{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T08:33:36Z","timestamp":1742978016128,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030997380"},{"type":"electronic","value":"9783030997397"}],"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.springernature.com\/gp\/researchers\/text-and-data-mining"},{"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.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-99739-7_47","type":"book-chapter","created":{"date-parts":[[2022,4,4]],"date-time":"2022-04-04T23:02:47Z","timestamp":1649113367000},"page":"374-381","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["LeQua@CLEF2022: Learning to Quantify"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5725-4322","authenticated-orcid":false,"given":"Andrea","family":"Esuli","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0377-1025","authenticated-orcid":false,"given":"Alejandro","family":"Moreo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4221-6427","authenticated-orcid":false,"given":"Fabrizio","family":"Sebastiani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,5]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Ala\u00edz-Rodr\u00edguez, R., Guerrero-Curieses, A., Cid-Sueiro, J.: Class and subclass probability re-estimation to adapt a classifier in the presence of concept drift. Neurocomputing 74(16), 2614\u20132623 (2011)","key":"47_CR1","DOI":"10.1016\/j.neucom.2011.03.019"},{"doi-asserted-by":"crossref","unstructured":"Card, D., Smith, N.A.: The importance of calibration for estimating proportions from annotations. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics (HLT-NAACL 2018), New Orleans, US, pp. 1636\u20131646 (2018)","key":"47_CR2","DOI":"10.18653\/v1\/N18-1148"},{"doi-asserted-by":"crossref","unstructured":"Da San Martino, G., Gao, W., Sebastiani, F.: Ordinal text quantification. In: Proceedings of the 39th ACM Conference on Research and Development in Information Retrieval (SIGIR 2016), Pisa, IT, pp. 937\u2013940 (2016)","key":"47_CR3","DOI":"10.1145\/2911451.2914749"},{"doi-asserted-by":"crossref","unstructured":"Jos\u00e9 del Coz, J., Gonz\u00e1lez, P., Moreo, A., Sebastiani, F.: Learning to quantify: Methods and applications (LQ 2021). In: Proceedings of the 30th ACM International Conference on Knowledge Management (CIKM 2021), Gold Coast, AU (2021). Forthcoming","key":"47_CR4","DOI":"10.1145\/3459637.3482040"},{"issue":"4","key":"47_CR5","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1007\/s10994-016-5604-6","volume":"106","author":"MC du Plessis","year":"2016","unstructured":"du Plessis, M.C., Niu, G., Sugiyama, M.: Class-prior estimation for learning from positive and unlabeled data. Mach. Learn. 106(4), 463\u2013492 (2016). https:\/\/doi.org\/10.1007\/s10994-016-5604-6","journal-title":"Mach. Learn."},{"doi-asserted-by":"crossref","unstructured":"Esuli, A., Moreo, A., Sebastiani, F.: A recurrent neural network for sentiment quantification. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM 2018), Torino, IT, pp. 1775\u20131778 (2018)","key":"47_CR6","DOI":"10.1145\/3269206.3269287"},{"doi-asserted-by":"crossref","unstructured":"Esuli, A., Sebastiani, F.: Optimizing text quantifiers for multivariate loss functions. ACM Trans. Knowl. Discov. Data 9(4), Article 27 (2015)","key":"47_CR7","DOI":"10.1145\/2700406"},{"issue":"2","key":"47_CR8","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1007\/s10618-008-0097-y","volume":"17","author":"G Forman","year":"2008","unstructured":"Forman, G.: Quantifying counts and costs via classification. Data Min. Knowl. Disc. 17(2), 164\u2013206 (2008)","journal-title":"Data Min. Knowl. Disc."},{"issue":"1","key":"47_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s13278-016-0327-z","volume":"6","author":"W Gao","year":"2016","unstructured":"Gao, W., Sebastiani, F.: From classification to quantification in tweet sentiment analysis. Soc. Netw. Anal. Min. 6(1), 1\u201322 (2016). https:\/\/doi.org\/10.1007\/s13278-016-0327-z","journal-title":"Soc. Netw. Anal. Min."},{"doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez, P., Casta\u00f1o, A., Chawla, N.V., Jos\u00e9 del Coz, J.: A review on quantification learning. ACM Comput. Surv. 50(5), 74:1\u201374:40 (2017)","key":"47_CR10","DOI":"10.1145\/3117807"},{"unstructured":"Higashinaka, R., Funakoshi, K., Inaba, M., Tsunomori, Y., Takahashi, T., Kaji, N.: Overview of the 3rd dialogue breakdown detection challenge. In: Proceedings of the 6th Dialog System Technology Challenge (2017)","key":"47_CR11"},{"issue":"1","key":"47_CR12","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1111\/j.1540-5907.2009.00428.x","volume":"54","author":"DJ Hopkins","year":"2010","unstructured":"Hopkins, D.J., King, G.: A method of automated nonparametric content analysis for social science. Am. J. Polit. Sci. 54(1), 229\u2013247 (2010)","journal-title":"Am. J. Polit. Sci."