{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:11:25Z","timestamp":1767337885272,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":30,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819755615"},{"type":"electronic","value":"9789819755622"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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\/978-981-97-5562-2_23","type":"book-chapter","created":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T07:01:50Z","timestamp":1729926110000},"page":"358-374","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Reinforced Negative Sampling for Knowledge Graph Embedding"],"prefix":"10.1007","author":[{"given":"Yushun","family":"Xie","sequence":"first","affiliation":[]},{"given":"Haiyan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Le","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Lei","family":"Luo","sequence":"additional","affiliation":[]},{"given":"Jianxin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhaoquan","family":"Gu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,27]]},"reference":[{"key":"23_CR1","unstructured":"Adler, J., Lunz, S.: Banach wasserstein GAN. Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018 pp. 6755\u20136764 (2018)"},{"key":"23_CR2","doi-asserted-by":"crossref","unstructured":"Ahrabian, K., Feizi, A., Salehi, Y., Hamilton, W.L., Bose, A.J.: Structure aware negative sampling in knowledge graphs. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing. pp. 6093\u20136101. Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.492"},{"key":"23_CR3","doi-asserted-by":"crossref","unstructured":"Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: Dbpedia: A nucleus for a web of open data. In: The Semantic Web, 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference. vol.\u00a04825, pp. 722\u2013735. Springer (2007)","DOI":"10.1007\/978-3-540-76298-0_52"},{"key":"23_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. ACM (2008)","DOI":"10.1145\/1376616.1376746"},{"issue":"2","key":"23_CR5","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1007\/s10994-013-5363-6","volume":"94","author":"A Bordes","year":"2014","unstructured":"Bordes, A., Glorot, X., Weston, J., Bengio, Y.: A semantic matching energy function for learning with multi-relational data. Mach. Learn. 94(2), 233\u2013259 (2014)","journal-title":"Mach. Learn."},{"key":"23_CR6","unstructured":"Bordes, A., Usunier, N., Garcia-Duran, A., Weston, J., Yakhnenko, O.: Translating embeddings for modeling multi-relational data. Advances in neural information processing systems 26: Annual Conference on Neural Information Processing Systems 2013 pp. 2787\u20132795 (2013)"},{"key":"23_CR7","doi-asserted-by":"crossref","unstructured":"Cai, L., Wang, W.Y.: Kbgan: Adversarial learning for knowledge graph embeddings. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). pp. 1470\u20131480. Association for Computational Linguistics (2018)","DOI":"10.18653\/v1\/N18-1133"},{"key":"23_CR8","unstructured":"Che, F., Yang, G., Shao, P., Zhang, D., Tao, J.: Mixkg: Mixing for harder negative samples in knowledge graph. CoRR abs\/2202.09606 (2022), https:\/\/arxiv.org\/abs\/2202.09606"},{"key":"23_CR9","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014. pp. 2672\u20132680 (2014)"},{"issue":"11","key":"23_CR10","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3422622","volume":"63","author":"I Goodfellow","year":"2020","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial networks. Commun. ACM 63(11), 139\u2013144 (2020)","journal-title":"Commun. ACM"},{"key":"23_CR11","doi-asserted-by":"publisher","unstructured":"Gu, Z., Wang, L., Chen, X., Tang, Y., Wang, X., Du, X., Guizani,M., Tian, Z.: Epidemic risk assessment by a novel communication station based method. IEEE Trans. Netw. Sci. Eng. 9(1), 332\u2013344 (2022). https:\/\/doi.org\/10.1109\/TNSE.2021.3058762, https:\/\/doi.org\/10.1109\/TNSE.2021.3058762","DOI":"10.1109\/TNSE.2021.3058762"},{"issue":"8","key":"23_CR12","doi-asserted-by":"publisher","first-page":"3549","DOI":"10.1109\/TKDE.2020.3028705","volume":"34","author":"Q Guo","year":"2022","unstructured":"Guo, Q., Zhuang, F., Qin, C., Zhu, H., Xie, X., Xiong, H., He, Q.: A survey on knowledge graph-based recommender systems. IEEE Trans. Knowl. Data Eng. 34(8), 3549\u20133568 (2022)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"23_CR13","doi-asserted-by":"crossref","unstructured":"Hao, Y., Zhang, Y., Liu, K., He, S., Liu, Z., Wu, H., Zhao, J.: An end-to-end model for question answering over knowledge base with cross-attention combining global knowledge. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). pp. 221\u2013231. Association for Computational Linguistics (2017)","DOI":"10.18653\/v1\/P17-1021"},{"key":"23_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109083","volume":"250","author":"MK Islam","year":"2022","unstructured":"Islam, M.K., Aridhi, S., Smail-Tabbone, M.: Negative sampling and rule mining for explainable link prediction in knowledge graphs. Knowl.-Based Syst. 250, 109083 (2022)","journal-title":"Knowl.-Based Syst."},{"key":"23_CR15","unstructured":"Kalantidis, Y., Sariyildiz, M.B., Pion, N., Weinzaepfel, P., Larlus, D.: Hard negative mixing for contrastive learning. Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020 33, 21798\u201321809 (2020)"},{"key":"23_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109889","volume":"256","author":"L Li","year":"2022","unstructured":"Li, L., Zhang, X., Ma, Y., Gao, C., Wang, J., Yu, Y., Yuan, Z., Ma, Q.: A knowledge graph completion model based on contrastive learning and relation enhancement method. Knowl.-Based Syst. 256, 109889 (2022)","journal-title":"Knowl.-Based Syst."},{"key":"23_CR17","unstructured":"Nickel, M., Tresp, V., Kriegel, H.P.: A three-way model for collective learning on multi-relational data. In: Proceedings of the 28th International Conference on Machine Learning. pp. 809\u2013816. Omnipress (2011)"},{"issue":"1","key":"23_CR18","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/JPROC.2015.2483592","volume":"104","author":"M Nickel","year":"2016","unstructured":"Nickel, M., Murphy, K., Tresp, V., Gabrilovich, E.: A review of relational machine learning for knowledge graphs. Proc. IEEE 104(1), 11\u201333 (2016)","journal-title":"Proc. IEEE"},{"key":"23_CR19","unstructured":"Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., Lerer, A.: Automatic differentiation in pytorch. In: Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017 (2017), https:\/\/openreview.net\/forum?id=BJJsrmfCZ"},{"key":"23_CR20","doi-asserted-by":"crossref","unstructured":"Shen, Z., Liu, Z., Liu, Z., Savvides, M., Darrell, T., Xing, E.: Un-mix: Rethinking image mixtures for unsupervised visual representation learning. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence. pp. 2216\u20132224. AAAI Press (2022)","DOI":"10.1609\/aaai.v36i2.20119"},{"key":"23_CR21","unstructured":"Sun, Z., Deng, Z.H., Nie, J.Y., Tang, J.: Rotate: Knowledge graph embedding by relational rotation in complex space. In: Proceedings of the 7th International Conference on Learning Representations (2019), https:\/\/openreview.net\/forum?id=HkgEQnRqYQ"},{"issue":"130","key":"23_CR22","first-page":"1","volume":"18","author":"T Trouillon","year":"2017","unstructured":"Trouillon, T., Dance, C., Gaussier, E., Welbl, J., Riedel, S., Bouchard, G.: Knowledge graph completion via complex tensor factorization. J. Mach. Learn. Res. 18(130), 1\u201338 (2017)","journal-title":"J. Mach. Learn. Res."},{"key":"23_CR23","unstructured":"Verma, V., Lamb, A., Beckham, C., Najafi, A., Mitliagkas, I., Lopez-Paz, D., Bengio, Y.: Manifold mixup: Better representations by interpolating hidden states. In: Proceedings of the 36th International Conference on Machine Learning. vol.\u00a097, pp. 6438\u20136447. PMLR (2019)"},{"issue":"12","key":"23_CR24","doi-asserted-by":"publisher","first-page":"2724","DOI":"10.1109\/TKDE.2017.2754499","volume":"29","author":"Q Wang","year":"2017","unstructured":"Wang, Q., Mao, Z., Wang, B., Guo, L.: Knowledge graph embedding: A survey of approaches and applications. IEEE Trans. Knowl. Data Eng. 29(12), 2724\u20132743 (2017)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"23_CR25","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhang, J., Feng, J., Chen, Z.: Knowledge graph embedding by translating on hyperplanes. In: Proceedings of the 28th AAAI conference on artificial intelligence. pp. 1112\u20131119. AAAI Press (2014)","DOI":"10.1609\/aaai.v28i1.8870"},{"key":"23_CR26","doi-asserted-by":"crossref","unstructured":"Xiong, C., Power, R., Callan, J.: Explicit semantic ranking for academic search via knowledge graph embedding. In: Proceedings of the 26th international conference on world wide web. pp. 1271\u20131279. ACM (2017)","DOI":"10.1145\/3038912.3052558"},{"key":"23_CR27","unstructured":"Yang, B., Yih, S.W.t., He, X., Gao, J., Deng, L.: Embedding entities and relations for learning and inference in knowledge bases. In: Proceedings of the 3rd International Conference on Learning Representations (2015), http:\/\/arxiv.org\/abs\/1412.6575"},{"key":"23_CR28","doi-asserted-by":"crossref","unstructured":"Yao, X., Van\u00a0Durme, B.: Information extraction over structured data: Question answering with freebase. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). pp. 956\u2013966. The Association for Computer Linguistics (2014)","DOI":"10.3115\/v1\/P14-1090"},{"key":"23_CR29","unstructured":"Zhang, H., Cisse, M., Dauphin, Y.N., Lopez-Paz, D.: mixup: Beyond empirical risk minimization. In: Proceedings of the 6th International Conference on Learning Representations (2018), https:\/\/openreview.net\/forum?id=r1Ddp1-Rb"},{"key":"23_CR30","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yao, Q., Shao, Y., Chen, L.: Nscaching: Simple and efficient negative sampling for knowledge graph embedding. In: Proceedings of the 35th IEEE International Conference on Data Engineering. pp. 614\u2013625. IEEE (2019)","DOI":"10.1109\/ICDE.2019.00061"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5562-2_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T07:59:35Z","timestamp":1748073575000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5562-2_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819755615","9789819755622"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5562-2_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"27 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gifu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2024a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.dasfaa2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}