{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:42:44Z","timestamp":1775144564333,"version":"3.50.1"},"publisher-location":"Cham","reference-count":52,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030339814","type":"print"},{"value":"9783030339821","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-33982-1_5","type":"book-chapter","created":{"date-parts":[[2019,10,31]],"date-time":"2019-10-31T17:27:48Z","timestamp":1572542868000},"page":"52-66","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A Survey of Relation Extraction of Knowledge Graphs"],"prefix":"10.1007","author":[{"given":"Aoran","family":"Li","sequence":"first","affiliation":[]},{"given":"Xinmeng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Wenhuan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Anman","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Bohan","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,11,1]]},"reference":[{"key":"5_CR1","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":"5_CR2","doi-asserted-by":"crossref","unstructured":"Niu, X., Sun, X.R., Wang, H.F., et al.: Zhishi.meweaving Chinese linking open data. In: Proceedings of the 10th International Semantic Web Conference, Bonn, Germany, pp. 205\u2013220 (2011)","DOI":"10.1007\/978-3-642-25093-4_14"},{"key":"5_CR3","doi-asserted-by":"publisher","unstructured":"Pan, J.Z., Horrocks, I.: RDFS(FA): connecting RDF(S) and OWL DL. IEEE Trans. Knowl. Data Eng. 19(2), 192\u2013206 (2007). https:\/\/doi.org\/10.1109\/TKDE.2007.37","DOI":"10.1109\/TKDE.2007.37"},{"key":"5_CR4","unstructured":"Mcguiness, D.L., Harmelen, F.: OWL Web ontology language overview. W3C Recomm. 63(45), 990\u2013996 (2004)"},{"issue":"3","key":"5_CR5","first-page":"582","volume":"53","author":"L Qiao","year":"2016","unstructured":"Qiao, L., Yang, L., Hong, D., et al.: Knowledge graph construction techniques. J. Comput. Res. Dev. 53(3), 582\u2013600 (2016). (in Chinese)","journal-title":"J. Comput. Res. Dev."},{"key":"5_CR6","unstructured":"Zhang, C., Chang, L., Wang, W., Chen, H., Bin, C.: Question and answer over fine-grained knowledge graph based on BiLSTM-CRF (2019)"},{"key":"5_CR7","unstructured":"Proceedings of the 6th Message Understanding Conference (MUC - 7). National Institute of Standars and Technology (1998)"},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Suchanek, F.M., Kasneci, G., Weikum, G.: YAGO: a core of semantic knowledge unifying WordNet and Wikipedia. In: Proceedings of WWW (2007)","DOI":"10.1145\/1242572.1242667"},{"key":"5_CR9","unstructured":"Banko, M., Cafarella, M.J., Soderland, S., et al.: Open information extraction for the web. In: Proceedings of the 20th Int Joint Conf on Artificial Intelligence, pp. 2670\u20132676. ACM, New York (2007)"},{"key":"5_CR10","first-page":"1","volume":"4","author":"B Yang","year":"2014","unstructured":"Yang, B., Cai, D.-F., Yang, H.: Progress in open information extraction. J. Chin. Inf. Process. 4, 1\u201311 (2014)","journal-title":"J. Chin. Inf. Process."},{"issue":"1","key":"5_CR11","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.artint.2005.03.001","volume":"165","author":"O Etzioni","year":"2005","unstructured":"Etzioni, O., Cafarella, M., Downey, D., et al.: Unsupervised named-entity extraction from the web: an experimental study. Artif. Intell. 165(1), 91\u2013134 (2005)","journal-title":"Artif. Intell."},{"key":"5_CR12","unstructured":"Banko, M., Cafarella, M.J., Soderland, S., et al.: Open information extraction from the web. In: Proceedings of IJCAI (2007)"},{"key":"5_CR13","unstructured":"Banko, M., Etzioni, O.: The tradeoffs between open and traditional relation extraction. In: Proceedings of Annual Meeting of the Association for Computational Linguistics (2008)"},{"key":"5_CR14","unstructured":"Wu, F., Weld, D.S.: Open information extraction using Wikipedia. In: Proceedings of Annual Meeting of the Association for Computational Linguistics, pp. 118\u2013127 (2010)"},{"key":"5_CR15","unstructured":"Fader, A., Soderland, S., Etzioni, O.: Identifying relations for open information extraction. In: Proceedings of Conference on Empirical Methods in Natural Language Processing (2011)"},{"key":"5_CR16","unstructured":"Etzioni, O., Fader, A., Christensen, J., et al.: Open information extraction: the second generation. In: Proceedings of International Joint Conference on Artificial Intelligence (2011)"},{"issue":"8","key":"5_CR17","first-page":"18","volume":"168","author":"J Xu","year":"2008","unstructured":"Xu, J., Zhang, Z., Wu, Z.: Review on techniques of entity relation extraction. New Technol. Libr. Inf. Serv. 168(8), 18\u201323 (2008)","journal-title":"New Technol. Libr. Inf. Serv."