{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:01:13Z","timestamp":1760709673856,"version":"3.37.3"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2018,8,4]],"date-time":"2018-08-04T00:00:00Z","timestamp":1533340800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61632011","61573231"],"award-info":[{"award-number":["61632011","61573231"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61432011","U1435212"],"award-info":[{"award-number":["61432011","U1435212"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672331"],"award-info":[{"award-number":["61672331"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2019,7]]},"DOI":"10.1007\/s13042-018-0858-x","type":"journal-article","created":{"date-parts":[[2018,8,4]],"date-time":"2018-08-04T09:23:28Z","timestamp":1533374608000},"page":"1805-1820","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Local dense mixed region cutting + global rebalancing: a method for imbalanced text sentiment classification"],"prefix":"10.1007","volume":"10","author":[{"given":"Yang","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suge","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiye","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juanzi","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,8,4]]},"reference":[{"key":"858_CR1","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1007\/s12559-015-9319-y","volume":"7","author":"RF Xu","year":"2015","unstructured":"Xu RF, Chen T, Xia YQ (2015) Word embedding composition for data imbalances in sentiment and emotion classification. Cogn Comput 7:226\u2013240","journal-title":"Cogn Comput"},{"key":"858_CR2","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1016\/j.knosys.2012.09.003","volume":"37","author":"S Wang","year":"2013","unstructured":"Wang S, Li D, Zhao L, Zhang J (2013) Sample cutting method for imbalanced text sentiment classification based on BRC. Knowl Based Syst 37:451\u2013461","journal-title":"Knowl Based Syst"},{"key":"858_CR3","doi-asserted-by":"crossref","unstructured":"Mountassir A, Benbrahim H, Berrada I (2012) An empirical study to address the problem of unbalanced data sets in sentiment classification. In: Proceedings of 2012 IEEE international conference on systems, man, and cybernetics, pp 14\u201317","DOI":"10.1109\/ICSMC.2012.6378300"},{"issue":"9","key":"858_CR4","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.1109\/TKDE.2008.239","volume":"21","author":"H He","year":"2009","unstructured":"He H, Garcia EA (2009) Learning from imbalanced data. IEEE Trans Knowl Data Eng 21(9):1263\u20131284","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"858_CR5","doi-asserted-by":"crossref","unstructured":"Junsomboon N, Phienthrakul T (2017) Combining over sampling and under sampling techniques for imbalance dataset. In: Proceedings of international conference on machine learning and computing, pp 243\u2013247","DOI":"10.1145\/3055635.3056643"},{"key":"858_CR6","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.patcog.2017.07.024","volume":"72","author":"T Zhu","year":"2017","unstructured":"Zhu T, Lin Y, Liu Y (2017) Synthetic minority oversampling technique for multiclass imbalance problems. Pattern Recogn 72:327\u2013340","journal-title":"Pattern Recogn"},{"issue":"1","key":"858_CR7","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla NV, Bowyer KW, Hall LO, Philip Kegelmeyer W (2002) Smote: synthetic minority over sampling technique. J Artif Intell Res 16(1):321\u2013357","journal-title":"J Artif Intell Res"},{"key":"858_CR8","doi-asserted-by":"publisher","first-page":"714","DOI":"10.1016\/j.asoc.2015.08.060","volume":"38","author":"B Krawczyk","year":"2016","unstructured":"Krawczyk B, Galar M, Jelen L, Herrera F (2016) Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy. Appl Soft Comput 38:714\u2013726","journal-title":"Appl Soft Comput"},{"key":"858_CR9","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.ins.2017.05.008","volume":"409","author":"WC Lin","year":"2017","unstructured":"Lin WC, Tsai CF, Hu YH (2017) Clustering based undersampling in class-imbalanced data. Inf Sci 409:17\u201326","journal-title":"Inf