{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T14:16:50Z","timestamp":1766067410287,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030864712"},{"type":"electronic","value":"9783030864729"}],"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\/978-3-030-86472-9_33","type":"book-chapter","created":{"date-parts":[[2021,8,30]],"date-time":"2021-08-30T22:02:41Z","timestamp":1630360961000},"page":"361-373","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Stacking Approach for Cross-Domain Argument Identification"],"prefix":"10.1007","author":[{"given":"Alaa","family":"Alhamzeh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Bouhaouel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"El\u0151d","family":"Egyed-Zsigmond","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jelena","family":"Mitrovi\u0107","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lionel","family":"Brunie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harald","family":"Kosch","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,8,31]]},"reference":[{"key":"33_CR1","volume-title":"A Practical Study of Argument","author":"T Govier","year":"2001","unstructured":"Govier, T.: A Practical Study of Argument. Wadsworth, Belmont (2001)"},{"key":"33_CR2","volume-title":"Good Arguments: An Introduction to Critical Thinking","author":"CA Missimer","year":"1995","unstructured":"Missimer, C.A.: Good Arguments: An Introduction to Critical Thinking. Prentice Hall, Englewood Cliffs (1995)"},{"key":"33_CR3","doi-asserted-by":"crossref","unstructured":"Stab, C., Gurevych, I.: Identifying argumentative discourse structures in persuasive essays. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 46\u201356 (2014)","DOI":"10.3115\/v1\/D14-1006"},{"key":"33_CR4","doi-asserted-by":"crossref","unstructured":"Wambsganss, T., Molyndris, N., S\u00f6llner, M.: Unlocking transfer learning in argumentation mining: a domain-independent modelling approach. In: 15th International Conference on Wirtschaftsinformatik (2020)","DOI":"10.30844\/wi_2020_c9-wambsganss"},{"key":"33_CR5","doi-asserted-by":"crossref","unstructured":"Reimers, N., Schiller, B., Beck, T., Daxenberger, J., Stab, C., Gurevych, I.: Classification and clustering of arguments with contextualized word embeddings. arXiv preprint arXiv:1906.09821 (2019)","DOI":"10.18653\/v1\/P19-1054"},{"key":"33_CR6","doi-asserted-by":"crossref","unstructured":"Niven, T., Kao, H.-Y.: Probing neural network comprehension of natural language arguments. arXiv preprint arXiv:1907.07355 (2019)","DOI":"10.18653\/v1\/P19-1459"},{"issue":"3","key":"33_CR7","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273\u2013297 (1995)","journal-title":"Mach. Learn."},{"key":"33_CR8","unstructured":"Sanh, V., Debut, L., Chaumond, J., Wolf, T.: Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter. arXiv preprint arXiv:1910.01108 (2019)"},{"key":"33_CR9","doi-asserted-by":"crossref","unstructured":"Sagi, O., Rokach, L.: Ensemble learning: a survey. Wiley Interdisc. Rev. Data Mining Knowl. Disc. 8(4), e1249 (2018)","DOI":"10.1002\/widm.1249"},{"key":"33_CR10","unstructured":"Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"33_CR11","unstructured":"Wolf, T., et al.: Transformers: state-of-the-art natural language processing. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pp. 38\u201345 (2020)"},{"key":"33_CR12","doi-asserted-by":"crossref","unstructured":"Moens, M.-F., Boiy, E., Palau, R.M., Reed, C.: Automatic detection of arguments in legal texts. In: Proceedings of the 11th International Conference on Artificial Intelligence and Law, pp. 225\u2013230 (2007)","DOI":"10.1145\/1276318.1276362"},{"key":"33_CR13","doi-asserted-by":"crossref","unstructured":"Palau, R.M., Moens, M.-F.: Argumentation mining: the detection, classification and structure of arguments in text. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law, pp. 98\u2013107 (2009)","DOI":"10.1145\/1568234.1568246"},{"key":"33_CR14","unstructured":"Stab, C., Gurevych, I.: Annotating argument components and relations in persuasive essays. In: Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, pp. 1501\u20131510 (2014)"},{"issue":"3","key":"33_CR15","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1162\/COLI_a_00295","volume":"43","author":"C Stab","year":"2017","unstructured":"Stab, C., Gurevych, I.: Parsing argumentation structures in persuasive essays. Comput. Linguist. 