{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T04:03:07Z","timestamp":1749787387023,"version":"3.41.0"},"reference-count":30,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,7]]},"DOI":"10.1109\/ijcnn.2016.7727475","type":"proceedings-article","created":{"date-parts":[[2016,11,8]],"date-time":"2016-11-08T21:15:56Z","timestamp":1478639756000},"page":"2228-2235","source":"Crossref","is-referenced-by-count":0,"title":["A non-parametric approach for learning from crowds"],"prefix":"10.1109","author":[{"given":"Jiayi","family":"Fu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinhong","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunfeng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenyu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ke","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref30","first-page":"1524","article-title":"Named entity recognition in tweets: an experimental study","author":"ritter","year":"2011","journal-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP' 11)"},{"key":"ref10","first-page":"932","article-title":"Modeling annotator expertise: Learning when everybody knows a bit of something","author":"yan","year":"2010","journal-title":"International Conference on Artificial Intelligence and Statistics (AISTATS)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1527\/tjsai.27.133"},{"key":"ref12","first-page":"1161","article-title":"Active learning from crowds","author":"yan","year":"2011","journal-title":"Proceedings of the 28th International Conference on Machine Learning (ICML)"},{"key":"ref13","first-page":"1061","article-title":"Active learning from crowds with unsure option","author":"zhong","year":"2015","journal-title":"Proceedings of the 24th InternationalJoint Conference on Artificial Intelligence '15)"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2010.5543189"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1609\/aaai.v27i1.8456","article-title":"Clustering crowds","author":"hiroshi kajino","year":"2013","journal-title":"Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI 2013)"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1086\/258244"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.2307\/2346806"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401965"},{"key":"ref19","first-page":"2035","article-title":"Whose vote should count more: Optimal integration of labels from labelers of unknown expertise","author":"whitehill","year":"2009","journal-title":"Advances in Neural Information Processing Systems (NIPS'09)"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.87.23.9193"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1017\/S1930297500002205","article-title":"Running experiments on amazon mechanical turk","volume":"5","author":"paolacci","year":"2010","journal-title":"Judgment and Decision Making"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2008.4562953"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1145\/1629911.1630023","article-title":"human computation","author":"von ahn","year":"2009","journal-title":"2009 46th ACM\/IEEE Design Automation Conference dac"},{"key":"ref6","first-page":"80","article-title":"Annotating named entities in twitter data with crowd-sourcing","author":"finin","year":"2010","journal-title":"Proc of NAACL HLT Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk 2010"},{"article-title":"UCI machine learning repository","year":"2007","author":"asuncion","key":"ref29"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1177\/1745691610393980"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3115\/1613715.1613751"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/1978942.1979148"},{"key":"ref9","first-page":"1297","article-title":"Learning from crowds","volume":"11","author":"raykar","year":"2010","journal-title":"The Iournal of Machine Learning Research"},{"key":"ref1","first-page":"255","article-title":"Convolutional networks for images, speech, and time series","volume":"3361","author":"lecun","year":"1995","journal-title":"The Handbook of Brain Theory and Neural Networks"},{"key":"ref20","first-page":"2424","article-title":"The multidimensional wisdom of crowds","author":"welinder","year":"2010","journal-title":"Advances in Neural Information Processing Systems 23 (NIPS'10)"},{"key":"ref22","first-page":"1612","article-title":"Max-margin majority voting for learning from crowds","author":"tian","year":"2015","journal-title":"Advances in Neural Information Processing Systems 28 (NIPS'15)"},{"key":"ref21","first-page":"18","article-title":"Vox populi: Collecting high-quality labels from a crowd","author":"dekel","year":"2009","journal-title":"22nd Annu Conf Learning Theory (COLT 2009)"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2013.6691593"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2013.08.007"},{"key":"ref26","article-title":"Fast training of support vector machines using sequential minimal optimization","volume":"3","author":"platt","year":"1999","journal-title":"Advances in Kernel Methods?Support Vector Learning"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014067"}],"event":{"name":"2016 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2016,7,24]]},"location":"Vancouver, BC, Canada","end":{"date-parts":[[2016,7,29]]}},"container-title":["2016 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7593175\/7726591\/07727475.pdf?arnumber=7727475","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,12]],"date-time":"2025-06-12T05:01:37Z","timestamp":1749704497000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7727475\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2016.7727475","relation":{},"subject":[],"published":{"date-parts":[[2016,7]]}}}