Sci"},{"key":"858_CR10","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.ins.2014.07.015","volume":"286","author":"S Maldonado","year":"2014","unstructured":"Maldonado S, Weber R, Famili F (2014) Feature selection for high dimensional class imbalanced data sets using support vector machines. Inf Sci 286:228\u2013246","journal-title":"Inf Sci"},{"key":"858_CR11","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1016\/j.neucom.2015.05.089","volume":"168","author":"Z Liu","year":"2015","unstructured":"Liu Z, Wang R, Tao M (2015) A class oriented feature selection approach for multi-class imbalanced network traffic datasets based on local and global metrics fusion. Neurocomputing 168:365\u2013381","journal-title":"Neurocomputing"},{"key":"858_CR12","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.neucom.2016.12.036","volume":"234","author":"P Cao","year":"2017","unstructured":"Cao P, Liu XI, Zhang J (2017) L2,1 norm regularized multi kernel based joint nonlinear feature selection and over sampling for imbalanced data classification. Neurocomputing 234:38\u201357","journal-title":"Neurocomputing"},{"issue":"1","key":"858_CR13","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1145\/1007730.1007741","volume":"6","author":"Z Zheng","year":"2004","unstructured":"Zheng Z, Wu X, Srihari RK (2004) Feature selection for text categorization on imbalanced data. Sigkdd Explor 6(1):80\u201389","journal-title":"Sigkdd Explor"},{"key":"858_CR14","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.ins.2017.09.013","volume":"422","author":"F Li","year":"2018","unstructured":"Li F, Zhang X, Zhang X (2018) Cost sensitive and hybrid attribute measure multi decision tree over imbalanced data sets. Inf Sci 422:242\u2013256","journal-title":"Inf Sci"},{"issue":"1","key":"858_CR15","first-page":"139","volume":"2","author":"LM Manevitz","year":"2002","unstructured":"Manevitz LM, Yousef M (2002) One-class SVMS for document classification. J Mach Learn Res 2(1):139\u2013154","journal-title":"J Mach Learn Res"},{"key":"858_CR16","doi-asserted-by":"crossref","unstructured":"Li S, Zhou G, Wang Z, Lee SYM, Wang R (2011) Imbalanced sentiment classification. In: Proceedings of ACM international conference on information and knowledge management, pp 2469\u20132472","DOI":"10.1145\/2063576.2063994"},{"key":"858_CR17","unstructured":"Zhang MD, Ma J (2016) An ensemble method for unbalanced sentiment classification. pp 440\u2013445"},{"key":"858_CR18","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/j.ipm.2016.08.003","volume":"53","author":"G Vinodhini","year":"2017","unstructured":"Vinodhini G, Chandrasekaran RM (2017) A sampling based sentiment mining approach fore commerce applications. Inf Process Manag 53:223\u2013236","journal-title":"Inf Process Manag"},{"key":"858_CR19","first-page":"220","volume":"73","author":"H Guo","year":"2016","unstructured":"Guo H, Li Y, Shang J (2016) Learning from class imbalanced data: review of methods and applications. Expert Syst Appl 73:220\u2013239","journal-title":"Expert Syst Appl"},{"key":"858_CR20","unstructured":"Kubat M, Matwin S (1997) Addressing the curse of imbalanced training sets: one sided selection. In: Proceedings of ICML-97, pp 179\u2013186"},{"issue":"3","key":"858_CR21","doi-asserted-by":"publisher","first-page":"5718","DOI":"10.1016\/j.eswa.2008.06.108","volume":"36","author":"S Yen","year":"2009","unstructured":"Yen S, Lee Y (2009) Cluster based under sampling approaches for imbalanced data distributions. Expert Syst Appl 36(3):5718\u20135727","journal-title":"Expert Syst Appl"},{"issue":"5","key":"858_CR22","doi-asserted-by":"publisher","first-page":"429","DOI":"10.3233\/IDA-2002-6504","volume":"6","author":"N Japkowicz","year":"2002","unstructured":"Japkowicz N, Stephen S (2002) The class imbalance problem: a systematic study. Intell Data Anal 6(5):429\u2013449","journal-title":"Intell Data Anal"},{"key":"858_CR23","unstructured":"Li S, Wang Z, Zhou G, Lee SYM (2009) Semi-supervised learning for imbalanced sentiment classification. In: Proceedings of Pacific-Asia conference on advances in knowledge discovery and data mining, pp 