{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T12:05:23Z","timestamp":1742990723259,"version":"3.40.3"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319973098"},{"type":"electronic","value":"9783319973104"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-97310-4_58","type":"book-chapter","created":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T16:06:19Z","timestamp":1532621179000},"page":"508-517","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Matrix Factorization for Identifying Noisy Labels of Multi-label Instances"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8223-5641","authenticated-orcid":false,"given":"Xia","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1667-6705","authenticated-orcid":false,"given":"Guoxian","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlotta","family":"Domeniconi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5890-0365","authenticated-orcid":false,"given":"Jun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zili","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,7,27]]},"reference":[{"issue":"11","key":"58_CR1","first-page":"2399","volume":"7","author":"M Belkin","year":"2006","unstructured":"Belkin, M., Niyogi, P., Sindhwani, V.: Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. JMLR 7(11), 2399\u20132434 (2006)","journal-title":"JMLR"},{"issue":"8","key":"58_CR2","doi-asserted-by":"publisher","first-page":"1548","DOI":"10.1109\/TPAMI.2010.231","volume":"33","author":"D Cai","year":"2011","unstructured":"Cai, D., He, X., Han, J., Huang, T.S.: Graph regularized nonnegative matrix factorization for data representation. TPAMI 33(8), 1548\u20131560 (2011)","journal-title":"TPAMI"},{"key":"58_CR3","unstructured":"Chen, Y., Lin, H.: Feature-aware label space dimension reduction for multi-label classification. In: NIPS, pp. 1529\u20131537 (2012)"},{"issue":"5","key":"58_CR4","first-page":"1501","volume":"12","author":"T Cour","year":"2011","unstructured":"Cour, T., Sapp, B., Taskar, B.: Learning from partial labels. JMLR 12(5), 1501\u20131536 (2011)","journal-title":"JMLR"},{"issue":"7","key":"58_CR5","first-page":"1734","volume":"28","author":"X Geng","year":"2016","unstructured":"Geng, X.: Label distribution learning. TKDE 28(7), 1734\u20131748 (2016)","journal-title":"TKDE"},{"issue":"3","key":"58_CR6","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1145\/2716262","volume":"47","author":"E Gibaja","year":"2015","unstructured":"Gibaja, E., Ventura, S.: A tutorial on multilabel learning. ACM Comput. Surv. 47(3), 52 (2015)","journal-title":"ACM Comput. Surv."},{"issue":"6","key":"58_CR7","doi-asserted-by":"publisher","first-page":"1737","DOI":"10.1109\/78.678511","volume":"46","author":"PC Hansen","year":"1998","unstructured":"Hansen, P.C., Jensen, S.H.: FIR filter representations of reduced-rank noise reduction. IEEE Trans. Signal Process. 46(6), 1737\u20131741 (1998)","journal-title":"IEEE Trans. Signal Process."},{"issue":"5","key":"58_CR8","doi-asserted-by":"crossref","first-page":"419","DOI":"10.3233\/IDA-2006-10503","volume":"10","author":"E H\u00fcllermeier","year":"2006","unstructured":"H\u00fcllermeier, E., Beringer, J.: Learning from ambiguously labeled examples. Intell. Data Anal. 10(5), 419\u2013439 (2006)","journal-title":"Intell. Data Anal."},{"issue":"1","key":"58_CR9","first-page":"36","volume":"31","author":"L Jiang","year":"2009","unstructured":"Jiang, L., Wang, D., Cai, Z., Jiang, S., Yan, X.: Scaling up the accuracy of k-nearest-neighbour classifiers: a Na\u00efve-Bayes hybrid. Int. J. Comput. Appl. 31(1), 36\u201343 (2009)","journal-title":"Int. J. Comput. Appl."},{"issue":"2","key":"58_CR10","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/s13042-013-0152-x","volume":"5","author":"L Jiang","year":"2014","unstructured":"Jiang, L., Cai, Z., Wang, D., Zhang, H.: Bayesian Citation-KNN with distance weighting. Int. J. Mach. Learn. Cybern. 