{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:39:33Z","timestamp":1742945973329,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030712136"},{"type":"electronic","value":"9783030712143"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/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":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-71214-3_7","type":"book-chapter","created":{"date-parts":[[2021,3,24]],"date-time":"2021-03-24T11:04:17Z","timestamp":1616583857000},"page":"78-89","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Multi-task Learning Approach to Text Simplification"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7124-6927","authenticated-orcid":false,"given":"Anna","family":"Dmitrieva","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3065-7989","authenticated-orcid":false,"given":"J\u00f6rg","family":"Tiedemann","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,3,25]]},"reference":[{"key":"7_CR1","doi-asserted-by":"crossref","unstructured":"Alva-Manchego, F., Martin, L., Scarton, C., Specia, L.: EASSE: easier automatic sentence simplification evaluation. arXiv preprint arXiv:1908.04567 (2019)","DOI":"10.18653\/v1\/D19-3009"},{"key":"7_CR2","unstructured":"Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)"},{"key":"7_CR3","unstructured":"Bott, S., Saggion, H.: An unsupervised alignment algorithm for text simplification corpus construction. In: Proceedings of the Workshop on Monolingual Text-To-Text Generation, pp. 20\u201326 (2011)"},{"issue":"3","key":"7_CR4","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/S0950-7051(97)00029-4","volume":"10","author":"R Chandrasekar","year":"1997","unstructured":"Chandrasekar, R., Srinivas, B.: Automatic induction of rules for text simplification. Knowl.-Based Syst. 10(3), 183\u2013190 (1997)","journal-title":"Knowl.-Based Syst."},{"issue":"1","key":"7_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10462-016-9475-9","volume":"47","author":"M Gambhir","year":"2016","unstructured":"Gambhir, M., Gupta, V.: Recent automatic text summarization techniques: a survey. Artif. Intell. Rev. 47(1), 1\u201366 (2016). https:\/\/doi.org\/10.1007\/s10462-016-9475-9","journal-title":"Artif. Intell. Rev."},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Gehrmann, S., Deng, Y., Rush, A.M.: Bottom-up abstractive summarization. arXiv preprint arXiv:1808.10792 (2018)","DOI":"10.18653\/v1\/D18-1443"},{"key":"7_CR7","unstructured":"Hermann, K.M., Kocisky, T., Grefenstette, E., Espeholt, L., Kay, W., Suleyman, M., Blunsom, P.: Teaching machines to read and comprehend. In: Advances in Neural Information Processing Systems, pp. 1693\u20131701 (2015)"},{"key":"7_CR8","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1162\/tacl_a_00065","volume":"5","author":"M Johnson","year":"2017","unstructured":"Johnson, M., et al.: Enabling zero-shot translation: Google\u2019s multilingual neural machine translation system. Trans. Assoc. Comput. Linguist. 5, 339\u2013351 (2017)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"Karpov, N., Sibirtseva, V.: Towards automatic text adaptation in Russian. Higher School of Economics Research Paper No. WP BRP, 16 (2014)","DOI":"10.2139\/ssrn.2548462"},{"key":"7_CR10","unstructured":"Kauchak, D.: Improving text simplification language modeling using unsimplified text data. In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Long papers), vol. 1, pp. 1537\u20131546, August 2013"},{"key":"7_CR11","unstructured":"Keskis\u00e4rkk\u00e4, R.: Automatic text simplification via synonym replacement (2012)"},{"key":"7_CR12","doi-asserted-by":"crossref","unstructured":"Klein, G., Kim, Y., Deng, Y., Senellart, J., Rush, A.M.: Opennmt: open-source toolkit for neural machine translation. arXiv preprint arXiv:1701.02810 (2017)","DOI":"10.18653\/v1\/P17-4012"},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Kriz, R., et al.: Complexity-weighted loss and diverse reranking for sentence simplification. arXiv preprint arXiv:1904.02767 (2019)","DOI":"10.18653\/v1\/N19-1317"},{"key":"7_CR14","unstructured":"Lal, P., Ruger, S.: Extract-based summarization with simplification. In: Proceedings of the ACL, July 2002"},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Nallapati, R., Zhou, B., Gulcehre, C., Xiang, B.: Abstractive text summarization using sequence-to-sequence RNNs and beyond. arXiv preprint arXiv:1602.06023 (2016)","DOI":"10.18653\/v1\/K16-1028"},{"key":"7_CR16","doi-asserted-by":"crossref","unstructured":"Nallapati, R., Zhai, F., Zhou, B.: SummaRuNNer: a recurrent neural network based sequence model for extractive summarization of documents. In: Thirty-First AAAI Conference on Artificial Intelligence (2017)","DOI":"10.1609\/aaai.v31i1.10958"},{"key":"7_CR17","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. arXiv preprint arXiv:1910.10683 (2019)"},{"issue":"1","key":"7_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00700ED1V01Y201602HLT032","volume":"10","author":"H Saggion","year":"2017","unstructured":"Saggion, H.: Automatic text simplification. Synth. Lect. Hum. Lang. Technol. 