43(3), 619\u2013659 (2017)","journal-title":"Comput. Linguist."},{"issue":"1","key":"33_CR16","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1162\/COLI_a_00276","volume":"43","author":"I Habernal","year":"2017","unstructured":"Habernal, I., Gurevych, I.: Argumentation mining in user-generated web discourse. Comput. Linguist. 43(1), 125\u2013179 (2017)","journal-title":"Comput. Linguist."},{"key":"33_CR17","doi-asserted-by":"crossref","unstructured":"Daxenberger, J., Eger, S., Habernal, I., Stab, C., Gurevych, I.: What is the essence of a claim? Cross-domain claim identification. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2055\u20132066, Copenhagen, Denmark, September 2017. Association for Computational Linguistics","DOI":"10.18653\/v1\/D17-1218"},{"issue":"10","key":"33_CR18","doi-asserted-by":"publisher","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","volume":"22","author":"SJ Pan","year":"2009","unstructured":"Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Trans. Knowl. Data Eng. 22(10), 1345\u20131359 (2009)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"33_CR19","unstructured":"Liga, D., Palmirani, M.: Transfer learning with sentence embeddings for argumentative evidence classification (2020)"},{"key":"33_CR20","doi-asserted-by":"crossref","unstructured":"Van der Laan, M.J., Polley, E.C., Hubbard, A.E.: Super learner (2007)","DOI":"10.2202\/1544-6115.1309"},{"key":"33_CR21","unstructured":"Goubin, R., Lefeuvre, D., Alhamzeh, A., Mitrovic, J., Egyed-Zsigmond, E., Fossi, L.G.: Bots and gender profiling using a multi-layer architecture. In: CLEF (Working Notes) (2019)"},{"key":"33_CR22","unstructured":"Ciccone, G., Sultan, A., Laporte, L., Egyed-Zsigmond, E., Alhamzeh, A., Granitzer, M.: Stacked gender prediction from tweet texts and images notebook for pan at CLEF 2018. In: CLEF 2018-Conference and Labs of the Evaluation, p. 11p (2018)"},{"key":"33_CR23","doi-asserted-by":"crossref","unstructured":"Toulmin, S.E.: The Uses of Argument. Cambridge University Press, Cambridge (2003)","DOI":"10.1017\/CBO9780511840005"},{"key":"33_CR24","unstructured":"Knott, A., Dale, R.: Using linguistic phenomena to motivate a set of rhetorical relations, August 1997"},{"key":"33_CR25","unstructured":"Caselli, T., Basile, V., Mitrovi\u0107, J., Kartoziya, I., Granitzer, M.: I feel offended, don\u2019t be abusive! Implicit\/explicit messages in offensive and abusive language. In: Proceedings of LREC (2020)"},{"key":"33_CR26","unstructured":"Liu, Y., et al.: Roberta: a robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692 (2019)"},{"key":"33_CR27","unstructured":"Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101 (2017)"}],"container-title":["Lecture Notes in Computer Science","Database and Expert Systems Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-86472-9_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T19:41:58Z","timestamp":1710358918000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-86472-9_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030864712","9783030864729"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-86472-9_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"31 August 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DEXA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database and Expert Systems Applications","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":"27 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"32","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dexa2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dexa.org\/dexa2021","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":"149","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":"37","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":"31","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":"25% - 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":"4","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","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"DEXA 2021 Workshops: 50 papers submitted, 23 papers accepted","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)"}}]}}