{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T06:04:21Z","timestamp":1776405861410,"version":"3.51.2"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031165634","type":"print"},{"value":"9783031165641","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-16564-1_13","type":"book-chapter","created":{"date-parts":[[2022,9,25]],"date-time":"2022-09-25T23:02:43Z","timestamp":1664146963000},"page":"127-137","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Impact of\u00a0Feedback Type on\u00a0Explanatory Interactive Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9318-9417","authenticated-orcid":false,"given":"Misgina Tsighe","family":"Hagos","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0095-9337","authenticated-orcid":false,"given":"Kathleen M.","family":"Curran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2518-0274","authenticated-orcid":false,"given":"Brian","family":"Mac Namee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,26]]},"reference":[{"key":"13_CR1","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1613\/jair.295","volume":"4","author":"DA Cohn","year":"1996","unstructured":"Cohn, D.A., Ghahramani, Z., Jordan, M.I.: Active learning with statistical models. J. Artif. Intell. Res. 4, 129\u2013145 (1996)","journal-title":"J. Artif. Intell. Res."},{"key":"13_CR2","unstructured":"Dalvi, B., Tafjord, O., Clark, P.: Towards teachable reasoning systems (2022). arXiv preprint arXiv:2204.13074"},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Fails, J.A., Olsen Jr, D.R.: Interactive machine learning. In: Proceedings of the 8th International Conference on Intelligent user Interfaces, pp. 39\u201345 (2003)","DOI":"10.1145\/604045.604056"},{"key":"13_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1007\/978-3-030-68796-0_2","volume-title":"Pattern Recognition. ICPR International Workshops and Challenges","author":"EM Kenny","year":"2021","unstructured":"Kenny, E.M., Delaney, E.D., Greene, D., Keane, M.T.: Post-hoc explanation options for XAI in deep learning: the Insight Centre for Data Analytics perspective. In: Del Bimbo, A., Cucchiara, R., Sclaroff, S., Farinella, G.M., Mei, T., Bertini, M., Escalante, H.J., Vezzani, R. (eds.) ICPR 2021. LNCS, vol. 12663, pp. 20\u201334. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-68796-0_2"},{"key":"13_CR5","unstructured":"Kim, B.: Interactive and interpretable machine learning models for human machine collaboration. Ph.D. thesis, Massachusetts Institute of Technology (2015)"},{"key":"13_CR6","unstructured":"Koh, P.W., Nguyen, T., Tang, Y.S., Mussmann, S., Pierson, E., Kim, B., Liang, P.: Concept bottleneck models. In: International Conference on Machine Learning, pp. 5338\u20135348. PMLR (2020)"},{"key":"13_CR7","unstructured":"Madaan, A., Tandon, N., Rajagopal, D., Yang, Y., Clark, P., Sakaguchi, K., Hovy, E.: Improving neural model performance through natural language feedback on their explanations. arXiv preprint arXiv:2104.08765 (2021)"},{"key":"13_CR8","unstructured":"Popordanoska, T., Kumar, M., Teso, S.: Machine guides, human supervises: Interactive learning with global explanations. arXiv preprint arXiv:2009.09723 (2020)"},{"key":"13_CR9","doi-asserted-by":"crossref","unstructured":"Rago, A., Cocarascu, O., Bechlivanidis, C., Lagnado, D., Toni, F.: Argumentative explanations for interactive recommendations. Artif. Intell. 296, 103506 (2021)","DOI":"10.1016\/j.artint.2021.103506"},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Ross, A.S., Hughes, M.C., Doshi-Velez, F.: Right for the right reasons: training differentiable models by constraining their explanations. arXiv preprint arXiv:1703.03717 (2017)","DOI":"10.24963\/ijcai.2017\/371"},{"issue":"8","key":"13_CR11","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1038\/s42256-020-0212-3","volume":"2","author":"P Schramowski","year":"2020","unstructured":"Schramowski, P., et al.: Making deep neural networks right for the right scientific reasons by interacting with their explanations. Nature Mach. Intell. 2(8), 476\u2013486 (2020)","journal-title":"Nature Mach. Intell."},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-cam: visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 618\u2013626 (2017)","DOI":"10.1109\/ICCV.2017.74"},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Lee, S., Shen, Y., Jin, H., Ghosh, S., Heck, L., Batra, D., Parikh, D.: Taking a hint: leveraging explanations to make vision and language models more grounded. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2591\u20132600 (2019)","DOI":"10.1109\/ICCV.2019.00268"},{"issue":"1","key":"13_CR14","first-page":"1","volume":"6","author":"B Settles","year":"2012","unstructured":"Settles, B.: Synthesis lectures on artificial intelligence and machine learning. Active learning 6(1), 1\u2013114 (2012)","journal-title":"Active learning"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Shao, X., Skryagin, A., Schramowski, P., Stammer, W., Kersting, K.: Right for better reasons: training differentiable models by constraining their influence function. In: Proceedings of Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI) (2021)","DOI":"10.1609\/aaai.v35i11.17148"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Teso, S., Kersting, K.: Explanatory interactive machine learning. In: Proceedings of the 2019 AAAI\/ACM Conference on AI, Ethics, and Society, pp. 239\u2013245 (2019)","DOI":"10.1145\/3306618.3314293"},{"key":"13_CR17","unstructured":"Xiao, H., Rasul, K., Vollgraf, R.: Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms. arXiv preprint arXiv:1708.07747 (2017)"}],"container-title":["Lecture Notes in Computer Science","Foundations of Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-16564-1_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T14:46:33Z","timestamp":1710341193000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-16564-1_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031165634","9783031165641"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-16564-1_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"26 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISMIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Methodologies for Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cosenza","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ismis2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ismis2022.icar.cnr.it\/","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":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"71","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":"31","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":"11","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":"44% - 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":"3.7","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","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":"Number and type of other papers accepted :\t4 industrial papers","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)"}}]}}