issue":"3","key":"720_CR50","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1007\/s10618-009-0157-y","volume":"21","author":"C Ruiz","year":"2010","unstructured":"Ruiz C, Spiliopoulou M, Menasalvas E (2010) Density-based semi-supervised clustering. Data Min Knowl Disc 21(3):345\u2013370","journal-title":"Data Min Knowl Disc"},{"issue":"2","key":"720_CR51","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1023\/A:1009745219419","volume":"2","author":"J Sander","year":"1998","unstructured":"Sander J, Ester M, Kriegel HP, Xu X (1998) Density-based clustering in spatial databases: the algorithm GDBSCAN and its applications. Data Min Knowl Disc 2(2):169\u2013194","journal-title":"Data Min Knowl Disc"},{"key":"720_CR52","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1016\/j.neucom.2017.06.053","volume":"267","author":"A Saxena","year":"2017","unstructured":"Saxena A, Prasad M, Gupta A, Bharill N, Patel OP, Tiwari A, Er MJ, Ding W, Lin CT (2017) A review of clustering techniques and developments. Neurocomputing 267:664\u2013681","journal-title":"Neurocomputing"},{"issue":"1","key":"720_CR53","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1016\/j.patcog.2011.04.032","volume":"45","author":"F Shang","year":"2012","unstructured":"Shang F, Jiao L, Shi J, Wang F, Gong M (2012) Fast affinity propagation clustering: a multilevel approach. Pattern Recogn 45(1):474\u2013486","journal-title":"Pattern Recogn"},{"key":"720_CR54","unstructured":"Singla P, Nath A, Domingos P (2010) Approximate lifted belief propagation. In: Proceedings of the twenty-fourth AAAI conference on artificial intelligence, Atlanta, Georgia, USA, 11\u201315 July 2010. AAAI Press, pp 92\u201397"},{"key":"720_CR55","doi-asserted-by":"crossref","unstructured":"Strack B, DeShazo JP, Gennings C, Olmo JL, Ventura S, Cios KJ, Clore JN (2014) Impact of hba1c measurement on hospital readmission rates: analysis of 70,000 clinical database patient records. BioMed research international 2014","DOI":"10.1155\/2014\/781670"},{"issue":"11","key":"720_CR56","doi-asserted-by":"publisher","first-page":"2731","DOI":"10.1109\/TKDE.2014.2310215","volume":"26","author":"L Sun","year":"2014","unstructured":"Sun L, Guo C (2014) Incremental affinity propagation clustering based on message passing. IEEE Trans Knowl Data Eng 26(11):2731\u20132744","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"720_CR57","unstructured":"Tarlow D, Zemel RS, Frey BJ (2008) Flexible priors for exemplar-based clustering. In: Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence. AUAI Press, pp 537\u2013545"},{"key":"720_CR58","first-page":"1385","volume-title":"Advances in neural information processing systems","author":"YW Teh","year":"2005","unstructured":"Teh YW, Jordan MI, Beal MJ, Blei DM (2005) Sharing clusters among related groups: hierarchical Dirichlet processes. In: Saul LK, Weiss Y, Bottou L (eds) Advances in neural information processing systems, vol 17. MIT Press, Cambridge, pp 1385\u20131392"},{"issue":"9","key":"720_CR59","doi-asserted-by":"publisher","first-page":"2223","DOI":"10.1109\/TPAMI.2013.28","volume":"35","author":"CD Wang","year":"2013","unstructured":"Wang CD, Lai JH, Suen CY, Zhu JY (2013) Multi-exemplar affinity propagation. IEEE Trans Pattern Anal Mach Intell 35(9):2223\u20132237","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"720_CR60","unstructured":"Weiss Y (1997) Belief propagation and revision in networks with loops. Technical Report"},{"key":"720_CR61","first-page":"661","volume":"6","author":"JM Winn","year":"2005","unstructured":"Winn JM, Bishop CM (2005) Variational message passing. J Mach Learn Res 6:661\u2013694","journal-title":"J Mach Learn Res"},{"key":"720_CR62","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1214\/aos\/1176346060","volume":"11","author":"CJ Wu","year":"1983","unstructured":"Wu CJ (1983) On the convergence properties of the EM algorithm. Ann Stat 11:95\u2013103","journal-title":"Ann Stat"},{"key":"720_CR63","unstructured":"Xu X, Ester M, Kriegel HP, Sander J (1998) A distribution-based clustering algorithm for mining in large spatial databases. In: 14th international conference on data engineering, 1998. Proceedings IEEE, pp 324\u2013331"},{"key":"720_CR64","unstructured":"Yang Y, Chu X, Liang F, Huang TS (2012) Pairwise exemplar clustering. In: Twenty-sixth AAAI conference on artificial intelligence"},{"key":"720_CR65","doi-asserted-by":"publisher","first-page":"2282","DOI":"10.1109\/TIT.2005.850085","volume":"7","author":"J Yedidia","year":"2005","unstructured":"Yedidia J, Freeman W, Weiss Y (2005) Constructing free-energy approximations and generalized belief propagation algorithms. IEEE Trans Inf Theory 7:2282\u20132312","journal-title":"IEEE Trans Inf Theory"},{"key":"720_CR66","doi-asserted-by":"crossref","unstructured":"Yu J, Jia C (2009) Convergence analysis of affinity propagation. In: International conference on knowledge science, engineering and management. Springer, Berlin, pp 54\u201365","DOI":"10.1007\/978-3-642-10488-6_9"},{"issue":"4","key":"720_CR67","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1086\/jar.33.4.3629752","volume":"33","author":"WW Zachary","year":"1977","unstructured":"Zachary WW (1977) An information flow model for conflict and fission in small groups. J Anthropol Res 33(4):452\u2013473","journal-title":"J Anthropol Res"},{"issue":"7","key":"720_CR68","doi-asserted-by":"publisher","first-page":"1644","DOI":"10.1109\/TKDE.2013.146","volume":"26","author":"X Zhang","year":"2014","unstructured":"Zhang X, Furtlehner C, Germain-Renaud C, Sebag M (2014) Data stream clustering with affinity propagation. IEEE Trans Knowl Data Eng 26(7):1644\u20131656","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"720_CR69","unstructured":"Zopf M, Menc\u00eda EL, F\u00fcrnkranz J (2016) Sequential clustering and contextual importance measures for incremental update summarization. In: Proceedings of COLING 2016, the 26th international conference on computational linguistics: technical papers, pp 1071\u20131082"}],"container-title":["Data Mining and Knowledge Discovery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-020-00720-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10618-020-00720-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-020-00720-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,16]],"date-time":"2024-08-16T15:42:52Z","timestamp":1723822972000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10618-020-00720-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,28]]},"references-count":69,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["720"],"URL":"https:\/\/doi.org\/10.1007\/s10618-020-00720-w","relation":{},"ISSN":["1384-5810","1573-756X"],"issn-type":[{"type":"print","value":"1384-5810"},{"type":"electronic","value":"1573-756X"}],"subject":[],"published":{"date-parts":[[2020,10,28]]},"assertion":[{"value":"7 February 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 October 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 October 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}