},{"issue":"1","key":"47_CR13","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1214\/07-STS247","volume":"23","author":"G King","year":"2008","unstructured":"King, G., Ying, L.: Verbal autopsy methods with multiple causes of death. Stat. Sci. 23(1), 78\u201391 (2008)","journal-title":"Stat. Sci."},{"doi-asserted-by":"crossref","unstructured":"Levin, R., Roitman, H.: Enhanced probabilistic classify and count methods for multi-label text quantification. In: Proceedings of the 7th ACM International Conference on the Theory of Information Retrieval (ICTIR 2017), Amsterdam, NL, pp. 229\u2013232 (2017)","key":"47_CR14","DOI":"10.1145\/3121050.3121083"},{"issue":"1","key":"47_CR15","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1016\/j.patcog.2011.06.019","volume":"45","author":"JG Moreno-Torres","year":"2012","unstructured":"Moreno-Torres, J.G., Raeder, T., Ala\u00edz-Rodr\u00edguez, R., Chawla, N.V., Herrera, F.: A unifying view on dataset shift in classification. Pattern Recogn. 45(1), 521\u2013530 (2012)","journal-title":"Pattern Recogn."},{"doi-asserted-by":"crossref","unstructured":"Moreo, A., Esuli, A., Sebastiani, F.: QuaPy: a python-based framework for quantification. In: Proceedings of the 30th ACM International Conference on Knowledge Management (CIKM 2021), Gold Coast, AU (2021). Forthcoming","key":"47_CR16","DOI":"10.1145\/3459637.3482015"},{"doi-asserted-by":"crossref","unstructured":"Nakov, P., Ritter, A., Rosenthal, S., Sebastiani, F., Stoyanov, V.: SemEval-2016 Task 4: sentiment analysis in Twitter. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval 2016), San Diego, US, pp. 1\u201318 (2016)","key":"47_CR17","DOI":"10.18653\/v1\/S16-1001"},{"volume-title":"Dataset Shift in Machine Learning","year":"2009","unstructured":"Qui\u00f1onero-Candela, J., Sugiyama, M., Schwaighofer, A., Lawrence, N.D. (eds.): Dataset Shift in Machine Learning. The MIT Press, Cambridge (2009)","key":"47_CR18"},{"issue":"3","key":"47_CR19","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/s10791-019-09363-y","volume":"23","author":"F Sebastiani","year":"2020","unstructured":"Sebastiani, F.: Evaluation measures for quantification: an axiomatic approach. Inf. Retrieval J. 23(3), 255\u2013288 (2020)","journal-title":"Inf. Retrieval J."},{"unstructured":"Smith, N.A., Tromble, R.W.: Sampling uniformly from the unit simplex (2004). Unpublished manuscript. https:\/\/www.cs.cmu.edu\/~nasmith\/papers\/smith+tromble.tr04.pdf","key":"47_CR20"},{"key":"47_CR21","volume-title":"Statistical Learning Theory","author":"V Vapnik","year":"1998","unstructured":"Vapnik, V.: Statistical Learning Theory. Wiley, New York (1998)"},{"unstructured":"Zeng, Z., Kato, S., Sakai, T.: Overview of the NTCIR-14 short text conversation task: dialogue quality and nugget detection subtasks. In: Proceedings of NTCIR-14, pp. 289\u2013315 (2019)","key":"47_CR22"},{"unstructured":"Zeng, Z., Kato, S., Sakai, T., Kang, I.: Overview of the NTCIR-15 dialogue evaluation task (DialEval-1). In: Proceedings of NTCIR-15, pp. 13\u201334 (2020)","key":"47_CR23"}],"container-title":["Lecture Notes in Computer Science","Advances in Information Retrieval"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-99739-7_47","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T15:42:16Z","timestamp":1710258136000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-99739-7_47"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030997380","9783030997397"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-99739-7_47","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"5 April 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECIR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Information Retrieval","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Stavanger","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Norway","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":"10 April 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"44","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecir2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecir2022.org","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":"395","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":"35","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":"29","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":"9% - 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":"4-6","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":"Additionally, there are other papers: 11 reproducibility, 12 doctoral, 13 CLEF Labs, 5 workshops and 4 tutorials.","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)"}}]}}