{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T18:20:25Z","timestamp":1779906025538,"version":"3.53.1"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031109829","type":"print"},{"value":"9783031109836","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-10983-6_19","type":"book-chapter","created":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T23:03:02Z","timestamp":1658185382000},"page":"240-254","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["CP Tensor Factorization for Knowledge Graph Completion"],"prefix":"10.1007","author":[{"given":"Yue","family":"Luo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunming","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xujian","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,7,19]]},"reference":[{"key":"19_CR1","doi-asserted-by":"crossref","unstructured":"Jiao, J., Wang, S., Zhang, Xiaowang, W.L., Feng, Z., Wang, J.: gMatch: knowledge base question answering via semantic matching. Knowl. Based Syst. 228 (2021). Author, F., Author, S.: Title of a proceedings paper. In: Editor, F., Editor, S. (eds.) CONFERENCE\u00a02016, LNCS, vol. 9999, pp.\u00a01\u201313. Springer, Heidelberg (2016)","DOI":"10.1016\/j.knosys.2021.107270"},{"key":"19_CR2","doi-asserted-by":"crossref","unstructured":"Xiong, C., Power, R., Callan, J.: Explicit semantic ranking for academic search via knowledge. graph embedding. In: Barrett, R., Cummings, R., Agichtein, E., et al. Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, 3\u20137 April 2017, pp. 1271\u20131279. ACM (2017)","DOI":"10.1145\/3038912.3052558"},{"key":"19_CR3","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1007\/978-3-319-93037-4_18","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"Z Zhou","year":"2018","unstructured":"Zhou, Z., Liu, S., Xu, G., Xie, X., Yin, J., Li, Y., Zhang, W.: Knowledge-based recommendation with hierarchical collaborative embedding. In: Phung, D., Tseng, V.S., Webb, G.I., Ho, B., Ganji, M., Rashidi, L. (eds.) PAKDD 2018. LNCS (LNAI), vol. 10938, pp. 222\u2013234. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-93037-4_18"},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"Bollacker, K., Evans, C., Paritosh, P., et al.: Freebase: a collaboratively created graph database for. structuring human knowledge. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data - SIGMOD 2008, Vancouver, Canada, p. 1247. ACM Press (2008)","DOI":"10.1145\/1376616.1376746"},{"key":"19_CR5","unstructured":"Mahdisoltani, F., Biega, J., Suchanek, F.M.: YAGO3: a knowledge base from multilingual. Wikipedias. In: CIDR 2015, Seventh Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, 4\u20137 January 2015, Online Proceedings. www.cidrdb.org (2015)"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Nathani, D., Chauhan, J., Sharma, C., Manohar, K.: Learning attention-based. embeddings for relation prediction in knowledge graphs. CoRR,2019.abs \/1906.01195","DOI":"10.18653\/v1\/P19-1466"},{"issue":"11","key":"19_CR7","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1145\/219717.219748","volume":"38","author":"GA Miller","year":"1995","unstructured":"Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38(11), 39\u201341 (1995)","journal-title":"Commun. ACM"},{"issue":"2","key":"19_CR8","doi-asserted-by":"publisher","first-page":"494","DOI":"10.1109\/TNNLS.2021.3070843","volume":"33","author":"S Ji","year":"2022","unstructured":"Ji, S., Pan, S., Cambria, E., Marttinen, P., Yu, P.S.: A survey on knowledge graphs: representation, acquisition, and applications. IEEE Trans. Neural Netw. Learn. Syst. 33(2), 494\u2013514 (2022)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"19_CR9","unstructured":"Han, X., Minlie, H., Yu, H., Xiaoyan, Z.: TransA: an adaptive approach for. knowledge graph embedding. CoRR,2015, abs\/1509.05490"},{"key":"19_CR10","unstructured":"Bordes, A., Usunier, N., Garcia-Duran, A., et al.: Translating Embeddings for Modeling Multi-relational Data. Curran Associates Inc. (2013)"},{"key":"19_CR11","unstructured":"Msahli, M., Qiu, H., Zheng, Q., et