{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T11:20:14Z","timestamp":1742988014590,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031495519"},{"type":"electronic","value":"9783031495526"}],"license":[{"start":{"date-parts":[[2023,12,20]],"date-time":"2023-12-20T00:00:00Z","timestamp":1703030400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,20]],"date-time":"2023-12-20T00:00:00Z","timestamp":1703030400000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-49552-6_28","type":"book-chapter","created":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T16:03:00Z","timestamp":1703001780000},"page":"323-334","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Good Negative Sampling for\u00a0Triple Classification"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5615-375X","authenticated-orcid":false,"given":"Yoan Antonio","family":"L\u00f3pez-Rodr\u00edguez","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8263-0425","authenticated-orcid":false,"given":"Orlando Grabiel","family":"Toledano-L\u00f3pez","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5763-0669","authenticated-orcid":false,"given":"Yusniel","family":"Hidalgo-Delgado","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7601-4201","authenticated-orcid":false,"given":"H\u00e9ctor","family":"Gonz\u00e1lez Di\u00e9z","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4997-0828","authenticated-orcid":false,"given":"Rey","family":"Segundo-Guerrero","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,12,20]]},"reference":[{"issue":"1","key":"28_CR1","first-page":"3723","volume":"22","author":"M Ali","year":"2021","unstructured":"Ali, M., et al.: PyKEEN 1.0: a python library for training and evaluating knowledge graph embeddings. J. Mach. Learn. Res. 22(1), 3723\u20133728 (2021)","journal-title":"J. Mach. Learn. Res."},{"key":"28_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1613\/jair.2820","volume":"36","author":"A Artale","year":"2009","unstructured":"Artale, A., Calvanese, D., Kontchakov, R., Zakharyaschev, M.: The DL-Lite family and relations. J. Artif. Intell. Res. 36, 1\u201369 (2009)","journal-title":"J. Artif. Intell. Res."},{"key":"28_CR3","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":"28_CR4","doi-asserted-by":"crossref","unstructured":"Bollacker, K., Evans, C., Paritosh, P., Sturge, T., Taylor, J.: Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 1247\u20131250 (2008)","DOI":"10.1145\/1376616.1376746"},{"key":"28_CR5","unstructured":"Bordes, A., Usunier, N., Garcia-Duran, A., Weston, J., Yakhnenko, O.: Translating embeddings for modeling multi-relational data. In: Advances in Neural Information Processing Systems, vol. 26, 2013"},{"key":"28_CR6","unstructured":"Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"28_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1007\/978-3-030-77385-4_26","volume-title":"The Semantic Web","author":"C d\u2019Amato","year":"2021","unstructured":"d\u2019Amato, C., Quatraro, N.F., Fanizzi, N.: Injecting background knowledge into embedding models for predictive tasks on knowledge graphs. In: Verborgh, R., et al. (eds.) ESWC 2021. LNCS, vol. 12731, pp. 441\u2013457. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-77385-4_26"},{"issue":"4","key":"28_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3447772","volume":"54","author":"A Hogan","year":"2021","unstructured":"Hogan, A., et al.: Knowledge graphs. ACM Comput. Surv. (CSUR) 54(4), 1\u201337 (2021)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"28_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1007\/978-3-030-88361-4_24","volume-title":"The Semantic Web \u2013 ISWC 2021","author":"N Jain","year":"2021","unstructured":"Jain, N., Tran, T.-K., Gad-Elrab, M.H., Stepanova, D.: Improving knowledge graph embeddings with ontological reasoning. In: Hotho, A., et al. (eds.) ISWC 2021. LNCS, vol. 12922, pp. 410\u2013426. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-88361-4_24"},{"key":"28_CR10","unstructured":"Kamigaito, H., Hayashi, K.: Comprehensive analysis of negative sampling in knowledge graph representation learning. In: International Conference on Machine Learning, pp. 10661\u201310675. PMLR (2022)"},{"key":"28_CR11","unstructured":"Kotnis, B., Nastase, V.: Analysis of the impact of negative sampling on link prediction in knowledge graphs. arXiv preprint arXiv:1708.06816 (2017)"},{"key":"28_CR12","doi-asserted-by":"publisher","first-page":"17637","DOI":"10.1007\/s00521-020-04940-5","volume":"32","author":"H Liu","year":"2020","unstructured":"Liu, H., Kairong, H., Wang, F.