{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T06:09:59Z","timestamp":1776838199570,"version":"3.51.2"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030875701","type":"print"},{"value":"9783030875718","type":"electronic"}],"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\/978-3-030-87571-8_28","type":"book-chapter","created":{"date-parts":[[2021,9,16]],"date-time":"2021-09-16T09:02:47Z","timestamp":1631782967000},"page":"323-334","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Constructing Chinese Historical Literature Knowledge Graph Based on\u00a0BERT"],"prefix":"10.1007","author":[{"given":"Qingyan","family":"Guo","sequence":"first","affiliation":[]},{"given":"Yang","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Guanzhong","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Zijun","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Zijing","family":"Ji","sequence":"additional","affiliation":[]},{"given":"Yuxin","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,9,17]]},"reference":[{"key":"28_CR1","doi-asserted-by":"crossref","unstructured":"Bollacker, K., Evans, C., Paritosh, P., Sturge, T., Taylo, J.: Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 1247\u20131250 (2008)","DOI":"10.1145\/1376616.1376746"},{"key":"28_CR2","doi-asserted-by":"crossref","unstructured":"Christopoulou, F., Miwa, M., Ananiadou, S.: A walk-based model on entity graphs for relation extraction. arXiv preprint arXiv:1902.07023 (2019)","DOI":"10.18653\/v1\/P18-2014"},{"key":"28_CR3","unstructured":"Collins, M., Singer, Y.: Unsupervised models for named entity classification. In: 1999 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (1999)"},{"key":"28_CR4","unstructured":"Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., Kuksa, P.: Natural language processing (almost) from scratch. J. Mach. Learn. Res. 12, 2493\u20132537 (2011)"},{"key":"28_CR5","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":"28_CR6","unstructured":"Gao, Y., Liang, J., Han, B., Yakout, M., Mohamed, A.: Building a large-scale, accurate and fresh knowledge graph. In: KDD-2018, Tutorial, vol. 39, pp. 1939\u20131374 (2018)"},{"key":"28_CR7","unstructured":"Hashimoto, K., Miwa, M., Tsuruoka, Y., Chikayama, T.: Simple customization of recursive neural networks for semantic relation classification. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp. 1372\u20131376 (2013)"},{"issue":"8","key":"28_CR8","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"28_CR9","unstructured":"Huang, Z., Xu, W., Yu, K.: Bidirectional LSTM-CRF models for sequence tagging. arXiv preprint arXiv:1508.01991 (2015)"},{"key":"28_CR10","doi-asserted-by":"crossref","unstructured":"Katiyar, A., Cardie, C.: Investigating LSTMs for joint extraction of opinion entities and relations. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 919\u2013929 (2016)","DOI":"10.18653\/v1\/P16-1087"},{"key":"28_CR11","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"28_CR12","unstructured":"Lafferty, J., McCallum, A., Pereira, F.C.: Conditional random fields: probabilistic models for segmenting and labeling sequence data (2001)"},{"key":"28_CR13","unstructured":"Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., Soricut, R.: Albert: a lite BERT for self-supervised learning of language representations. arXiv preprint arXiv:1909.11942 (2019)"},{"issue":"3","key":"28_CR14","doi-asserted-by":"publisher","first-page":"1450","DOI":"10.1007\/s11227-017-2229-x","volume":"76","author":"J Li","year":"2020","unstructured":"Li, J., et al.: WCP-RNN: a novel RNN-based approach for bio-NER in Chinese EMRs. J. Supercomput. 76(3), 1450\u20131467 (2020)","journal-title":"J. Supercomput."},{"key":"28_CR15","unstructured":"Liu, Y., et al.: Roberta: a robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692 (2019)"},{"key":"28_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/978-3-642-25093-4_14","volume-title":"The Semantic Web \u2013 ISWC 2011","author":"X Niu","year":"2011","unstructured":"Niu, X., Sun, X., Wang, H., Rong, S., Qi, G., Yu, Y.: Zhishi.me - weaving Chinese linking open data. In: Aroyo, L., et al. (eds.) ISWC 2011. LNCS, vol. 7032, pp. 205\u2013220. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-25093-4_14"},{"key":"28_CR17","unstructured":"Peters, M.E., et al.: Deep contextualized word representations. arXiv preprint arXiv:1802.05365 (2018)"},{"key":"28_CR18","unstructured":"Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Improving language understanding by generative pre-training (2018)"},{"key":"28_CR19","doi-asserted-by":"crossref","unstructured":"Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Proceedings of the 16th International Conference on World Wide Web, pp. 697\u2013706 (2007)","DOI":"10.1145\/1242572.1242667"},{"key":"28_CR20","unstructured":"Sun, Y., et al.: ERNIE: enhanced representation through knowledge integration. arXiv preprint arXiv:1904.09223 (2019)"},{"key":"28_CR21","unstructured":"Vaswani, A., et al.: Attention is all you need. arXiv preprint arXiv:1706.03762 (2017)"},{"key":"28_CR22","doi-asserted-by":"crossref","unstructured":"Wang, L., Cao, Z., De Melo, G., Liu, Z.: Relation classification via multi-level attention CNNs. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1298\u20131307 (2016)","DOI":"10.18653\/v1\/P16-1123"},{"key":"28_CR23","unstructured":"Wang, Z., et al.: XLore: a large-scale English-Chinese bilingual knowledge graph. In: International Semantic Web Conference (Posters & Demos), vol. 1035, pp. 121\u2013124 (2013)"},{"key":"28_CR24","unstructured":"Wikipedia contributors: Named-entity recognition \u2013 Wikipedia, the free encyclopedia. https:\/\/en.wikipedia.org\/w\/index.php?title=Named-entity_recognition&oldid=959772078 (2020). Accessed 20 May 2021"},{"key":"28_CR25","unstructured":"Wikipedia contributors: Yellow emperor \u2013 Wikipedia, the free encyclopedia (2021). https:\/\/en.wikipedia.org\/w\/index.php?title=Yellow_Emperor&oldid=1038043350. Accessed 14 Aug 2021"},{"key":"28_CR26","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1007\/978-3-319-60045-1_44","volume-title":"Advances in Artificial Intelligence: From Theory to Practice","author":"B Xu","year":"2017","unstructured":"Xu, B., et al.: CN-DBpedia: a never-ending Chinese knowledge extraction system. In: Benferhat, S., Tabia, K., Ali, M. (eds.) IEA\/AIE 2017. LNCS (LNAI), vol. 10351, pp. 428\u2013438. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-60045-1_44"},{"key":"28_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1007\/978-3-030-60029-7_27","volume-title":"Web Information Systems and Applications","author":"P Yu","year":"2020","unstructured":"Yu, P., Wang, X.: BERT-based named entity recognition in Chinese twenty-four histories. In: Wang, G., Lin, X., Hendler, J., Song, W., Xu, Z., Liu, G. (eds.) WISA 2020. LNCS, vol. 12432, pp. 289\u2013301. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-60029-7_27"},{"key":"28_CR28","unstructured":"Zeng, D., Liu, K., Lai, S., Zhou, G., Zhao, J.: Relation classification via convolutional deep neural network. In: Proceedings of COLING 2014, The 25th International Conference on Computational Linguistics: Technical Papers, pp. 2335\u20132344 (2014)"},{"key":"28_CR29","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1007\/978-3-319-46128-1_28","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"S Zheng","year":"2016","unstructured":"Zheng, S., et al.: Joint learning of entity semantics and relation pattern for relation extraction. In: Frasconi, P., Landwehr, N., Manco, G., Vreeken, J. (eds.) ECML PKDD 2016. LNCS (LNAI), vol. 9851, pp. 443\u2013458. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46128-1_28"}],"container-title":["Lecture Notes in Computer Science","Web Information Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-87571-8_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T17:53:18Z","timestamp":1709833998000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-87571-8_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030875701","9783030875718"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-87571-8_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"17 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WISA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Web Information Systems and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kaifeng","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wisa22021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.wisa.org.cn\/wisa2021\/index.html","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":"206","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":"49","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":"18","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":"6,5","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}