{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T11:01:57Z","timestamp":1775041317458,"version":"3.50.1"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030750145","type":"print"},{"value":"9783030750152","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-75015-2_14","type":"book-chapter","created":{"date-parts":[[2021,5,3]],"date-time":"2021-05-03T21:11:27Z","timestamp":1620076287000},"page":"133-142","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Data-Debugging Through Interactive Visual Explanations"],"prefix":"10.1007","author":[{"given":"Shazia","family":"Afzal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arunima","family":"Chaudhary","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nitin","family":"Gupta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hima","family":"Patel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carolina","family":"Spina","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dakuo","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,5,3]]},"reference":[{"issue":"4","key":"14_CR1","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1609\/aimag.v35i4.2513","volume":"35","author":"S Amershi","year":"2014","unstructured":"Amershi, S., Cakmak, M., Knox, W.B., Kulesza, T.: Power to the people: the role of humans in interactive machine learning. AI Mag. 35(4), 105 (2014). https:\/\/doi.org\/10.1609\/aimag.v35i4.2513","journal-title":"AI Mag."},{"key":"14_CR2","doi-asserted-by":"publisher","unstructured":"Desmond, M., Finegan-Dollak, C., Boston, J., Arnold, M.: Label noise in context. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 157\u2013186. Association for Computational Linguistics, July 2020. https:\/\/doi.org\/10.18653\/v1\/2020.acl-demos.21. https:\/\/www.aclweb.org\/anthology\/2020.acl-demos.21","DOI":"10.18653\/v1\/2020.acl-demos.21"},{"issue":"5","key":"14_CR3","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1109\/TNNLS.2013.2292894","volume":"25","author":"B Fr\u00e9nay","year":"2013","unstructured":"Fr\u00e9nay, B., Verleysen, M.: Classification in the presence of label noise: a survey. IEEE Trans. Neural Netw. Learn. Syst. 25(5), 845\u2013869 (2013)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"14_CR4","unstructured":"Ham, K.: Openrefine (version 2.5) open-source tool for cleaning and transforming data. J. Med. Libr. Assoc. JMLA 101(3), 233 (2013). http:\/\/openrefine.org.free"},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Hohman, F., Srinivasan, A., Drucker, S.M.: TeleGam: combining visualization and verbalization for interpretable machine learning, p. 5 (2019)","DOI":"10.31219\/osf.io\/p3wnm"},{"key":"14_CR6","doi-asserted-by":"publisher","unstructured":"Jain, A., et al.: Overview and importance of data quality for machine learning tasks, pp. 3561\u20133562, August 2020. https:\/\/doi.org\/10.1145\/3394486.3406477","DOI":"10.1145\/3394486.3406477"},{"key":"14_CR7","doi-asserted-by":"crossref","unstructured":"Kandel, S., Paepcke, A., Hellerstein, J., Heer, J.: Wrangler: interactive visual specification of data transformation scripts. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 3363\u20133372 (2011)","DOI":"10.1145\/1978942.1979444"},{"key":"14_CR8","unstructured":"Mohseni, S., Zarei, N., Ragan, E.D.: A multidisciplinary survey and framework for design and evaluation of explainable AI systems. arXiv:1811.11839 [cs], August 2020"},{"key":"14_CR9","doi-asserted-by":"crossref","unstructured":"Northcutt, C.G., Jiang, L., Chuang, I.L.: Confident learning: estimating uncertainty in dataset labels (2020)","DOI":"10.1613\/jair.1.12125"},{"key":"14_CR10","unstructured":"Sevastjanova, R., et al.: Going beyond visualization: verbalization as complementary medium to explain machine learning models (2018)"},{"key":"14_CR11","unstructured":"Smilkov, D., Thorat, N., Nicholson, C., Reif, E., Vi\u00e9gas, F.B., Wattenberg, M.: Embedding projector: interactive visualization and interpretation of embeddings. arXiv preprint arXiv:1611.05469 (2016)"},{"key":"14_CR12","doi-asserted-by":"publisher","unstructured":"Spinner, T., Schlegel, U., Schafer, H., El-Assady, M.: Explainer: a visual analytics framework for interactive and explainable machine learning. IEEE Trans. Vis. Comput. Graph. 1 (2019). https:\/\/doi.org\/10.1109\/TVCG.2019.2934629","DOI":"10.1109\/TVCG.2019.2934629"}],"container-title":["Lecture Notes in Computer Science","Trends and Applications in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-75015-2_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,3]],"date-time":"2021-05-03T21:17:56Z","timestamp":1620076676000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-75015-2_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030750145","9783030750152"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-75015-2_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"3 May 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 May 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 May 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pakdd2021.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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"673","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":"157","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":"23% - 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","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":"7","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)"}}]}}