{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T04:01:49Z","timestamp":1774929709087,"version":"3.50.1"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030454418","type":"print"},{"value":"9783030454425","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-45442-5_1","type":"book-chapter","created":{"date-parts":[[2020,4,10]],"date-time":"2020-04-10T21:03:47Z","timestamp":1586552627000},"page":"3-11","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned"],"prefix":"10.1007","author":[{"given":"Max","family":"Berrendorf","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evgeniy","family":"Faerman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Valentyn","family":"Melnychuk","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Volker","family":"Tresp","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Seidl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,4,8]]},"reference":[{"key":"1_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"722","DOI":"10.1007\/978-3-540-76298-0_52","volume-title":"The Semantic Web","author":"S Auer","year":"2007","unstructured":"Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: DBpedia: a nucleus for a web of open data. In: Aberer, K., et al. (eds.) ASWC\/ISWC -2007. LNCS, vol. 4825, pp. 722\u2013735. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-76298-0_52"},{"key":"1_CR2","unstructured":"Bordes, A., Usunier, N., Garc\u00eda-Dur\u00e1n, A., Weston, J., Yakhnenko, O.: Translating embeddings for modeling multi-relational data. In: Burges, C.J.C., Bottou, L., Ghahramani, Z., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a Meeting, Lake Tahoe, Nevada, United States, 5\u20138 December 2013. pp. 2787\u20132795 (2013). http:\/\/papers.nips.cc\/paper\/5071-translating-embeddings-for-modeling-multi-relational-data"},{"key":"1_CR3","unstructured":"Cao, Y., Liu, Z., Li, C., Liu, Z., Li, J., Chua, T.: Multi-channel graph neural network for entity alignment. In: Korhonen et al. [10], pp. 1452\u20131461. https:\/\/www.aclweb.org\/anthology\/P19-1140\/"},{"key":"1_CR4","doi-asserted-by":"publisher","unstructured":"Chen, M., Tian, Y., Chang, K., Skiena, S., Zaniolo, C.: Co-training embeddings of knowledge graphs and entity descriptions for cross-lingual entity alignment. In: Lang [12], pp. 3998\u20134004. https:\/\/doi.org\/10.24963\/ijcai.2018\/556","DOI":"10.24963\/ijcai.2018\/556"},{"key":"1_CR5","doi-asserted-by":"publisher","unstructured":"Chen, M., Tian, Y., Yang, M., Zaniolo, C.: Multilingual knowledge graph embeddings for cross-lingual knowledge alignment. In: Sierra [16], pp. 1511\u20131517. https:\/\/doi.org\/10.24963\/ijcai.2017\/209","DOI":"10.24963\/ijcai.2017\/209"},{"key":"1_CR6","unstructured":"Fey, M., Lenssen, J.E., Morris, C., Masci, J., Kriege, N.M.: Deep graph matching consensus. In: International Conference on Learning Representations (2020). https:\/\/openreview.net\/forum?id=HyeJf1HKvS"},{"key":"1_CR7","unstructured":"Gilmer, J., Schoenholz, S.S., Riley, P.F., Vinyals, O., Dahl, G.E.: Neural message passing for quantum chemistry. In: Proceedings of the 34th International Conference on Machine Learning-Volume 70, pp. 1263\u20131272. JMLR. org (2017)"},{"key":"1_CR8","unstructured":"Guo, L., Sun, Z., Hu, W.: Learning to exploit long-term relational dependencies in knowledge graphs. In: Chaudhuri, K., Salakhutdinov, R. (eds.) Proceedings of the 36th International Conference on Machine Learning (ICML 2019), Long Beach, California, USA, 9\u201315 June 2019. Proceedings of Machine Learning Research, vol. 97, pp. 2505\u20132514. PMLR (2019). http:\/\/proceedings.mlr.press\/v97\/guo19c.html"},{"key":"1_CR9","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"1_CR10","unstructured":"Korhonen, A., Traum, D.R., M\u00e0rquez, L. (eds.): Proceedings of the 57th Conference of the Association for Computational Linguistics (ACL 2019), Florence, Italy, 28 July \u2013 2 August 2019, Volume 1: Long Papers. Association for Computational Linguistics (2019). https:\/\/www.aclweb.org\/anthology\/volumes\/P19-1\/"},{"key":"1_CR11","doi-asserted-by":"publisher","unstructured":"Kraus, S. (ed.): Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China, 10\u201316 August 2019. ijcai.org (2019). https:\/\/doi.org\/10.24963\/ijcai.2019","DOI":"10.24963\/ijcai.2019"},{"key":"1_CR12","unstructured":"Lang, J. (ed.): Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2018), Stockholm, Sweden, 13\u201319 July 2018. ijcai.org (2018). http:\/\/www.ijcai.org\/proceedings\/2018\/"},{"key":"1_CR13","unstructured":"Mahdisoltani, F., Biega, J., Suchanek, F.M.: YAGO3: a knowledge base from multilingual wikipedias. In: Seventh Biennial Conference on Innovative Data Systems Research (CIDR 2015), Asilomar, CA, USA, 4\u20137 January 2015, Online Proceedings. www.cidrdb.org (2015). http:\/\/cidrdb.org\/cidr2015\/Papers\/CIDR15_Paper1.pdf"},{"issue":"1","key":"1_CR14","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/JPROC.2015.2483592","volume":"104","author":"M Nickel","year":"2015","unstructured":"Nickel, M., Murphy, K., Tresp, V., Gabrilovich, E.: A review of relational machine learning for knowledge graphs. Proc. IEEE 104(1), 11\u201333 (2015)","journal-title":"Proc. IEEE"},{"key":"1_CR15","doi-asserted-by":"publisher","unstructured":"Pei, S., Yu, L., Hoehndorf, R., Zhang, X.: Semi-supervised entity alignment via knowledge