588\u2013595"},{"issue":"1","key":"858_CR24","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/j.dss.2009.07.011","volume":"48","author":"A Sun","year":"2009","unstructured":"Sun A, Lim E, Liu Y (2009) On strategies for imbalanced text classification using SVM: a comparative study. Decis Support Syst 48(1):191\u2013201","journal-title":"Decis Support Syst"},{"key":"858_CR25","unstructured":"Drummond C, Holte RC (2003) Class imbalance, and cost sensitivity: why under sampling beats over sampling. In: Proceedings of working notes ICML workshop learn, imbalanced data sets, Washington DC, pp 1\u20138"},{"issue":"12","key":"858_CR26","doi-asserted-by":"publisher","first-page":"2809","DOI":"10.1109\/TKDE.2013.37","volume":"25","author":"C Hong","year":"2013","unstructured":"Hong C, Xiaoli L, Yewkwong WD, Seekiong N (2013) Integrated oversampling for imbalanced time series classification. IEEE Trans Knowl Data Eng 25(12):2809\u20132822","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"3","key":"858_CR27","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1007\/s10489-011-0287-y","volume":"36","author":"C Bunkhumpornpat","year":"2012","unstructured":"Bunkhumpornpat C, Sinapiromsaran K, Lursinsap C (2012) Dbsmote: density-based yynthetic minority over-sampling technique. Appl Intell 36(3):664\u2013684","journal-title":"Appl Intell"},{"key":"858_CR28","doi-asserted-by":"crossref","unstructured":"Liu XY, Wu J, Zhou ZH (2006) Exploratory under-sampling for class-imbalance learning. In: Proceedings of international conference on data mining, pp 965\u2013969","DOI":"10.1109\/ICDM.2006.68"},{"issue":"3","key":"858_CR29","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1109\/TSMC.1972.4309137","volume":"2","author":"DL Wilson","year":"1972","unstructured":"Wilson DL (1972) Asymptotic properties of nearest neighbor rules using edited data. IEEE Trans Syst Man Cybern 2(3):408\u2013421","journal-title":"Syst Man Cybern"},{"key":"858_CR30","first-page":"1","volume":"99","author":"SH Khan","year":"2017","unstructured":"Khan SH, Hayat M, Bennamoun M, Sohel FA, Togneri R (2017) Cost-sensitive learning of deep feature representations from imbalanced data. IEEE Trans Neural Netw Learn Syst 99:1\u201315","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"858_CR31","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1016\/j.neucom.2013.05.003","volume":"122","author":"A Ghazikhani","year":"2013","unstructured":"Ghazikhani A, Monsefi R, Yazdi HS (2013) Ensemble of online neural networks for non-stationary and imbalanced data streams. Neurocomputing 122:535\u2013544","journal-title":"Neurocomputing"},{"issue":"6","key":"858_CR32","doi-asserted-by":"publisher","first-page":"888","DOI":"10.1109\/TNNLS.2013.2246188","volume":"24","author":"CL Castro","year":"2013","unstructured":"Castro CL, Braga AP (2013) Novel cost sensitive approach to improve the multilayer perceptron performance on imbalanced data. IEEE Trans Neural Netw Learn Syst 24(6):888\u2013899","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"3","key":"858_CR33","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/S0031-3203(02)00257-1","volume":"36","author":"R Barandela","year":"2003","unstructured":"Barandela R, Snchez JS, GarciA V, Rangel E (2003) Strategies for learning in class imbalance problems. Pattern Recogn 36(3):849\u2013851","journal-title":"Pattern Recogn"},{"issue":"7","key":"858_CR34","doi-asserted-by":"publisher","first-page":"1443","DOI":"10.1162\/089976601750264965","volume":"13","author":"JC Platt","year":"2001","unstructured":"Platt JC, Shawe-Taylor JC, Smola AJ, Williamson RC (2001) Estimating the support of a high-dimensional distribution. Neural Comput 13(7):1443","journal-title":"Neural Comput"},{"key":"858_CR35","doi-asserted-by":"crossref","unstructured":"Wagstaff KL, Lanza NL, Thompson DR, Dietterich TG, Gilmore MS (2013) Guiding scientific discovery with explanations using demud. In: Proceedings of twenty-seventh AAAI conference on artificial intelligence, pp 905\u2013911","DOI":"10.1609\/aaai.v27i1.8561"},{"key":"858_CR36","unstructured":"Yessenalina A, Yue Y, Cardie C (2010) Multi level