{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T04:15:06Z","timestamp":1746591306588,"version":"3.40.5"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030461461"},{"type":"electronic","value":"9783030461478"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","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":[[2020]]},"DOI":"10.1007\/978-3-030-46147-8_2","type":"book-chapter","created":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T02:03:39Z","timestamp":1588298619000},"page":"20-36","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Continual Rare-Class Recognition with Emerging Novel Subclasses"],"prefix":"10.1007","author":[{"given":"Hung","family":"Nguyen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuejian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leman","family":"Akoglu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,4,30]]},"reference":[{"issue":"3","key":"2_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00737ED1V01Y201610AIM033","volume":"10","author":"Z Chen","year":"2016","unstructured":"Chen, Z., Liu, B.: Lifelong machine learning. Synth. Lect. Artif. Intell. Mach. Learn. 10(3), 1\u2013145 (2016)","journal-title":"Synth. Lect. Artif. Intell. Mach. Learn."},{"key":"2_CR2","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/S1364-6613(99)01294-2","volume":"3","author":"R French","year":"1999","unstructured":"French, R.: Catastrophic forgetting in connectionist networks. Trends Cogn. Sci. 3, 128\u2013135 (1999)","journal-title":"Trends Cogn. Sci."},{"key":"2_CR3","unstructured":"Kemker, R., Kanan, C.: Fearnet: brain-inspired model for incremental learning. In ICLR (2018)"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. In: EMNLP (2014)","DOI":"10.3115\/v1\/D14-1181"},{"issue":"13","key":"2_CR5","doi-asserted-by":"publisher","first-page":"3521","DOI":"10.1073\/pnas.1611835114","volume":"114","author":"J Kirkpatrick","year":"2017","unstructured":"Kirkpatrick, J., et al.: Overcoming catastrophic forgetting in neural networks. PNAS 114(13), 3521\u20133526 (2017)","journal-title":"PNAS"},{"key":"2_CR6","first-page":"1188","volume":"14","author":"QV Le","year":"2014","unstructured":"Le, Q.V., Mikolov, T.: Distributed representations of sentences and documents. ICML 14, 1188\u20131196 (2014)","journal-title":"ICML"},{"key":"2_CR7","unstructured":"Lee, S.-W., Kim, J.-H., Jun, J., Ha, J.-W., Zhang, B.-T.: Overcoming catastrophic forgetting by incremental moment matching. In NeurlPS, pp. 4652\u20134662 (2017)"},{"issue":"8","key":"2_CR8","first-page":"1605","volume":"29","author":"X Mu","year":"2017","unstructured":"Mu, X., Ting, K.M., Zhou, Z.-H.: Classification under streaming emerging new classes: a solution using completely-random trees. IEEE TKDE 29(8), 1605\u20131618 (2017)","journal-title":"IEEE TKDE"},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"Mu, X., Zhu, F., Du, J., Lim, E.-P., Zhou, Z.-H.: Streaming classification with emerging new class by class matrix sketching. In: AAAI (2017)","DOI":"10.1609\/aaai.v31i1.10842"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Nguyen, H., Wang, X., Akoglu, L.: Continual rare-class recognition with emerging novel subclasses. arXiv preprint (2019)","DOI":"10.1007\/978-3-030-46147-8_2"},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Rebuffi, S.-A., Kolesnikov, A., Sperl, G., Lampert, C.H.: ICARL: Incremental classifier and representation learning. In: CVPR, pp. 2001\u20132010 (2017)","DOI":"10.1109\/CVPR.2017.587"},{"key":"2_CR12","unstructured":"Shin, H., Lee, J.K., Kim, J., Kim, J.: Continual learning with deep generative replay. In: NeurlPS, pp. 2990\u20132999 (2017)"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Shu, L., Xu, H., Liu, B.: Doc: deep open classification of text documents. In: EMNLP (2017)","DOI":"10.18653\/v1\/D17-1314"},{"key":"2_CR14","unstructured":"Shu, L., Xu, H., Liu, B.: Unseen class discovery in open-world classification. arXiv preprint arXiv:1801.05609 (2018)"},{"key":"2_CR15","doi-asserted-by":"crossref","unstructured":"Siffer, A., Fouque, P.-A., Termier, A., Largouet, C.: Anomaly detection in streams with extreme value theory. In: KDD, pp. 1067\u20131075. ACM (2017)","DOI":"10.1145\/3097983.3098144"},{"key":"2_CR16","doi-asserted-by":"crossref","unstructured":"Xu, H., Liu, B., Shu, L., Yu, P.: Open-world learning and application to product classification. In: WWW (2019)","DOI":"10.1145\/3308558.3313644"},{"key":"2_CR17","unstructured":"Zhang, X., Zhao, J., LeCun, Y.: Character-level convolutional networks for text classification. In: NeurlPS, pp. 649\u2013657 (2015)"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-46147-8_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T09:24:37Z","timestamp":1746523477000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-46147-8_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030461461","9783030461478"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-46147-8_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"30 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"W\u00fcrzburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ecmlpkdd2019.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"733","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":"130","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":"0","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":"18% - 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":"3.04","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":"5.3","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)"}},{"value":"ECML PKDD Workshops Information: single-blind review, submissions: 200, full papers accepted: 70, short papers accepted: 46","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}