{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T14:04:10Z","timestamp":1742997850512,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030029333"},{"type":"electronic","value":"9783030029340"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","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":[[2018]]},"DOI":"10.1007\/978-3-030-02934-0_19","type":"book-chapter","created":{"date-parts":[[2018,11,19]],"date-time":"2018-11-19T05:42:53Z","timestamp":1542606173000},"page":"203-214","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Deep Learning Based Temporal Information Extraction Framework on Chinese Electronic Health Records"],"prefix":"10.1007","author":[{"given":"Bing","family":"Tian","sequence":"first","affiliation":[]},{"given":"Chunxiao","family":"Xing","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,11,20]]},"reference":[{"issue":"3","key":"19_CR1","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1109\/TKDE.2017.2773493","volume":"30","author":"X Ao","year":"2018","unstructured":"Ao, X., Luo, P., Wang, J., Zhuang, F., He, Q.: Mining precise-positioning episode rules from event sequences. IEEE Trans. Knowl. Data Eng. 30(3), 530\u2013543 (2018)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"19_CR2","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1146\/annurev-publhealth-031914-122747","volume":"36","author":"GS Birkhead","year":"2015","unstructured":"Birkhead, G.S., Klompas, M., Shah, N.R.: Uses of electronic health records for public health surveillance to advance public health. Annu. Rev. Public Health 36, 345\u2013359 (2015)","journal-title":"Annu. Rev. Public Health"},{"key":"19_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1007\/978-3-319-32025-0_30","volume-title":"Database Systems for Advanced Applications","author":"X Chen","year":"2016","unstructured":"Chen, X., Zhang, Y., Xu, J., Xing, C., Chen, H.: Deep learning based topic identification and categorization: mining diabetes-related topics on Chinese health websites. In: Navathe, S.B., Wu, W., Shekhar, S., Du, X., Wang, X.S., Xiong, H. (eds.) DASFAA 2016. LNCS, vol. 9642, pp. 481\u2013500. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-32025-0_30"},{"key":"19_CR4","doi-asserted-by":"publisher","first-page":"S48","DOI":"10.1016\/j.jbi.2013.09.010","volume":"46","author":"Y Cheng","year":"2013","unstructured":"Cheng, Y., Anick, P., Hong, P., Xue, N.: Temporal relation discovery between events and temporal expressions identified in clinical narrative. J. Biomed. Inform. 46, S48\u2013S53 (2013)","journal-title":"J. Biomed. Inform."},{"issue":"5","key":"19_CR5","first-page":"843","volume":"20","author":"C Cherry","year":"2013","unstructured":"Cherry, C., Zhu, X., Martin, J.D., de Bruijn, B.: \u00c0 la recherche du temps perdu: extracting temporal relations from medical text in the 2012 i2b2 NLP challenge. JAMIA 20(5), 843\u2013848 (2013)","journal-title":"JAMIA"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Cho, K., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014)","DOI":"10.3115\/v1\/D14-1179"},{"issue":"Aug","key":"19_CR7","first-page":"2493","volume":"12","author":"R Collobert","year":"2011","unstructured":"Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., Kuksa, P.: Natural language processing (almost) from scratch. J. Mach. Learn. Res. 12(Aug), 2493\u20132537 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Dligach, D., Miller, T., Lin, C., Bethard, S., Savova, G.: Neural temporal relation extraction. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, Short Papers, vol. 2, pp. 746\u2013751 (2017)","DOI":"10.18653\/v1\/E17-2118"},{"key":"19_CR9","doi-asserted-by":"publisher","unstructured":"D\u2019Souza, J., Ng, V.: Temporal relation identification and classification in clinical notes. In: ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013, Washington, DC, USA, 22\u201325 September 2013, p. 392 (2013). https:\/\/doi.org\/10.1145\/2506583.2506654","DOI":"10.1145\/2506583.2506654"},{"issue":"1","key":"19_CR10","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1186\/s12859-014-0365-3","volume":"16","author":"D Hristovski","year":"2015","unstructured":"Hristovski, D., Dinevski, D., Kastrin, A., Rindflesch, T.C.: Biomedical question answering using semantic relations. BMC Bioinform. 16(1), 6 (2015)","journal-title":"BMC Bioinform."},{"key":"19_CR11","unstructured":"Lafferty, J., McCallum, A., Pereira, F.C.: Conditional random fields: probabilistic models for segmenting and labeling sequence data (2001)"},{"issue":"2","key":"19_CR12","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1504\/IJES.2017.083730","volume":"9","author":"L Li","year":"2017","unstructured":"Li, L., Zhang, J., He, Y., Wang, H.: Chinese temporal relation resolution based on Chinese-English parallel corpus. Int. J. Embed. Syst. 9(2), 101\u2013111 (2017)","journal-title":"Int. J. Embed. Syst."},{"key":"19_CR13","first-page":"322","volume":"2017","author":"C Lin","year":"2017","unstructured":"Lin, C., Miller, T., Dligach, D., Bethard, S., Savova, G.: Representations of time expressions for temporal relation extraction with convolutional neural networks. BioNLP 2017, 322\u2013327 (2017)","journal-title":"BioNLP"},{"key":"19_CR14","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in Neural Information Processing Systems, pp. 3111\u20133119 (2013)"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Mirza, P., Tonelli, S.: Classifying temporal relations with simple features. In: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, pp. 308\u2013317 (2014)","DOI":"10.3115\/v1\/E14-1033"},{"key":"19_CR16","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1016\/j.jbi.2014.06.009","volume":"52","author":"R Mishra","year":"2014","unstructured":"Mishra, R., et al.: Text summarization in the biomedical domain: a systematic review of recent research. J. Biomed. Inform. 