5(2), 193\u2013199 (2014)","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"58_CR11","doi-asserted-by":"publisher","unstructured":"Jiang, L., Zhang, L., Li, C., Wu, J.: A correlation-based feature weighting filter for Naive Bayes. In: TKDE (2018). https:\/\/doi.org\/10.1109\/TKDE.2018.2836440","DOI":"10.1109\/TKDE.2018.2836440"},{"issue":"3","key":"58_CR12","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1109\/83.557359","volume":"6","author":"K Konstantinides","year":"1997","unstructured":"Konstantinides, K., Natarajan, B., Yovanof, G.S.: Noise estimation and filtering using block-based singular value decomposition. IEEE Trans. Image Process. 6(3), 479\u2013483 (1997)","journal-title":"IEEE Trans. Image Process."},{"key":"58_CR13","unstructured":"Lee, D.D., Seung, H.S.: Algorithms for non-negative matrix factorization. In: NIPS, pp. 556\u2013562 (2001)"},{"key":"58_CR14","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.knosys.2016.06.003","volume":"107","author":"C Li","year":"2016","unstructured":"Li, C., Sheng, V.S., Jiang, L., Li, H.: Noise filtering to improve data and model quality for crowdsourcing. Knowl. Based Syst. 107, 96\u2013103 (2016)","journal-title":"Knowl. Based Syst."},{"key":"58_CR15","unstructured":"Lin, Z., Ding, G., Hu, M., Wang, J.: Multi-label classification via feature-aware implicit label space encoding. In: ICML, pp. 325\u2013333 (2014)"},{"key":"58_CR16","unstructured":"Liu, L., Dietterich, T.G.: A conditional multinomial mixture model for superset label learning. In: NIPS, pp. 548\u2013556 (2012)"},{"key":"58_CR17","doi-asserted-by":"crossref","unstructured":"Meng, D., De La Torre, F.: Robust matrix factorization with unknown noise. In: ICCV, pp. 1337\u20131344 (2013)","DOI":"10.1109\/ICCV.2013.169"},{"key":"58_CR18","doi-asserted-by":"crossref","unstructured":"Nam, J., Kim, J., Menc\u00eda, E.L., Gurevych, I., F\u00fcrnkranz, J.: Large-scale multi-label text classification\u0142revisiting neural networks. In: ECML, pp. 437\u2013452 (2014)","DOI":"10.1007\/978-3-662-44851-9_28"},{"key":"58_CR19","doi-asserted-by":"crossref","unstructured":"Sun, Y., Zhang, Y., Zhou, Z.: Multi-label learning with weak label. In: AAAI, pp. 593\u2013598 (2010)","DOI":"10.1609\/aaai.v24i1.7699"},{"issue":"9","key":"58_CR20","doi-asserted-by":"publisher","first-page":"2508","DOI":"10.1162\/NECO_a_00320","volume":"24","author":"F Tai","year":"2012","unstructured":"Tai, F., Lin, H.: Multilabel classification with principal label space transformation. Neural Comput. 24(9), 2508\u20132542 (2012)","journal-title":"Neural Comput."},{"key":"58_CR21","doi-asserted-by":"crossref","unstructured":"Tang, C., Zhang, M.: Confidence-rated discriminative partial label learning. In: AAAI, pp. 2611\u20132617 (2017)","DOI":"10.1609\/aaai.v31i1.10775"},{"key":"58_CR22","first-page":"66","volume":"10","author":"L Van Der Maaten","year":"2009","unstructured":"Van Der Maaten, L., Postma, E., Van den Herik, J.: Dimensionality reduction: a comparative review. JMLR 10, 66\u201371 (2009)","journal-title":"JMLR"},{"issue":"7","key":"58_CR23","doi-asserted-by":"publisher","first-page":"2279","DOI":"10.1016\/j.patcog.2015.01.022","volume":"48","author":"B Wu","year":"2015","unstructured":"Wu, B., Lyu, S., Hu, B.G., Ji, Q.: Multi-label learning with missing labels for image annotation and facial action unit recognition. Pattern Recogn. 48(7), 2279\u20132289 (2015)","journal-title":"Pattern Recogn."},{"key":"58_CR24","doi-asserted-by":"crossref","unstructured":"Xu, C., Tao, D., Xu, C.: Robust extreme multi-label learning. In: KDD, pp. 1275\u20131284 (2016)","DOI":"10.1145\/2939672.2939798"},{"key":"58_CR25","doi-asserted-by":"crossref","unstructured":"Yeh, C., Wu, W., Ko, W., Wang, Y.F.: Learning deep latent space for multi-label classification. In: AAAI, pp. 2838\u20132844 (2017)","DOI":"10.1609\/aaai.v31i1.10769"},{"issue":"4","key":"58_CR26","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1007\/s10994-016-5606-4","volume":"104","author":"F Yu","year":"2017","unstructured":"Yu, F., Zhang, M.L.: Maximum margin partial label learning. Mach. Learn. 