},{"key":"5_CR18","unstructured":"Gudovskiy, D., Hodgkinson, A.: Explanation-based attention for semi-supervised deep active learning (2019)"},{"key":"5_CR19","unstructured":"Wang, Z., Schaul, T., Hessel, M., van Hasselt, H., Lanctot, M.: Dueling network architectures for deep reinforcement learning (2019)"},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Hasegawa, T., Sekine, S., Grishman, R.: Discovering relations among named entities from large corpora. In: Proceedings of ACL-2004, pp. 415\u2013422 (2004)","DOI":"10.3115\/1218955.1219008"},{"key":"5_CR21","unstructured":"Socher, R., Chen, D., Manning, C.D., Ng, A.Y.: Reasoning with neural tensor networks for knowledge base completion (2013)"},{"key":"5_CR22","doi-asserted-by":"crossref","unstructured":"Bordes, A., Weston, J., Collobert, R., Bengio, Y.: Learning structured embeddings of knowledge bases. In: AAAI (2011)","DOI":"10.1609\/aaai.v25i1.7917"},{"key":"5_CR23","unstructured":"Jenatton, R., Le Roux, N., Bordes, A., Obozinski, G.: A latent factor model for highly multi-relational data. In: NIPS (2012)"},{"key":"5_CR24","doi-asserted-by":"crossref","unstructured":"Heck, L., Hakkani-T\u00fcr, D., Tur, G.: Leveraging knowledge graphs for web-scale unsupervised semantic parsing. In: ISCA (2013)","DOI":"10.21437\/Interspeech.2013-401"},{"key":"5_CR25","unstructured":"Luus, F., Khan, N., Akhalwaya, I.: Active learning with TensorBoard projector (2019)"},{"key":"5_CR26","unstructured":"Liu, F., Zhong, Z., Lei, L., Wu, Y.: Entity relation extraction method based on machine learning (2013)"},{"key":"5_CR27","doi-asserted-by":"crossref","unstructured":"Xia, S., Lehong, D.: Feature-based approach to Chinese term relation extraction In: 2009 International Conference on Signal Processing Systems, pp. 410\u2013414 (2009)","DOI":"10.1109\/ICSPS.2009.79"},{"key":"5_CR28","doi-asserted-by":"crossref","unstructured":"Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines. Cambridge University Press, Cambridge University (2000)","DOI":"10.1017\/CBO9780511801389"},{"key":"5_CR29","unstructured":"Zhang, T.: Regularized winnow methods. In: Advances in Neural Information Processing Systems 13, pp. 703\u2013709 (2001)"},{"key":"5_CR30","doi-asserted-by":"crossref","unstructured":"Dong, X.L., Gabrilovich, E., Heitz, G.: Knowledge vault: a web-scale approach to probabilistic knowledge fusion. In: KDD (2014)","DOI":"10.1145\/2623330.2623623"},{"key":"5_CR31","unstructured":"Zhou, Z.-H.: Cooperative Training Style in Semi-Supervised Learning. Machine Learning and Its Applications, pp. 259\u2013275. Tsinghua University Press, Beijing (2007)"},{"key":"5_CR32","doi-asserted-by":"crossref","unstructured":"Chapelle, O., Sch\u00f6lkopf, B., Zien, A. (eds.): Semi-Supervised Learning (2006). The MIT Press, Cambridge","DOI":"10.7551\/mitpress\/9780262033589.001.0001"},{"key":"5_CR33","doi-asserted-by":"crossref","unstructured":"Pise, N.N., Kulkarni, P.: A survey of semi-supervised learning methods. In: 2008 International Conference on Computational Intelligence and Security (2008)","DOI":"10.1109\/CIS.2008.204"},{"issue":"11","key":"5_CR34","doi-asserted-by":"publisher","first-page":"1529","DOI":"10.1109\/TKDE.2005.186","volume":"17","author":"Z-H Zhou","year":"2005","unstructured":"Zhou, Z.-H., Li, M.: Tri-training: exploiting unlabeled data using three classifiers. IEEE Trans. Knowl. Data Eng. 17(11), 1529\u20131541 (2005)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"11","key":"5_CR35","first-page":"1479","volume":"19","author":"M Li","year":"2007","unstructured":"Li, M., Zhou, Z.-H.: Improve computer-aided diagnosis with machine learning techniques using undiagnosed samples. IEEE Trans. Syst. 19(11), 1479\u20131493 (2007)","journal-title":"IEEE Trans. Syst."},{"key":"5_CR36","doi-asserted-by":"publisher","first-page":"1612","DOI":"10.1109\/TSMCB.2011.2157998","volume":"41","author":"M-L Zhang","year":"2011","unstructured":"Zhang, M.-L., Zhou, Z.-H.: CoTRADE: confident co-training with data editing. IEEE Trans. Syst. Man Cybern. Part B Cybern. 41, 1612\u20131626 (2011)","journal-title":"IEEE Trans. Syst. Man Cybern. Part B Cybern."},{"key":"5_CR37","unstructured":"Hoffmann, R., Zhang, C., Ling, X., Zettlemoyer, L., Weld, D.S.: CoTRADE: knowledge-based weak supervision for information extraction of overlapping relations. In: The 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pp. 541\u2013550 (2011)"},{"key":"5_CR38","doi-asserted-by":"crossref","unstructured":"Li, Q., Han, Z., Wu, X.