10(1), 1\u2013137 (2017)","journal-title":"Synth. Lect. Hum. Lang. Technol."},{"key":"7_CR19","doi-asserted-by":"crossref","unstructured":"See, A., Liu, P.J., Manning, C.D.: Get to the point: Summarization with pointer-generator networks. arXiv preprint arXiv:1704.04368 (2017)","DOI":"10.18653\/v1\/P17-1099"},{"issue":"2","key":"7_CR20","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1075\/itl.165.2.06sid","volume":"165","author":"A Siddharthan","year":"2014","unstructured":"Siddharthan, A.: A survey of research on text simplification. ITL-Int. J. Appl. Linguist. 165(2), 259\u2013298 (2014)","journal-title":"ITL-Int. J. Appl. Linguist."},{"key":"7_CR21","doi-asserted-by":"crossref","unstructured":"\u0160tajner, S., Saggion, H.: Data-driven text simplification. In: Proceedings of the 27th International Conference on Computational Linguistics: Tutorial Abstracts, pp. 19\u201323 (2018)","DOI":"10.1093\/oxfordhb\/9780199573691.013.52"},{"key":"7_CR22","doi-asserted-by":"crossref","unstructured":"Sulem, E., Abend, O., Rappoport, A.: BLEU is not suitable for the evaluation of text simplification. arXiv preprint arXiv:1810.05995 (2018)","DOI":"10.18653\/v1\/D18-1081"},{"key":"7_CR23","doi-asserted-by":"crossref","unstructured":"Surya, S., Mishra, A., Laha, A., Jain, P., Sankaranarayanan, K.: Unsupervised Neural Text Simplification. arXiv preprint arXiv:1810.07931 (2018)","DOI":"10.18653\/v1\/P19-1198"},{"key":"7_CR24","unstructured":"Vinyals, O., Fortunato, M., Jaitly, N.: Pointer networks. In: Advances in Neural Information Processing Systems, pp. 2692\u20132700 (2015)"},{"key":"7_CR25","doi-asserted-by":"crossref","unstructured":"Wang, T., Chen, P., Rochford, J., Qiang, J.: Text simplification using neural machine translation. In: Thirtieth AAAI Conference on Artificial Intelligence (2016)","DOI":"10.1609\/aaai.v30i1.9933"},{"key":"7_CR26","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1162\/tacl_a_00139","volume":"3","author":"W Xu","year":"2015","unstructured":"Xu, W., Callison-Burch, C., Napoles, C.: Problems in current text simplification research: new data can help. Trans. Assoc. Comput. Linguist. 3, 283\u2013297 (2015)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"7_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, X., Lapata, M.: Sentence simplification with deep reinforcement learning. arXiv preprint arXiv:1703.10931 (2017)","DOI":"10.18653\/v1\/D17-1062"}],"container-title":["Communications in Computer and Information Science","Recent Trends in Analysis of Images, Social Networks and Texts"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-71214-3_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,22]],"date-time":"2022-12-22T09:04:53Z","timestamp":1671699893000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-71214-3_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030712136","9783030712143"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-71214-3_7","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"25 March 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIST","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Analysis of Images, Social Networks and Texts","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Moscow","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Russia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aist2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aistconf.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":"108","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":"41","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":"13","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":"38% - 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":"3.1","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":"2.33","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":"Due to the COVID-19 pandemic the conference was held online","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)"}}]}}