{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T01:04:31Z","timestamp":1752282271191,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031289552"},{"type":"electronic","value":"9783031289569"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-28956-9_23","type":"book-chapter","created":{"date-parts":[[2023,4,7]],"date-time":"2023-04-07T19:02:26Z","timestamp":1680894146000},"page":"293-301","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["RoBERTa: An Efficient Dating Method of\u00a0Ancient Chinese Texts"],"prefix":"10.1007","author":[{"given":"Meiwei","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunhui","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Huangfu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,4,8]]},"reference":[{"issue":"4\u20135","key":"23_CR1","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1163\/156853267X00061","volume":"53","author":"WACH Dobson","year":"1967","unstructured":"Dobson, W.A.C.H.: Authenticating and dating archaic Chinese texts. Toung Pao (Second Ser.) 53(4\u20135), 233\u2013242 (1967)","journal-title":"Toung Pao (Second Ser.)"},{"issue":"4","key":"23_CR2","first-page":"9","volume":"18","author":"S Lihua","year":"2004","unstructured":"Lihua, S., Yuqin, L.: Rule-based automatic category application on text category. J. Chin. Inf. Process. 18(4), 9\u201314 (2004)","journal-title":"J. Chin. Inf. Process."},{"issue":"3","key":"23_CR3","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1145\/321075.321084","volume":"8","author":"ME Maron","year":"1961","unstructured":"Maron, M.E.: Automatic indexing: an experimental inquiry. J. ACM 8(3), 404\u2013417 (1961)","journal-title":"J. ACM"},{"issue":"1","key":"23_CR4","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"T Cover","year":"1967","unstructured":"Cover, T., Hart, P.: Nearest neighbor pattern classification. IEEE Trans. Inf. Theory 13(1), 21\u201327 (1967)","journal-title":"IEEE Trans. Inf. Theory"},{"doi-asserted-by":"crossref","unstructured":"Joachims, T.: Text categorization with support vector machines: learning with many relevant features (1998)","key":"23_CR5","DOI":"10.1007\/BFb0026683"},{"unstructured":"McCallum, A., Nigam, K.: A comparison of event models for Naive Bayes text classification (1998)","key":"23_CR6"},{"issue":"6","key":"23_CR7","first-page":"19","volume":"16","author":"L Bin","year":"2002","unstructured":"Bin, L., Tiejun, H., Jun, C., Wen, G.: A new statistical-based method in automatic text classification. J. Chin. Inf. Process. 16(6), 19 (2002)","journal-title":"J. Chin. Inf. Process."},{"doi-asserted-by":"crossref","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1746\u20131751, Doha, Qatar, October 2014","key":"23_CR8","DOI":"10.3115\/v1\/D14-1181"},{"doi-asserted-by":"crossref","unstructured":"Tang, D., Qin, B., Liu, T.: Document modeling with gated recurrent neural network for sentiment classification. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1422\u20131432, Lisbon, Portugal, September 2015","key":"23_CR9","DOI":"10.18653\/v1\/D15-1167"},{"doi-asserted-by":"crossref","unstructured":"Graves, A., Schmidhuber, J.: Framewise phoneme classification with bidirectional LSTM networks. In: Proceedings of the IEEE International Joint Conference on Neural Networks, vol. 4, pp. 2047\u20132052 (2005)","key":"23_CR10","DOI":"10.1109\/IJCNN.2005.1556215"},{"unstructured":"Vaswani, A., et al.: Attention is all you need. arXiv (2017)","key":"23_CR11"},{"unstructured":"Devlin, J., Chang, M., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171\u20134186, Minneapolis, Minnesota, June 2019","key":"23_CR12"},{"unstructured":"Liu, Y., et al.: RoBERTa: a robustly optimized BERT pretraining approach (2019)","key":"23_CR13"},{"doi-asserted-by":"crossref","unstructured":"Xuejin, Y., Huangfu, W.: A machine learning model for the dating of ancient Chinese texts. In: Proceedings of the 2019 International Conference on Asian Language Processing, pp. 115\u2013120 (2019)","key":"23_CR14","DOI":"10.1109\/IALP48816.2019.9037653"},{"unstructured":"Tan, Y.: GuwenBERT: a pre-trained language model for classical Chinese (literary Chinese). https:\/\/github.com\/Ethan-yt\/guwenbert(2021-07-06)","key":"23_CR15"}],"container-title":["Lecture Notes in Computer Science","Chinese Lexical Semantics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-28956-9_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T22:30:17Z","timestamp":1729204217000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-28956-9_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031289552","9783031289569"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-28956-9_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"8 April 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CLSW","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Workshop on Chinese Lexical Semantics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 May 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 May 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"clsw2022","order":10,"name":"conference_id","label":"Conference ID","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":"214","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":"51","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":"19","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":"24% - 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":"2","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":"8","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)"}}]}}