52, 457\u2013467 (2014)","journal-title":"J. Biomed. Inform."},{"key":"19_CR17","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1007\/978-1-4471-4474-8_22","volume-title":"Biomedical Informatics: Computer Applications in Health Care and Biomedicine","author":"MA Musen","year":"2014","unstructured":"Musen, M.A., Middleton, B., Greenes, R.A.: Clinical decision-support systems. In: Shortliffe, E.H., Cimino, J.J. (eds.) Biomedical Informatics: Computer Applications in Health Care and Biomedicine, pp. 643\u2013674. Springer, London (2014). https:\/\/doi.org\/10.1007\/978-1-4471-4474-8_22"},{"issue":"4","key":"19_CR18","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1109\/TASLP.2016.2520371","volume":"24","author":"H Palangi","year":"2016","unstructured":"Palangi, H., et al.: Deep sentence embedding using long short-term memory networks: analysis and application to information retrieval. IEEE\/ACM Trans. Audio, Speech Lang. Process. (TASLP) 24(4), 694\u2013707 (2016)","journal-title":"IEEE\/ACM Trans. Audio, Speech Lang. Process. (TASLP)"},{"issue":"5","key":"19_CR19","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1136\/amiajnl-2013-001628","volume":"20","author":"W Sun","year":"2013","unstructured":"Sun, W., Rumshisky, A., Uzuner, O.: Evaluating temporal relations in clinical text: 2012 i2b2 challenge. J. Am. Med. Inform. Assoc. 20(5), 806\u2013813 (2013)","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"19_CR20","first-page":"828","volume":"20","author":"B Tang","year":"2013","unstructured":"Tang, B., Wu, Y., Jiang, M., Chen, Y., Denny, J.C., Xu, H.: A hybrid system for temporal information extraction from clinical text. JAMIA 20(5), 828\u2013835 (2013)","journal-title":"JAMIA"},{"key":"19_CR21","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 (2015)","DOI":"10.18653\/v1\/D15-1167"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Tourille, J., Ferret, O., Neveol, A., Tannier, X.: Neural architecture for temporal relation extraction: a Bi-LSTM approach for detecting narrative containers. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Short Papers, vol. 2, pp. 224\u2013230 (2017)","DOI":"10.18653\/v1\/P17-2035"},{"key":"19_CR23","doi-asserted-by":"crossref","unstructured":"Wang, J., Wang, Z., Zhang, D., Yan, J.: Combining knowledge with deep convolutional neural networks for short text classification. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence, pp. 2915\u20132921. AAAI Press (2017)","DOI":"10.24963\/ijcai.2017\/406"},{"issue":"5","key":"19_CR24","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1136\/amiajnl-2012-001607","volume":"20","author":"Y Xu","year":"2013","unstructured":"Xu, Y., Wang, Y., Liu, T., Tsujii, J., Chang, E.I.C.: An end-to-end system to identify temporal relation in discharge summaries: 2012 i2b2 challenge. J. Am. Med. Inform. Assoc. 20(5), 849\u2013858 (2013)","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"19_CR25","first-page":"849","volume":"20","author":"Y Xu","year":"2013","unstructured":"Xu, Y., Wang, Y., Liu, T., Tsujii, J., Chang, E.I.: An end-to-end system to identify temporal relation in discharge summaries: 2012 i2b2 challenge. JAMIA 20(5), 849\u2013858 (2013)","journal-title":"JAMIA"},{"key":"19_CR26","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Li, X., Wang, J., Zhang, Y., Xing, C., Yuan, X.: An efficient framework for exact set similarity search using tree structure indexes. In: 2017 IEEE 33rd International Conference on Data Engineering (ICDE), pp. 759\u2013770. IEEE (2017)","DOI":"10.1109\/ICDE.2017.127"},{"key":"19_CR27","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1007\/978-3-319-27194-1_55","volume-title":"Chinese Lexical Semantics","author":"X Zheng","year":"2015","unstructured":"Zheng, X., Li, P., Huang, Y., Zhu, Q.: An approach to recognize temporal relations between Chinese events. In: Lu, Q., Gao, H. (eds.) Chinese Lexical Semantics. LNCS (LNAI), vol. 9332, pp. 543\u2013553. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-27194-1_55"}],"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\/978-3-030-02934-0_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T18:42:16Z","timestamp":1710268936000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-02934-0_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030029333","9783030029340"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-02934-0_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"20 November 2018","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":"Taiyuan","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":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wisa22018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/jisq.nju.edu.cn\/wisa2018\/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":"103","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":"29","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":"16","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":"28% - 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":"4","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)"}}]}}