{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T09:47:39Z","timestamp":1770284859869,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Singapore","isbn-type":[{"value":"9789811619632","type":"print"},{"value":"9789811619649","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\/978-981-16-1964-9_9","type":"book-chapter","created":{"date-parts":[[2021,5,5]],"date-time":"2021-05-05T21:06:58Z","timestamp":1620248818000},"page":"106-118","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Learning Global Representations for Document-Level Biomedical Relation Extraction"],"prefix":"10.1007","author":[{"given":"Lishuang","family":"Li","sequence":"first","affiliation":[]},{"given":"Hongbin","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Shuang","family":"Qian","sequence":"additional","affiliation":[]},{"given":"Shiyi","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Yifan","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,5,6]]},"reference":[{"key":"9_CR1","unstructured":"Li, J., et al.: Annotating chemicals, diseases, and their interactions in biomedical literature. In: Proceedings of the Fifth BioCreative Challenge Evaluation Workshop, Seville, Spain, pp. 173\u2013182 (2015)"},{"key":"9_CR2","unstructured":"Lowe, D., O\u2019Boyle, N., Sayle, R.: LeadMine: disease identification and concept mapping using Wikipedia. In: Proceedings of the Fifth BioCreative Challenge Evaluation Workshop, Spain, pp. 240\u2013246 (2015)"},{"key":"9_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1093\/database\/bax024","volume":"2017","author":"J Gu","year":"2017","unstructured":"Gu, J., Sun, F., Qian, L., Zhou, G.: Chemical-induced disease relation extraction via convolutional neural network. Database 2017, 1\u201310 (2017)","journal-title":"Database"},{"key":"9_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1093\/database\/baw036","volume":"2016","author":"J Xu","year":"2016","unstructured":"Xu, J., Wu, Y., Zhang, Y., Wang, J., Lee, H.J., Xu, H.: CD-REST: a system for extracting chemical-induced disease relation in literature. Database 2016, 1\u20139 (2016)","journal-title":"Database"},{"key":"9_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1093\/database\/baw048","volume":"2016","author":"H Zhou","year":"2016","unstructured":"Zhou, H., Deng, H., Chen, L., Yang, Y., Jia, C., Huang, D.: Exploiting syntactic and semantics information for chemical\u2013disease relation extraction. Database 2016, 1\u201310 (2016)","journal-title":"Database"},{"issue":"2","key":"9_CR6","first-page":"45","volume":"18","author":"H Li","year":"2018","unstructured":"Li, H., Yang, M., Chen, Q., Tang, B., Wang, X., Yan, J.: Chemical-induced disease extraction via recurrent piecewise convolutional neural networks. BMC Med. Inf. Decis. Making 18(2), 45\u201351 (2018)","journal-title":"BMC Med. Inf. Decis. Making"},{"key":"9_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jbi.2018.05.001","volume":"83","author":"W Zheng","year":"2018","unstructured":"Zheng, W., et al.: An effective neural model extracting document-level chemical-induced disease relations from biomedical literature. J. Biomed. Inf. 83, 1\u20139 (2018)","journal-title":"J. Biomed. Inf."},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Verga, P., Strubell, E., McCallum, A.: Simultaneously self-attending to all mentions for full-abstract biological relation extraction. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, New Orleans, Louisiana, pp. 872\u2013884 (2018)","DOI":"10.18653\/v1\/N18-1080"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Sahu, S.K., Christopoulou, F., Miwa, M., Ananiadou, S.: Inter-sentence relation extraction with document-level graph convolutional neural network. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, pp. 4309\u20134316 (2019)","DOI":"10.18653\/v1\/P19-1423"},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Christopoulou, F., Miwa, M., Ananiadou, S.: Connecting the dots: document-level neural relation extraction with edge-oriented graphs. In: Conference on Empirical Methods in Natural Language Processing, Hong Kong, China, pp. 4924\u20134935 (2019)","DOI":"10.18653\/v1\/D19-1498"},{"key":"9_CR11","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.jbi.2015.03.002","volume":"55","author":"S Kim","year":"2015","unstructured":"Kim, S., Liu, H., Yeganova, L., Wilbur, W.J.: Extracting drug-drug interactions from literature using a rich feature-based linear kernel approach. J. Biomed. Inf. 55, 23\u201330 (2015)","journal-title":"J. Biomed. Inf."},{"key":"9_CR12","first-page":"6918381","volume":"2016","author":"S Liu","year":"2016","unstructured":"Liu, S., Tang, B., Chen, Q., Wang, X.: Drug-Drug interaction extraction via convolutional neural networks. Comput. Math. Methods Med. 2016, 6918381\u20136918388 (2016)","journal-title":"Comput. Math. Methods Med."},{"key":"9_CR13","unstructured":"Masaki, A., Miwa, M., Sasaki, Y.: Extracting drug-drug interactions with attention CNNs. In: Proceedings of the BioNLP workshop, Vancouver, Canada, pp. 9\u201318 (2017)"},{"key":"9_CR14","doi-asserted-by":"crossref","unstructured":"Cho, K., Mer\u00efenboer, V., Gulcehre, C., Bougares, F., Bougares, H., Bengio, Y.: Learning phrase representations using RNN encoder\u2013decoder for statistical machine translation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, Doha, Qatar, pp. 1724\u20131734 (2014)","DOI":"10.3115\/v1\/D14-1179"},{"key":"9_CR15","doi-asserted-by":"crossref","unstructured":"Chen, Q., Zhu, X., Ling, Z., Wei, S., Jiang, H., Inkpen, D.: Enhanced LSTM for natural language inference. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Vancouver, Canada, pp. 1657\u20131668 (2017)","DOI":"10.18653\/v1\/P17-1152"},{"key":"9_CR16","doi-asserted-by":"publisher","first-page":"786","DOI":"10.1093\/nar\/gkn580","volume":"27","author":"AP Davis","year":"2009","unstructured":"Davis, A.P., Murphy, C.G., Saracenirichards, C.A., Rosenstein, M.C., Wiegers, T.C., Mattingly, C.J.: Comparative toxicogenomics database: a knowledgebase and discovery tool for chemical\u2013gene\u2013disease networks. Nucleic Acids Res. 27, 786\u2013792 (2009)","journal-title":"Nucleic Acids Res."},{"key":"9_CR17","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, Doha, Qatar, pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"}],"container-title":["Communications in Computer and Information Science","Knowledge Graph and Semantic Computing: Knowledge Graph and Cognitive Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-1964-9_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,5]],"date-time":"2021-05-05T21:08:38Z","timestamp":1620248918000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-1964-9_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811619632","9789811619649"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-1964-9_9","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"6 May 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CCKS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China Conference on Knowledge Graph and Semantic Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanchang","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":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 November 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 November 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccks2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/sigkg.cn\/ccks2020\/","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":"173","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":"26","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":"0","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":"15% - 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":"5.5","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)"}}]}}