{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T00:10:03Z","timestamp":1750983003810,"version":"3.41.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2017,11,10]],"date-time":"2017-11-10T00:00:00Z","timestamp":1510272000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"National Natural Science Foundation of China (CN)","award":["61473150"],"award-info":[{"award-number":["61473150"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2018,8]]},"DOI":"10.1007\/s10489-017-1084-z","type":"journal-article","created":{"date-parts":[[2017,11,10]],"date-time":"2017-11-10T05:55:07Z","timestamp":1510293307000},"page":"2355-2372","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A novel knowledge-leverage-based transfer learning algorithm"],"prefix":"10.1007","volume":"48","author":[{"given":"Meiling","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qun","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,11,10]]},"reference":[{"issue":"10","key":"1084_CR1","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","volume":"22","author":"SJ Pan","year":"2010","unstructured":"Pan SJ, Yang Q (2010) A survey on transfer learning. IEEE Trans Knowl Data Eng 22(10):1345\u20131359","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1084_CR2","doi-asserted-by":"crossref","unstructured":"Dai W, Xue GR, Yang Q, Yu Y (2007) Co-clustering based classification for out-of-domain documents. In: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining, KDD \u201907. San Jose, California, USA, pp 210\u2013219","DOI":"10.1145\/1281192.1281218"},{"issue":"12","key":"1084_CR3","doi-asserted-by":"crossref","first-page":"1638","DOI":"10.1109\/TKDE.2007.190663","volume":"19","author":"K Sarinnapakorn","year":"2007","unstructured":"Sarinnapakorn K, Kubat M (2007) Combining subclassifiers in text categorization: a DST-Based solution and a case study. IEEE Trans Knowl Data Eng 19(12):1638\u20131651","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1084_CR4","doi-asserted-by":"crossref","unstructured":"Xue GR, Dai W, Yang Q, Yu Y (2008) Topic-bridged PLSA for cross-domain text classification. In: Proceedings of the 31st annual international ACM SIGIR conference on research and development in information retrieval, SIGIR \u201908. Singapore, pp 627\u2013634","DOI":"10.1145\/1390334.1390441"},{"key":"1084_CR5","doi-asserted-by":"crossref","unstructured":"Zhu Y, Chen Y, Lu Z, Pan SJ, Xue GR, Yu Y et al (2011) Heterogeneous transfer learning for image classification. In: Proceedings of the twenty-fifth AAAI conference on artificial intelligence, AAAI 2011. San Francisco, California, USA, pp 7\u201311","DOI":"10.1609\/aaai.v25i1.8090"},{"key":"1084_CR6","doi-asserted-by":"crossref","unstructured":"Wu P, Dietterich TG (2004) Improving SVM accuracy by training on auxiliary data sources. In: Proceedings of the twenty-first international conference on machine learning, ICML \u201904. Banff, Alberta, Canada, July 04 - 08","DOI":"10.1145\/1015330.1015436"},{"issue":"1","key":"1084_CR7","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1613\/jair.1872","volume":"26","author":"I Hal Daum\u00e9","year":"2006","unstructured":"Hal Daum\u00e9 I, Marcu D (2006) Domain adaptation for statistical classifiers. J Artif Intell Res 26(1):101\u2013126","journal-title":"J Artif Intell Res"},{"key":"1084_CR8","doi-asserted-by":"crossref","unstructured":"Yang J, Yan R, Hauptmann AG (2007) Cross-domain video concept detection using adaptive svms. In: Proceedings of the 15th ACM international conference on multimedia, MM \u201907. Augsburg, Germany, pp 188\u2013197","DOI":"10.1145\/1291233.1291276"},{"key":"1084_CR9","doi-asserted-by":"crossref","unstructured":"Jiang W, Zavesky E, Chang SF, Loui A (2008) Cross-domain learning methods for high-level visual concept classification. In: 15th IEEE