-L., Hao, T.: Aggregating neighborhood information for negative sampling for knowledge graph embedding. Neural Comput. Appl. 32, 17637\u201317653 (2020). https:\/\/doi.org\/10.1007\/s00521-020-04940-5","journal-title":"Neural Comput. Appl."},{"key":"28_CR13","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, vol. 26 (2013)"},{"issue":"1","key":"28_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":"28_CR15","unstructured":"Nickel, M., Tresp, V., Kriegel, H.-P., et al.: A three-way model for collective learning on multi-relational data. In: ICML, vol. 11, pp. 3104482\u20133104584 (2011)"},{"key":"28_CR16","doi-asserted-by":"publisher","first-page":"13071","DOI":"10.1007\/s10462-023-10465-9","volume":"56","author":"C Peng","year":"2023","unstructured":"Peng, C., Xia, F., Naseriparsa, M., Osborne, F.: Knowledge graphs: opportunities and challenges. Artif. Intell. Rev. 56, 13071\u201313102 (2023). https:\/\/doi.org\/10.1007\/s10462-023-10465-9","journal-title":"Artif. Intell. Rev."},{"key":"28_CR17","unstructured":"Socher, R., Chen, D., Manning, C.D., Ng, A.: Reasoning with neural tensor networks for knowledge base completion. In: Advances in Neural Information Processing Systems, vol. 26 (2013)"},{"key":"28_CR18","doi-asserted-by":"crossref","unstructured":"Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Proceedings of the 16th International Conference on World Wide Web, pp. 697\u2013706 (2007)","DOI":"10.1145\/1242572.1242667"},{"key":"28_CR19","unstructured":"Trouillon, T., Welbl, J., Riedel, S., Gaussier, \u00c9., Bouchard, G.: Complex embeddings for simple link prediction. In: International Conference on Machine Learning, pp. 2071\u20132080. PMLR (2016)"},{"key":"28_CR20","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"issue":"10","key":"28_CR21","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1145\/2629489","volume":"57","author":"D Vrande\u010di\u0107","year":"2014","unstructured":"Vrande\u010di\u0107, D., Kr\u00f6tzsch, M.: Wikidata: a free collaborative knowledgebase. Commun. ACM 57(10), 78\u201385 (2014)","journal-title":"Commun. ACM"},{"key":"28_CR22","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhang, J., Feng, J., Chen, Z.: Knowledge graph embedding by translating on hyperplanes. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 28 (2014)","DOI":"10.1609\/aaai.v28i1.8870"},{"key":"28_CR23","unstructured":"Yang, B., Yih, W., He, X., Gao, J., Deng, L.: Embedding entities and relations for learning and inference in knowledge bases. arXiv preprint arXiv:1412.6575 (2014)"},{"key":"28_CR24","unstructured":"Yao, L., Mao, C., Luo, Y.: KG-BERT: BERT for knowledge graph completion. arXiv preprint arXiv:1909.03193 (2019)"},{"key":"28_CR25","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.aiopen.2021.03.001","volume":"2","author":"J Zhang","year":"2021","unstructured":"Zhang, J., Chen, B., Zhang, L., Ke, X., Ding, H.: Neural, symbolic and neural-symbolic reasoning on knowledge graphs. AI Open 2, 14\u201335 (2021)","journal-title":"AI Open"},{"issue":"2","key":"28_CR26","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1007\/s00778-020-00640-7","volume":"30","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Yao, Q., Chen, L.: Simple and automated negative sampling for knowledge graph embedding. VLDB J. 30(2), 259\u2013285 (2021). https:\/\/doi.org\/10.1007\/s00778-020-00640-7","journal-title":"VLDB J."}],"container-title":["Lecture Notes in Computer Science","Progress in Artificial Intelligence and Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-49552-6_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T16:06:36Z","timestamp":1703001996000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-49552-6_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,20]]},"ISBN":["9783031495519","9783031495526"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-49552-6_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023,12,20]]},"assertion":[{"value":"20 December 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IWAIPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Artificial Intelligence and Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Varadero","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cuba","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iwaipr2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/uciencia.uci.cu\/en\/v-international-scientific-conference-uciencia-2023","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":"Springer Nature EquinOCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"68","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":"38","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":"56% - 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":"2.45","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}