104(4), 573\u2013593 (2017)","journal-title":"Mach. Learn."},{"key":"58_CR27","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1007\/978-3-642-40988-2_37","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"Guoxian Yu","year":"2013","unstructured":"Yu, G., Domeniconi, C., Rangwala, H., Zhang, G.: Protein function prediction using dependence maximization. In: ECML\/PKDD, pp. 574\u2013589 (2013)"},{"key":"58_CR28","doi-asserted-by":"crossref","unstructured":"Yu, G., Zhang, G., Rangwala, H., Domeniconi, C., Yu, Z.: Protein function prediction using weak-label learning. In: ACM Conference on Bioinformatics, Computational Biology and Biomedicine, pp. 202\u2013209 (2012)","DOI":"10.1145\/2382936.2382962"},{"issue":"4","key":"58_CR29","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1007\/s10462-016-9491-9","volume":"46","author":"J Zhang","year":"2016","unstructured":"Zhang, J., Wu, X., Sheng, V.S.: Learning from crowdsourced labeled data: a survey. Artif. Intell. Rev. 46(4), 543\u2013576 (2016)","journal-title":"Artif. Intell. Rev."},{"issue":"02","key":"58_CR30","doi-asserted-by":"publisher","first-page":"1650003","DOI":"10.1142\/S0218001416500038","volume":"30","author":"L Zhang","year":"2016","unstructured":"Zhang, L., Jiang, L., Li, C.: A new feature selection approach to Naive Bayes text classifiers. Int. J. Pattern Recogn. Artif. Intell. 30(02), 1650003 (2016)","journal-title":"Int. J. Pattern Recogn. Artif. Intell."},{"key":"58_CR31","unstructured":"Zhang, M., Yu, F.: Solving the partial label learning problem: an instance-based approach. In: IJCAI, pp. 4048\u20134054 (2015)"},{"issue":"10","key":"58_CR32","first-page":"2155","volume":"29","author":"M Zhang","year":"2017","unstructured":"Zhang, M., Yu, F., Tang, C.: Disambiguation-free partial label learning. TKDE 29(10), 2155\u20132167 (2017)","journal-title":"TKDE"},{"key":"58_CR33","doi-asserted-by":"crossref","unstructured":"Zhang, M., Zhang, K.: Multi-label learning by exploiting label dependency. In: KDD, pp. 999\u20131008 (2010)","DOI":"10.1145\/1835804.1835930"},{"key":"58_CR34","doi-asserted-by":"crossref","unstructured":"Zhang, M., Zhou, B., Liu, X.: Partial label learning via feature-aware disambiguation. In: KDD, pp. 1335\u20131344 (2016)","DOI":"10.1145\/2939672.2939788"},{"issue":"7","key":"58_CR35","doi-asserted-by":"publisher","first-page":"2038","DOI":"10.1016\/j.patcog.2006.12.019","volume":"40","author":"M Zhang","year":"2007","unstructured":"Zhang, M., Zhou, Z.: ML-KNN: a lazy learning approach to multi-label learning. Pattern Recogn. 40(7), 2038\u20132048 (2007)","journal-title":"Pattern Recogn."},{"issue":"8","key":"58_CR36","first-page":"1819","volume":"26","author":"M Zhang","year":"2014","unstructured":"Zhang, M., Zhou, Z.: A review on multi-label learning algorithms. TKDE 26(8), 1819\u20131837 (2014)","journal-title":"TKDE"}],"container-title":["Lecture Notes in Computer Science","PRICAI 2018: Trends in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-97310-4_58","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T16:13:46Z","timestamp":1709828026000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-97310-4_58"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319973098","9783319973104"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-97310-4_58","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"27 July 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 August 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pricai2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/cse.seu.edu.cn\/pricai18\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"382","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"82","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"58","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"21% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.95","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.95","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}