{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T16:46:22Z","timestamp":1749487582356,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030595050"},{"type":"electronic","value":"9783030595067"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-59506-7_28","type":"book-chapter","created":{"date-parts":[[2020,10,7]],"date-time":"2020-10-07T23:07:55Z","timestamp":1602112075000},"page":"345-356","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Cross-lingual Metaphor Paraphrase Detection \u2013 Experimental Corpus and Baselines"],"prefix":"10.1007","author":[{"given":"Martin","family":"V\u00edta","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,8]]},"reference":[{"issue":"6","key":"28_CR1","doi-asserted-by":"publisher","first-page":"922","DOI":"10.1016\/j.ipm.2018.06.005","volume":"54","author":"B Agarwal","year":"2018","unstructured":"Agarwal, B., Ramampiaro, H., Langseth, H., Ruocco, M.: A deep network model for paraphrase detection in short text messages. Inf. Process. Manag. 54(6), 922\u2013937 (2018)","journal-title":"Inf. Process. Manag."},{"key":"28_CR2","unstructured":"Agi\u0107, \u017d., Schluter, N.: Baselines and test data for cross-lingual inference. arXiv preprint \narXiv:1704.05347\n\n (2017)"},{"key":"28_CR3","doi-asserted-by":"crossref","unstructured":"Agirre, E., et al.: SemEval-2016 task 1: semantic textual similarity, monolingual and cross-lingual evaluation. In: Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pp. 497\u2013511 (2016)","DOI":"10.18653\/v1\/S16-1081"},{"key":"28_CR4","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1613\/jair.2985","volume":"38","author":"I Androutsopoulos","year":"2010","unstructured":"Androutsopoulos, I., Malakasiotis, P.: A survey of paraphrasing and textual entailment methods. J. Artif. Intell. Res. 38, 135\u2013187 (2010)","journal-title":"J. Artif. Intell. Res."},{"key":"28_CR5","unstructured":"Baran\u010d\u00edkov\u00e1, P., Bojar, O.: In search for linear relations in sentence embedding spaces. arXiv preprint \narXiv:1910.03375\n\n (2019)"},{"key":"28_CR6","doi-asserted-by":"publisher","unstructured":"Bizzoni, Y., Lappin, S.: Predicting human metaphor paraphrase judgments with deep neural networks. In: Proceedings of the Workshop on Figurative Language Processing, pp. 45\u201355. Association for Computational Linguistics, New Orleans, June 2018. \nhttps:\/\/doi.org\/10.18653\/v1\/W18-0906\n\n. \nhttps:\/\/www.aclweb.org\/anthology\/W18-0906","DOI":"10.18653\/v1\/W18-0906"},{"issue":"9","key":"28_CR7","doi-asserted-by":"publisher","first-page":"e74304","DOI":"10.1371\/journal.pone.0074304","volume":"8","author":"D Bollegala","year":"2013","unstructured":"Bollegala, D., Shutova, E.: Metaphor interpretation using paraphrases extracted from the web. PLoS ONE 8(9), e74304 (2013)","journal-title":"PLoS ONE"},{"key":"28_CR8","unstructured":"Cer, D., et al.: Universal sentence encoder. arXiv preprint \narXiv:1803.11175\n\n (2018)"},{"issue":"4","key":"28_CR9","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","volume":"40","author":"LC Chen","year":"2017","unstructured":"Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 834\u2013848 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"28_CR10","doi-asserted-by":"crossref","unstructured":"Conneau, A., et al.: XNLI: evaluating cross-lingual sentence representations. arXiv preprint \narXiv:1809.05053\n\n (2018)","DOI":"10.18653\/v1\/D18-1269"},{"key":"28_CR11","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint \narXiv:1810.04805\n\n (2018)"},{"key":"28_CR12","unstructured":"Dien, D., et al.: Vietnamese-English cross-lingual paraphrase identification using siamese recurrent architectures. In: 2019 19th International Symposium on Communications and Information Technologies (ISCIT), pp. 70\u201375. IEEE (2019)"},{"key":"28_CR13","unstructured":"Klebanov, B.B., Shutova, E., Lichtenstein, P., Muresan, S., Wee, C.: Proceedings of the Workshop on Figurative Language Processing (2018)"},{"key":"28_CR14","unstructured":"Ko\u0161arko, O., Vari\u0161, D., Popel, M.: LINDAT translation service. LINDAT\/CLARIN digital library at the Institute of Formal and Applied Linguistics (\u00daFAL), Faculty of Mathematics and Physics, Charles University (2019). \nhttp:\/\/hdl.handle.net\/11234\/1-2922"},{"key":"28_CR15","unstructured":"Lample, G., Conneau, A., Denoyer, L., Ranzato, M.: Unsupervised machine translation using monolingual corpora only. arXiv preprint \narXiv:1711.00043\n\n (2017)"},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.D.: GloVe: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"28_CR17","unstructured":"Peters, M.E., et al.: Deep contextualized word representations. arXiv preprint \narXiv:1802.05365\n\n (2018)"},{"key":"28_CR18","unstructured":"Shutova, E., Teufel, S.: Metaphor corpus annotated for source-target domain mappings. In: LREC, vol. 2, p. 2. Citeseer (2010)"},{"key":"28_CR19","unstructured":"Zhou, L., Hovy, E.: Headline summarization at ISI. In: Proceedings of the HLT-NAACL 2003 Text Summarization Workshop and Document Understanding Conference (DUC 2003), pp. 174\u2013178 (2003)"}],"container-title":["Communications in Computer and Information Science","Information and Software Technologies"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59506-7_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,7]],"date-time":"2020-10-07T23:13:09Z","timestamp":1602112389000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-59506-7_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030595050","9783030595067"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59506-7_28","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"8 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIST","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Information and Software Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kaunas","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lithuania","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":"17 October 2020","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":"icist2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icist.ktu.edu\/","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":"78","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":"23","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":"7","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":"29% - 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":"3","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)"}}]}}