{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T19:45:46Z","timestamp":1775245546013,"version":"3.50.1"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030017156","type":"print"},{"value":"9783030017163","type":"electronic"}],"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\/978-3-030-01716-3_13","type":"book-chapter","created":{"date-parts":[[2018,10,6]],"date-time":"2018-10-06T10:11:06Z","timestamp":1538820666000},"page":"147-158","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Attention-Based Convolutional Neural Networks for Chinese Relation Extraction"],"prefix":"10.1007","author":[{"given":"Wenya","family":"Wu","sequence":"first","affiliation":[]},{"given":"Yufeng","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Jinan","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Yujie","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,10,7]]},"reference":[{"key":"13_CR1","unstructured":"Zeng, D., Liu, K., Lai, S., Zhou, G., Zhao, J.: Relation classification via convolutional deep neural network. In: Proceedings of COLING, pp. 2335\u20132344 (2014)"},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Zeng, D., Liu, K., Chen, Y., Zhao, J.: Distant supervision for relation extraction via piecewise convolutional neural networks. In: Proceedings of EMNLP, pp. 17\u201321. Association for Computational Linguistics, Stroudsburg (2015)","DOI":"10.18653\/v1\/D15-1203"},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Lin, Y., Shen, S., Liu, Z., Luan, H., Sun, M.: Neural relation extraction with selective attention over instances. In: Proceedings of ACL, pp. 2124\u20132133. Association for Computational Linguistics, Berlin (2016)","DOI":"10.18653\/v1\/P16-1200"},{"key":"13_CR4","unstructured":"Jiang, X., Wang, Q., Li, P., Wang, B.: Relation extraction with multi-instance multi-label convolutional neural networks. In: Proceedings of COLING, pp. 1471\u20131480 (2016)"},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"dos Santos, C.N., Xiang, B., Zhou, B.: Classifying relations by ranking with convolutional neural networks. In: Proceedings of ACL (2015)","DOI":"10.3115\/v1\/P15-1061"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Liu, Y., Wei, F., Li, S., Ji, H., Zhou, M., Wang, H.: A dependency-based neural network for relation classification. Comput. Sci. (2015)","DOI":"10.3115\/v1\/P15-2047"},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Bunescu, R.C., Mooney, R.J.: A shortest path dependency kernel for relation extraction. In: Proceedings of HLT\/EMNLP, pp. 724\u2013731. Association for Computational Linguistics, Vancouver (2005)","DOI":"10.3115\/1220575.1220666"},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Wang, L., Cao, Z., Melo, G.D., Liu, Z.: Relation classification via multi-level attention CNNs. In: Proceedings of ACL, pp. 1298\u20131307. Association for Computational Linguistics, Berlin (2016)","DOI":"10.18653\/v1\/P16-1123"},{"key":"13_CR9","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1007\/978-981-10-7134-8_3","volume-title":"Machine Translation","author":"S Li","year":"2017","unstructured":"Li, S., Xu, J., Zhang, Y., Chen, Y.: A method of unknown words processing for neural machine translation using HowNet. In: Wong, D.F., Xiong, D. (eds.) CWMT 2017. CCIS, vol. 787, pp. 20\u201329. Springer, Singapore (2017). https:\/\/doi.org\/10.1007\/978-981-10-7134-8_3"},{"key":"13_CR10","unstructured":"Sun, J., Gu, X., Li, Y., Xu, W.: Chinese entity relation extraction algorithms based on COAE2016 datasets. J. Shandong Univ. (Nat. Sci.) 52(9), 7\u201312 (2017)"},{"issue":"2","key":"13_CR11","first-page":"91","volume":"28","author":"D Liu","year":"2014","unstructured":"Liu, D., Peng, C., Qian, L., Zhou, G.: The effect of Tongyici Cilin in Chinese entity relation extraction. J. Chin. Inf. Process. 28(2), 91\u201399 (2014)","journal-title":"J. Chin. Inf. Process."},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Cai, R., Zhang, X., Wang, H.: Bidirectional recurrent convolutional neural network for relation classification. In: Proceedings of ACL, pp. 756\u2013765. Association for Computational Linguistics, Berlin (2016)","DOI":"10.18653\/v1\/P16-1072"},{"issue":"7","key":"13_CR13","first-page":"941","volume":"71","author":"K Xu","year":"2015","unstructured":"Xu, K., Feng, Y., Huang, S., Zhao, D.: Semantic relation classification via convolutional neural networks with simple negative sampling. Comput. Sci. 71(7), 941\u2013949 (2015)","journal-title":"Comput. Sci."},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Zhou, P., et al.: Attention-based bidirectional long short-term memory networks for relation classification. In: Proceedings of ACL, pp. 207\u2013212. Association for Computational Linguistics, Berlin (2016)","DOI":"10.18653\/v1\/P16-2034"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Hashimoto, K., Miwa, M., Tsuruoka, Y., Chikayama, T.: Simple customization of recursive neural networks for semantic relation classification. In: Proceedings of EMNLP, pp. 1372\u20131376. Association for Computational Linguistics, Seattle (2013)","DOI":"10.18653\/v1\/D13-1137"},{"key":"13_CR16","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. JMLR 12, 2493\u20132537 (2011)","journal-title":"JMLR"},{"key":"13_CR17","unstructured":"Socher, R., Huval, B., Manning, C.D., Ng, A.Y.: Semantic compositionality through recursive matrix-vector spaces. In: Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 1201\u20131211 (2012)"},{"key":"13_CR18","unstructured":"Rink, B., Harabagiu, S.: UTD: classifying semantic relations by combining lexical and semantic resources. In: Proceedings of the 5th International Workshop on Semantic Evaluation, pp. 256\u2013259. Association for Computational Linguistics (2010)"}],"container-title":["Lecture Notes in Computer Science","Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01716-3_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T18:46:56Z","timestamp":1775242016000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-01716-3_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030017156","9783030017163"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01716-3_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"7 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CCL","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China National Conference on Chinese Computational Linguistics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Changsha","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":"19 October 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 October 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cncl2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.cips-cl.org\/static\/CCL2018\/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":"www.softconf.com","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"84","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":"33","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":"39% - 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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}