international conference on image processing, ICIP 2008, pp 161\u2013164","DOI":"10.1109\/ICIP.2008.4711716"},{"issue":"2","key":"1084_CR10","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.knosys.2012.08.024","volume":"37","author":"Q Dai","year":"2013","unstructured":"Dai Q (2013) A competitive ensemble pruning approach based on cross-validation technique. Knowl-Based Syst 37(2):394\u2013414","journal-title":"Knowl-Based Syst"},{"key":"1084_CR11","doi-asserted-by":"crossref","unstructured":"Kamishima T, Hamasaki M, Akaho S (2009) TrBagg: a simple transfer learning method and its application to personalization in collaborative tagging. In: Ninth IEEE international conference on data mining, ICDM \u201909, pp 219\u2013228","DOI":"10.1109\/ICDM.2009.9"},{"issue":"1","key":"1084_CR12","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/S0004-3702(02)00190-X","volume":"137","author":"Z Zhou","year":"2002","unstructured":"Zhou Z, Wu J, Tang W (2002) Ensembling neural networks: many could be better than all. Artif Intell 137(1):239\u2013263","journal-title":"Artif Intell"},{"issue":"2","key":"1084_CR13","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1109\/TPAMI.2008.78","volume":"31","author":"G Mart\u00ednez-Mu\u00f1oz","year":"2009","unstructured":"Mart\u00ednez-Mu\u00f1oz G, Hern\u00e1ndez-Lobato D, Su\u00e1rez A (2009) An analysis of ensemble pruning techniques based on ordered aggregation. IEEE Trans Pattern Anal Mach Intell 31(2):245\u2013259","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1084_CR14","doi-asserted-by":"crossref","unstructured":"Tsoumakas G, Partalas I, Vlahavas I (2009) An ensemble pruning primer. In: Okun O, Valentini G (eds) Applications of supervised and unsupervised ensemble methods, the series studies in computational intelligence, vol 245. Springer, Heidelberg, pp 1\u201313","DOI":"10.1007\/978-3-642-03999-7_1"},{"issue":"3","key":"1084_CR15","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1007\/s10994-010-5172-0","volume":"81","author":"I Partalas","year":"2010","unstructured":"Partalas I, Tsoumakas G, Vlahavas I (2010) An ensemble uncertainty aware measure for directed hill climbing ensemble pruning. Mach Learn 81(3):257\u2013282","journal-title":"Mach Learn"},{"key":"1084_CR16","unstructured":"Mart\u00ednez-Mu\u00f1oz G, Su\u00e1rez A (2004) Aggregation ordering in bagging. In: Proceeding of the IASTED international conference on artificial intelligence and applications. Innsbruck, Austria, pp 258\u2013263"},{"key":"1084_CR17","volume-title":"A study on greedy algorithms for ensemble pruning, Technical Report TR-LPIS-360-12, Department of Informatics","author":"I Partalas","year":"2012","unstructured":"Partalas I, Tsoumakas G, Vlahavas I (2012) A study on greedy algorithms for ensemble pruning, Technical Report TR-LPIS-360-12, Department of Informatics. Aristotle University of Thessaloniki, Greece"},{"issue":"2","key":"1084_CR18","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman L (1996) Bagging predictors. Mach Learn 24(2):123\u2013140","journal-title":"Mach Learn"},{"issue":"7","key":"1084_CR19","doi-asserted-by":"crossref","first-page":"1900","DOI":"10.1016\/j.neucom.2008.06.007","volume":"72","author":"I Partalas","year":"2009","unstructured":"Partalas I, Tsoumakas G, Vlahavas I (2009) Pruning an ensemble of classifiers via reinforcement learning. Neurocomputing 72(7):1900\u20131909","journal-title":"Neurocomputing"},{"issue":"3","key":"1084_CR20","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1109\/TPAMI.2011.114","volume":"34","author":"L Duan","year":"2012","unstructured":"Duan L, Tsang IW, Xu D (2012) Domain transfer multiple kernel learning. IEEE Trans Pattern Anal Mach Intell 34(3):465\u2013479","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"15","key":"1084_CR21","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.1016\/j.patrec.2009.07.006","volume":"30","author":"H