structured models for document level sentiment classification. In: Proceedings of conference on empirical methods in natural language processing, pp 1046\u20131056"},{"key":"858_CR37","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1080\/0952813X.2012.721139","volume":"25","author":"H Wang","year":"2013","unstructured":"Wang H, Yin P, Yao J, Liu JN (2013) Document feature selection for sentiment classification of Chinese online reviews. J Exp Theor Artif Intell 25:425\u2013439","journal-title":"J Exp Theor Artif Intell"},{"issue":"1","key":"858_CR38","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.dss.2013.08.002","volume":"57","author":"G Wang","year":"2014","unstructured":"Wang G, Sun J, Ma J, Kaiquan X, Jibao G (2014) Sentiment classification: the contribution of ensemble learning. Decis Support Syst 57(1):77\u201393","journal-title":"Decis Support Syst"},{"issue":"2","key":"858_CR39","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1016\/j.eswa.2012.07.059","volume":"40","author":"M Rodrigo","year":"2013","unstructured":"Rodrigo M, Francisco VJ, Gavio Neto Wilson P (2013) Document-level sentiment classification: an empirical comparison between SVM and ANN. Expert Syst Appl 40(2):621\u2013633","journal-title":"Expert Syst Appl"},{"issue":"4","key":"858_CR40","doi-asserted-by":"publisher","first-page":"1857","DOI":"10.1016\/j.eswa.2014.09.011","volume":"42","author":"D Zhang","year":"2015","unstructured":"Zhang D, Hua X, Zengcai S, Yunfeng X (2015) Chinese comments sentiment classification based on word2vec and SVMperf. Expert Syst Appl 42(4):1857\u20131863","journal-title":"Expert Syst Appl"},{"key":"858_CR41","unstructured":"Li S, Ju S, Zhou G, Li X (2012) Active learning for imbalanced sentiment classification. In: Proceedings of joint conference on empirical methods in natural language processing and computational natural language learning, pp 139\u2013148"},{"key":"858_CR42","doi-asserted-by":"crossref","unstructured":"Prusa J, Khoshgoftaar TM, Dittman DJ, Napolitano A (2015) Using random undersampling to alleviate class imbalance on tweet sentiment data. In: Proceedings of IEEE international conference on information reuse and integration, pp 197\u2013202","DOI":"10.1109\/IRI.2015.39"},{"issue":"7","key":"858_CR43","doi-asserted-by":"publisher","first-page":"8696","DOI":"10.1016\/j.eswa.2011.01.077","volume":"38","author":"S Wang","year":"2011","unstructured":"Wang S, Li D, Song X, Wei Y, Li H (2011) A feature selection method based on improved Fisher\u2019s discriminant ratio for text sentiment classification. Expert Syst Appl 38(7):8696\u20138702","journal-title":"Expert Syst Appl"},{"key":"858_CR44","doi-asserted-by":"crossref","unstructured":"Pang B, Lee L, Vaithyanathan S (2002) Thumbs up?: sentiment classification using machine learning techniques. In: Proceedings of conference on empirical methods in natural language processing, pp 79\u201386","DOI":"10.3115\/1118693.1118704"},{"issue":"4","key":"858_CR45","doi-asserted-by":"publisher","first-page":"2622","DOI":"10.1016\/j.eswa.2007.05.028","volume":"34","author":"S Tan","year":"2008","unstructured":"Tan S, Zhang J (2008) An empirical study of sentiment analysis for Chinese documents. Expert Syst Appl 34(4):2622\u20132629","journal-title":"Expert Syst Appl"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0858-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-018-0858-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0858-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,28]],"date-time":"2022-08-28T19:32:41Z","timestamp":1661715161000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-018-0858-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,4]]},"references-count":45,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2019,7]]}},"alternative-id":["858"],"URL":"https:\/\/doi.org\/10.1007\/s13042-018-0858-x","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2018,8,4]]},"assertion":[{"value":"15 April 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 July 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 August 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}