graph embedding with awareness of degree difference. In: Liu, L., et\u00a0al. (eds.) The World Wide Web Conference (WWW 2019), San Francisco, CA, USA, 13\u201317 May 2019, pp. 3130\u20133136. ACM (2019). https:\/\/doi.org\/10.1145\/3308558.3313646","DOI":"10.1145\/3308558.3313646"},{"key":"1_CR16","unstructured":"Sierra, C. (ed.): Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne, Australia, 19\u201325 August 2017. ijcai.org (2017). http:\/\/www.ijcai.org\/Proceedings\/2017\/"},{"key":"1_CR17","unstructured":"Singhal, A.: Introducing the knowledge graph: things, not strings. Official Google Blog 5, (2012)"},{"key":"1_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"628","DOI":"10.1007\/978-3-319-68288-4_37","volume-title":"The Semantic Web \u2013 ISWC 2017","author":"Z Sun","year":"2017","unstructured":"Sun, Z., Hu, W., Li, C.: Cross-lingual entity alignment via joint attribute-preserving embedding. In: d\u2019Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10587, pp. 628\u2013644. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-68288-4_37"},{"key":"1_CR19","doi-asserted-by":"publisher","unstructured":"Sun, Z., Hu, W., Zhang, Q., Qu, Y.: Bootstrapping entity alignment with knowledge graph embedding. In: Lang [12], pp. 4396\u20134402. https:\/\/doi.org\/10.24963\/ijcai.2018\/611","DOI":"10.24963\/ijcai.2018\/611"},{"key":"1_CR20","doi-asserted-by":"crossref","unstructured":"Trisedya, B.D., Qi, J., Zhang, R.: Entity alignment between knowledge graphs using attribute embeddings. In: The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI 2019), Honolulu, Hawaii, USA, 27 January \u2013 1 February 2019, pp. 297\u2013304. AAAI Press (2019). https:\/\/aaai.org\/ojs\/index.php\/AAAI\/article\/view\/3798","DOI":"10.1609\/aaai.v33i01.3301297"},{"key":"1_CR21","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., Bengio, Y.: Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)"},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Wang, Z., Lv, Q., Lan, X., Zhang, Y.: Cross-lingual knowledge graph alignment via graph convolutional networks. In: Riloff, E., Chiang, D., Hockenmaier, J., Tsujii, J. (eds.) Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, 31 October \u2013 4 November 2018, pp. 349\u2013357. Association for Computational Linguistics (2018). https:\/\/www.aclweb.org\/anthology\/D18-1032\/","DOI":"10.18653\/v1\/D18-1032"},{"key":"1_CR23","unstructured":"Wikidata. https:\/\/www.wikidata.org\/"},{"key":"1_CR24","doi-asserted-by":"crossref","unstructured":"Xu, K., et al.: Cross-lingual knowledge graph alignment via graph matching neural network. In: Korhonen et al. [10], pp. 3156\u20133161 (2019). https:\/\/www.aclweb.org\/anthology\/P19-1304\/. arXiv preprint arXiv:1905.11605","DOI":"10.18653\/v1\/P19-1304"},{"key":"1_CR25","doi-asserted-by":"publisher","unstructured":"Zhang, Q., Sun, Z., Hu, W., Chen, M., Guo, L., Qu, Y.: Multi-view knowledge graph embedding for entity alignment. In: Kraus [11], pp. 5429\u20135435. https:\/\/doi.org\/10.24963\/ijcai.2019\/754","DOI":"10.24963\/ijcai.2019\/754"},{"key":"1_CR26","doi-asserted-by":"publisher","unstructured":"Zhu, H., Xie, R., Liu, Z., Sun, M.: Iterative entity alignment via joint knowledge embeddings. In: Sierra [17], pp. 4258\u20134264. https:\/\/doi.org\/10.24963\/ijcai.2017\/595","DOI":"10.24963\/ijcai.2017\/595"},{"key":"1_CR27","doi-asserted-by":"publisher","unstructured":"Zhu, Q., Zhou, X., Wu, J., Tan, J., Guo, L.: Neighborhood-aware attentional representation for multilingual knowledge graphs. In: Kraus [11], pp. 1943\u20131949. https:\/\/doi.org\/10.24963\/ijcai.2019\/269","DOI":"10.24963\/ijcai.2019\/269"}],"container-title":["Lecture Notes in Computer Science","Advances in Information Retrieval"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-45442-5_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T19:22:45Z","timestamp":1710357765000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-45442-5_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030454418","9783030454425"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-45442-5_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"8 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECIR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Information Retrieval","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lisbon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","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":"14 April 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 April 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"42","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecir2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecir2020.org\/","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":"457","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":"55","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":"46","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":"12% - 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":"4","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)"}},{"value":"Also included: 8 reproducibility papers, 10 demonstration papers, 12 CLEF organizers lab track papers, 7 doctoral consortium papers, 4 workshops, 3 tutorials. Due to the COVID-19 pandemic, this conference was held virtually.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}