Duan","year":"2009","unstructured":"Duan H, Shao X, Hou W, He G, Zeng Q (2009) An incremental learning algorithm for Lagrangian support vector machines. Pattern Recogn Lett 30(15):1384\u20131391","journal-title":"Pattern Recogn Lett"},{"issue":"2","key":"1084_CR22","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1023\/A:1009715923555","volume":"2","author":"CJC Burges","year":"1998","unstructured":"Burges CJC (1998) A tutorial on support vector machines for pattern recognition. Data Min Knowl Disc 2 (2):121\u2013167","journal-title":"Data Min Knowl Disc"},{"key":"1084_CR23","doi-asserted-by":"crossref","unstructured":"Gao J, Fan W, Jiang J, Han J (2008) Knowledge transfer via multiple model local structure mapping. In: Proceedings of the 14th ACM SIGKDD international conference on knowledge discovery and data mining, KDD \u201908. Las Vegas, Nevada, USA, pp 283\u2013291","DOI":"10.1145\/1401890.1401928"},{"issue":"12","key":"1084_CR24","doi-asserted-by":"crossref","first-page":"2585","DOI":"10.1109\/TCYB.2014.2311014","volume":"44","author":"Z Deng","year":"2014","unstructured":"Deng Z, Choi KS, Jiang Y, Wang S (2014) Generalized hidden-mapping ridge regression, knowledge-leveraged inductive transfer learning for neural networks, fuzzy systems and kernel methods. IEEE Trans Cybern 44(12):2585\u20132599","journal-title":"IEEE Trans Cybern"},{"key":"1084_CR25","doi-asserted-by":"crossref","unstructured":"Wang Y, Xiao J (2011) Transfer ensemble model for customer churn prediction with imbalanced class distribution. In: International conference on information technology, computer engineering and management sciences, vol 3, pp 177\u2013181","DOI":"10.1109\/ICM.2011.397"},{"key":"1084_CR26","unstructured":"Margineantu DD, Dietterich TG (1997) Pruning adaptive boosting. In: Proceedings of the fourteenth international conference on machine learning, ICML \u201997. Nashville, TN, pp 211\u2013218"},{"key":"1084_CR27","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.ins.2016.02.056","volume":"354","author":"M Galar","year":"2016","unstructured":"Galar M, Fern\u00e1ndez A, Barrenechea E, Bustince H, Herrera F (2016) Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets. Inf Sci 354:178\u2013196","journal-title":"Inf Sci"},{"key":"1084_CR28","doi-asserted-by":"crossref","unstructured":"Zhou Z, Wu X, Jiang Y, Chen S (2001) Genetic algorithm based selective neural network ensemble. In: IJCAI-01: proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, Seattle, Washington","DOI":"10.1142\/S1469026801000287"},{"key":"1084_CR29","first-page":"1315","volume":"7","author":"Y Zhang","year":"2006","unstructured":"Zhang Y, Burer S, Street WN (2006) Ensemble pruning via semi-definite programming. J Mach Learn Res 7:1315\u20131338","journal-title":"J Mach Learn Res"},{"key":"1084_CR30","doi-asserted-by":"crossref","unstructured":"Fu B, Wang Z, Pan R, Xu G, Dolog P (2013) An integrated pruning criterion for ensemble learning based on classification accuracy and diversity. In: Uden L, Herrera F, Bajo P\u00e9rez J, Corchado Rodr\u00edguez J (eds) 7th international conference on knowledge management in organizations: service and cloud computing. Advances in intelligent systems and computing, vol 172. Springer, Berlin, Heidelberg","DOI":"10.1007\/978-3-642-30867-3_5"},{"issue":"3","key":"1084_CR31","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1002\/sam.10008","volume":"1","author":"XZ Fern","year":"2008","unstructured":"Fern XZ, Lin W (2008) Cluster ensemble selection. Stat Anal Data Min 1(3):128\u2013141","journal-title":"Stat Anal Data Min"},{"issue":"2","key":"1084_CR32","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/S0893-6080(02)00187-9","volume":"16","author":"B