al.; Topological graph convolutional network-based urban traffic flow and density prediction. IEEE Trans. Intell. Transp. Syst. PP(99) (2020)"},{"key":"19_CR12","unstructured":"Sedghi, H., Sabharwal, A.: Knowledge completion for generics using guided tensor. factorization. CoRR, abs \/1612.03871 (2016)"},{"key":"19_CR13","unstructured":"Patents: Polynomial Method of Constructing a Non-Deterministic (NP) Turing Machine. In: Patent Application Approval Process (USPTO 20160012339). Politics & Government Week (2016)"},{"key":"19_CR14","doi-asserted-by":"crossref","unstructured":"Balazevic, I., Allen, C., Hospedales, T.M.: TuckER: tensor factorization for. knowledge graph completion. CoRR,abs\/1901.09590 (2019)","DOI":"10.18653\/v1\/D19-1522"},{"issue":"3","key":"19_CR15","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1137\/07070111X","volume":"51","author":"TG Kolda","year":"2009","unstructured":"Kolda, T.G., Bader, B.W.: Tensor Decompositions and applications. SIAM Rev. 51(3), 455\u2013500 (2009)","journal-title":"SIAM Rev."},{"key":"19_CR16","unstructured":"Lin, Y., Liu, Z., Sun, M., et al.: Learning entity and relation embeddings for knowledge graph. Completion. In: Bonet, B., Koenig, S. (eds.) Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 25\u201330 January 2015, Austin, Texas, USA, pp. 2181\u20132187. AAAI Press (2015)"},{"key":"19_CR17","unstructured":"Fan, M., Zhou, Q., Chang, E., et al.: Transition-based Knowledge Graph Embedding with Relational Mapping Properties (2014)"},{"key":"19_CR18","unstructured":"Xiao, H., Huang, M., Zhu X.: From one point to a manifold: knowledge graph embedding for. Precise Link Prediction. In: KAMBHAMPATI S. Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9\u201315 July 2016, pp. 1315\u20131321. IJCAI\/AAAI Press (2016)"},{"key":"19_CR19","unstructured":"Ji, G., Liu, K., He, S., et al.: Knowledge graph completion with adaptive sparse transfer. Matrix. In: Schuurmans, D., Wellman, M.P. (eds.) Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 12\u201317 February 2016, Phoenix, Arizona, USA, pp. 985\u2013991. AAAI Press (2016)"},{"key":"19_CR20","unstructured":"Wang, Z., Zhang, J., Feng, J., et al.: Knowledge graph embedding by translating on. Hyperplanes. In: Brodley, C.E., Stone, P. (eds.) Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 27\u201331 July 2014, Qu\u00e9bec City, Qu\u00e9bec, Canada, pp. 1112\u20131119. AAAI Press (2014)"},{"key":"19_CR21","unstructured":"Socker, R., Chen, D., Manning, C.D., et al.: Reasoning with neural tensor networks for knowledge. Base completion. In: Advances in Neural Information Processing Systems, pp. 926\u2013934 (2013)"},{"issue":"1","key":"19_CR22","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":"19_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1007\/978-3-319-93417-4_38","volume-title":"The Semantic Web","author":"M Schlichtkrull","year":"2018","unstructured":"Schlichtkrull, M., Kipf, T.N., Bloem, P., van\u00a0den Berg, R., Titov, I., Welling, M.: Modeling relational data with graph convolutional networks. In: Gangemi, A., Navigli, R., Vidal, M.-E., Hitzler, P., Troncy, R., Hollink, L., Tordai, A., Alam, M. (eds.) ESWC 2018. LNCS, vol. 10843, pp. 593\u2013607. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-93417-4_38"},{"key":"19_CR24","unstructured":"Dettmers, T., Minervini, P., Stenetorp, P., et al.: Convolutional 2D knowledge graph. Embeddings. In: Mcilraith, S.A., Weinberger, K.Q. (eds.) Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, 2\u20137 February 2018, pp. 1811\u20131818. AAAI Press (2018)"},{"key":"19_CR25","doi-asserted-by":"crossref","unstructured":"Nguyen, D.Q., Nguyen, T.D., Nguyen, D.Q., et al.: A novel embedding model for knowledge. Base completion based on convolutional neural network. In: Walker, M.A., Ji, H., Stent, A. (eds.) Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT, New Orleans, Louisiana, USA, 1\u20136 June 2018, Volume 2 (Short Papers), pp. 327\u2013333. Association for Computational Linguistics (2018)","DOI":"10.18653\/v1\/N18-2053"},{"key":"19_CR26","unstructured":"Nickel, M., Tresp, V., Kriegel, H.