-M.: CoTRADE: deeper insights into graph convolutional networks for semi-supervised learning. In: The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) (2018)","DOI":"10.1609\/aaai.v32i1.11604"},{"key":"5_CR39","doi-asserted-by":"crossref","unstructured":"Luan, Y., Wadden, D., He, L., Shah, A., Ostendorf, M., Hajishirzi, H.: CoTRADE: a general framework for information extraction using dynamic span graphs. In: NAACL (2019)","DOI":"10.18653\/v1\/N19-1308"},{"key":"5_CR40","doi-asserted-by":"crossref","unstructured":"Agrawal, K., Mittal, A., Pudi, V.: CoTRADE: scalable, semi-supervised extraction of structured information from scientific literature, pp. 11\u201320. Association for Computational Linguistics (2019)","DOI":"10.18653\/v1\/W19-2602"},{"key":"5_CR41","unstructured":"Kim, S.N., Medelyan, O., Kan, M.-Y., Baldwin, T.: SemEval-2010 task 5: automatic keyphrase extraction from scientifific articles. In: Proceedings of the 5th International Workshop on Semantic Evaluation, SemEval 2010, Stroudsburg, PA, USA, pp. 21\u201326. Association for Computational Linguistics (2010)"},{"key":"5_CR42","doi-asserted-by":"crossref","unstructured":"Gollapalli, S.D., Caragea, C.: Extracting keyphrases from research papers using citation networks. In: Proceedings of the Twenty-Eighth AAAI Conference on Artifificial Intelligence, AAAI 2014, pp. 1629\u20131635. AAAI Press (2014)","DOI":"10.1609\/aaai.v28i1.8946"},{"issue":"2","key":"5_CR43","first-page":"163","volume":"19","author":"K Jaidka","year":"2016","unstructured":"Jaidka, K., Chandrasekaran, M.K., Rustagi, S., Kan, M.-Y.: Insights from CL-SciSumm 2016: the faceted scientific document summarization shared task. Int. J. Digit. Libr. 19(2), 163\u2013171 (2016)","journal-title":"Int. J. Digit. Libr."},{"key":"5_CR44","doi-asserted-by":"crossref","unstructured":"Agrawal, K., Mittal, A., Pudi, V.: Scalable, semi-supervised extraction of structured information from scientifific literature (2019)","DOI":"10.18653\/v1\/W19-2602"},{"key":"5_CR45","unstructured":"Drugman, T., Pylkkonen, J., Kneser, R.: Active and semi-supervised learning in ASR: benefits on the acoustic and language models (2019)"},{"key":"5_CR46","doi-asserted-by":"crossref","unstructured":"Arora, C., Sabetzadeh, M., Nejati, S., Briand, L.: An active learning approach for improving the accuracy of automated domain model extraction (2019)","DOI":"10.1145\/3293454"},{"key":"5_CR47","doi-asserted-by":"crossref","unstructured":"Mintz, M., Bills, S., Snow, R., Jurafsky, D.: Distant supervision for relation extraction without labeled data, ACL 2009 (2009)","DOI":"10.3115\/1690219.1690287"},{"key":"5_CR48","unstructured":"Surdeanu, M., Tibshirani, J., Nallapati, R., Manning, C.D.: Multi-instance multi-label learning for relation extraction. In: Proceedings of EMNLP-CoNLL, pp. 455\u2013465 (2012)"},{"key":"5_CR49","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":"5_CR50","doi-asserted-by":"crossref","unstructured":"Zeng, D., Liu, K., Chen, Y., Zhao, J.: Distant supervision for relation extraction via piecewise convolutional neural networks (2015)","DOI":"10.18653\/v1\/D15-1203"},{"key":"5_CR51","doi-asserted-by":"crossref","unstructured":"Lin, Y., Shen, S., Liu, Z., Luan, H., Sun, M.: Neural relation extraction with selective attention over instances (2016)","DOI":"10.18653\/v1\/P16-1200"},{"key":"5_CR52","doi-asserted-by":"crossref","unstructured":"Wang, G., Zhang, W., Wang, R., Zhou, Y.: Label-free distant supervision for relation extraction via knowledge graph embedding (2018)","DOI":"10.18653\/v1\/D18-1248"}],"container-title":["Lecture Notes in Computer Science","Web and Big Data"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-33982-1_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,3]],"date-time":"2022-10-03T04:23:47Z","timestamp":1664771027000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-33982-1_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030339814","9783030339821"],"references-count":52,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-33982-1_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"1 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APWeb-WAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chengdu","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apwebwaim2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/cfm.uestc.edu.cn\/apwebwaim2019\/","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":"Research Microsoft","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"180","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":"42","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":"17","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":"23% - 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","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)"}}]}}