Bakker","year":"2003","unstructured":"Bakker B, Heskes T (2003) Clustering ensembles of neural network models. Neural Netw 16(2):261\u2013269","journal-title":"Neural Netw"},{"issue":"5","key":"1084_CR33","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1631\/jzus.2005.A0387","volume":"6","author":"Q Fu","year":"2005","unstructured":"Fu Q, Qiang S, Zhao S (2005) Clustering-based selective neural network ensemble. J Zheijang Univ Sci A 6(5):387\u2013392","journal-title":"J Zheijang Univ Sci A"},{"issue":"1","key":"1084_CR34","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.patrec.2006.06.018","volume":"28","author":"G Mart\u00ednez-Mu\u00f1oz","year":"2007","unstructured":"Mart\u00ednez-Mu\u00f1oz G, Su\u00e1rez A (2007) Using boosting to prune bagging ensembles. Pattern Recogn Lett 28(1):156\u2013165","journal-title":"Pattern Recogn Lett"},{"key":"1084_CR35","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez-Mu\u00f1oz G, Su\u00e1rez A (2006) Pruning in ordered bagging ensembles. In: Proceedings of the 23rd international conference on machine learning, pp 609\u2013616","DOI":"10.1145\/1143844.1143921"},{"key":"1084_CR36","doi-asserted-by":"crossref","unstructured":"Dai W, Yang Q, Xue G-R, Yu Y (2007) Boosting for transfer learning. In: Proceedings of the 24th international conference on machine learning, ICML \u201907. Corvalis, Oregon, USA , pp 193\u2013200","DOI":"10.1145\/1273496.1273521"},{"key":"1084_CR37","unstructured":"Bickel S (2006) ECML-PKDD discovery challenge 2006 overview. In: Proceedings of ECML-PKDD discovery challenge workshop at Humboldt-Universit\u00e4t zu Berlin, Germany, pp 1\u20139"},{"key":"1084_CR38","doi-asserted-by":"crossref","unstructured":"Meng J, Lin H, Yu Y (2010) Transfer learning based on svd for spam filtering. In: 2010 international conference on intelligent computing and cognitive informatics (ICICCI), vol 2010 , pp 491\u2013494","DOI":"10.1109\/ICICCI.2010.115"},{"key":"1084_CR39","doi-asserted-by":"crossref","unstructured":"Shi X, Fan W, Ren J (2008) Actively transfer domain knowledge. In: Machine learning and knowledge discovery in databases, pp 342\u2013357","DOI":"10.1007\/978-3-540-87481-2_23"},{"key":"1084_CR40","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.knosys.2015.10.032","volume":"94","author":"S Zhao","year":"2016","unstructured":"Zhao S, Cao Q, Chen J, Zhang Y, Tang J, Duan Z (2016) A multi-atl method for transfer learning across multiple domains with arbitrarily different distribution. Knowl-Based Syst 94:60\u201369","journal-title":"Knowl-Based Syst"},{"key":"1084_CR41","doi-asserted-by":"crossref","unstructured":"Xue G, Dai W, Yang Q, Yu Y (2008) Topic-bridged PLSA for cross-domain text classification. In: Proceedings of the 31st annual international ACM SIGIR conference on research and development in information retrieval, pp 627\u2013634","DOI":"10.1145\/1390334.1390441"},{"key":"1084_CR42","doi-asserted-by":"crossref","unstructured":"Dai W, Xue G, Yang Q, Yu Y (2007) Co-clustering based classification for out-of-domain documents. In: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining, pp 210\u2013219","DOI":"10.1145\/1281192.1281218"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10489-017-1084-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-017-1084-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-017-1084-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T23:31:09Z","timestamp":1750980669000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10489-017-1084-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,10]]},"references-count":42,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2018,8]]}},"alternative-id":["1084"],"URL":"https:\/\/doi.org\/10.1007\/s10489-017-1084-z","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2017,11,10]]}}}