-P.: A three-way model for collective learning on multi-relational data. In: Getoor, L., Scheffer, T. (eds.) Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, 28 June\u20132 July 2011, pp. 809\u2013816. Omnipress (2011)"},{"key":"19_CR27","unstructured":"Yang, B., Yih, W., He, X., et al.: Embedding entities and relations for learning and inference in. knowledge bases. In: Bengio, Y., Lecun, Y. (eds.) 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, 7\u20139 May 2015, Conference Track Proceedings (2015)"},{"key":"19_CR28","unstructured":"Trouillon, T., Welbl, J., Riedel, S., et al.: Complex embeddings for simple link. Prediction. In: Balcan, M.-F., Weinberger, K.Q. (eds.) Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, 19\u201324 June 2016. JMLR.org, vol. 48, pp. 2071\u20132080 (2016)"},{"key":"19_CR29","unstructured":"Kazemi, S.M., Poole, D.: SimplE embedding for link prediction in knowledge. Graphs. In: Bengio, S., Wallach, H.M., Larochelle, H., et al. Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, 3\u20138 December 2018, Montr\u00e9al, Canada. 2018, pp. 4289\u20134300 (2018)"},{"key":"19_CR30","doi-asserted-by":"crossref","unstructured":"Akrami, F., Saeef, M.S., Zhang, Q., Hu, W., Li, C.: Realistic Re-evaluation of Knowledge Graph Completion Methods: An Experimental Study. Management of Data (2020)","DOI":"10.1145\/3318464.3380599"},{"key":"19_CR31","doi-asserted-by":"crossref","unstructured":"Toutanova, K., Chen, D., Pantel, P., Poon, H., Choudhury, P., Gamon, M.: Representing text for joint embedding of text and knowledge bases. In: Proceedings of the 2015Conference on Empirical Methods in Natural Language Processing (2015)","DOI":"10.18653\/v1\/D15-1174"},{"key":"19_CR32","unstructured":"Xiong, W., Hoang, T., Wang, W.Y.: De eppath: a reinforcement learning method for knowledge graph reasoning. arXivpreprint arXiv:1707.06690,201"},{"key":"19_CR33","doi-asserted-by":"crossref","unstructured":"Lin, X.V., Socher, R., Xiong, C.: Multi-hop knowledge graph reasoning with reward shaping. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2018)","DOI":"10.18653\/v1\/D18-1362"},{"key":"19_CR34","unstructured":"Sun, Z., Deng, Z.H., Nie, J.Y., et al.: RotatE: knowledge graph embedding by relational rotation in complex space (2019)"},{"key":"19_CR35","doi-asserted-by":"crossref","unstructured":"Chao, L., He, J., Wang, T., et al.: PairRE: knowledge graph embeddings via paired relation vectors (2020)","DOI":"10.18653\/v1\/2021.acl-long.336"},{"key":"19_CR36","doi-asserted-by":"crossref","unstructured":"Vashishth, S., Sanyal, S., Nitin, V., et al.: InteractE: improving convolution-based knowledge graph embeddings by increasing feature interactions. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 3, pp. 3009\u20133016 (2020)","DOI":"10.1609\/aaai.v34i03.5694"}],"container-title":["Lecture Notes in Computer Science","Knowledge Science, Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-10983-6_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T14:16:00Z","timestamp":1667312160000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-10983-6_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031109829","9783031109836"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-10983-6_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"19 July 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"KSEM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Knowledge Science, Engineering and Management","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2022","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":"ksem2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ksem22.smart-conf.net\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-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":"498","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":"169","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":"34% - 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":"10","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)"}}]}}