{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T18:39:09Z","timestamp":1742927949280,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031203084"},{"type":"electronic","value":"9783031203091"}],"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.springernature.com\/gp\/researchers\/text-and-data-mining"},{"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.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-20309-1_9","type":"book-chapter","created":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T06:11:35Z","timestamp":1670393495000},"page":"102-114","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Multi-view Based Entity Frequency-Aware Graph Neural Network for Temporal Knowledge Graph Link Prediction"],"prefix":"10.1007","author":[{"given":"Jinyu","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Derong","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tiezheng","family":"Nie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Kou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,12,8]]},"reference":[{"key":"9_CR1","unstructured":"Anonymous: Learning representation over dynamic graph. arXiv preprint arXiv:2106.01678 (2016)"},{"key":"9_CR2","doi-asserted-by":"crossref","unstructured":"Jin, W., Qu, M., Jin, X., et al.: Recurrent event network: autoregressive structure inferenceover temporal knowledge graphs. arXiv preprint arXiv:1904.05530 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.541"},{"key":"9_CR3","unstructured":"Zaremba, W., Sutskever, I., Vinyals, O.: Recurrent neural network regularization. arXiv preprint arXiv:1409.2329 (2014)"},{"key":"9_CR4","unstructured":"Bordes, A., Usunier, N., Garcia-Duran, A., et al.: Translating embeddings for modeling multi-relational data. In: Curran Associates Inc., pp. 1\u20139 (2013)"},{"key":"9_CR5","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhang, J., Feng, J., et al.: Knowledge graph embedding by translating on hyperplanes. In: AAAI, pp. 1112\u20131119 (2014)","DOI":"10.1609\/aaai.v28i1.8870"},{"key":"9_CR6","doi-asserted-by":"crossref","unstructured":"Lin, Y., Liu, Z., Sun, M., Liu, Y., Zhu, X.: Learning entity and relation embeddings for knowledge graph completion. In: AAAI, pp. 2181\u20132187 (2015)","DOI":"10.1609\/aaai.v29i1.9491"},{"key":"9_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1007\/978-3-030-87571-8_43","volume-title":"Web Information Systems and Applications","author":"C Li","year":"2021","unstructured":"Li, C., Zhai, R., Zuo, F., Yu, J., Zhang, L.: Mixed multi-channel graph convolution network on complex relation graph. In: Xing, C., Fu, X., Zhang, Y., Zhang, G., Borjigin, C. (eds.) WISA 2021. LNCS, vol. 12999, pp. 497\u2013504. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87571-8_43"},{"key":"9_CR8","unstructured":"Yang, B., Yih, W, T., He, X., et al.: Embedding entities and relations for learning and inference in knowledge bases. arXiv preprint arXiv:1412.6575 (2014)"},{"key":"9_CR9","unstructured":"Nickel M., et al.: A three-way model for collective learning on multi-relational data. In: International Conference on Machine Learning, pp. 438\u2013445(2011)"},{"key":"9_CR10","unstructured":"Trouillon, T., Welbl, J., Riedel, S., Gaussier, \u00c9., Bouchard, G.: Complex embeddings for simple link prediction. In: ICML, pp. 2071\u20132080 (2016)"},{"key":"9_CR11","doi-asserted-by":"crossref","unstructured":"Nickel, M., Rosasco, L., Poggio, T.A.: Holographic embeddings of knowledge graphs. In: AAAI, pp. 1955\u20131961 (2016)","DOI":"10.1609\/aaai.v30i1.10314"},{"key":"9_CR12","doi-asserted-by":"crossref","unstructured":"Dettmers, T., Minervini, P., Stenetorp, P., Riedel, S.: Convolutional 2D knowledge graph embeddings. In: AAAI, pp. 1811\u20131818 (2018)","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"9_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1007\/978-3-030-04167-0_33","volume-title":"Neural Information Processing","author":"Y Seo","year":"2018","unstructured":"Seo, Y., Defferrard, M., Vandergheynst, P., Bresson, X.: Structured sequence modeling with graph convolutional recurrent networks. In: Cheng, L., Leung, A.C.S., Ozawa, S. (eds.) ICONIP 2018. LNCS, vol. 11301, pp. 362\u2013373. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-04167-0_33"},{"key":"9_CR14","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., et al. (eds.) ESWC 2018. LNCS, vol. 10843, pp. 593\u2013607. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-93417-4_38"},{"key":"9_CR15","unstructured":"Velikovi, P., et al.: Graph attention networks. arXiv preprint arXiv:1710.10903 (2018)"},{"key":"9_CR16","doi-asserted-by":"crossref","unstructured":"Jiang, T., et al.: Encoding temporal information for time-aware link prediction. In: EMNLP, pp. 2350\u20132354 (2016)","DOI":"10.18653\/v1\/D16-1260"},{"key":"9_CR17","doi-asserted-by":"crossref","unstructured":"Dasgupta, S.S., Ray, S.N., Talukdar, P.P.: HyTE: hyperplane-based temporally aware knowledge graph embedding. In: EMNLP, pp. 2001\u20132011 (2018)","DOI":"10.18653\/v1\/D18-1225"},{"key":"9_CR18","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-Dur\u00e1n, A., Dumani, S., Niepert, M.: Learning sequence encoders for temporal knowledge graph completion. arXiv preprint arXiv:1809.03202 (2018)","DOI":"10.18653\/v1\/D18-1516"},{"key":"9_CR19","unstructured":"Pareja A., Domeniconi G., Chen J., et al.: EvolveGCN: evolving graph convolutional networks for dynamic graphs. arXiv preprint arXiv:1902.10191 (2019)"},{"key":"9_CR20","unstructured":"Sun Z., Deng Z H., Nie J Y., et al.: RotatE: knowledge graph embedding by relational rotation in complex space. arXiv preprint arXiv:1902.10197 (2019)"},{"key":"9_CR21","unstructured":"Kipf, T, N., Welling, M.: Semi-Supervised Classification with Graph Convolutional Networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"9_CR22","doi-asserted-by":"crossref","unstructured":"Cho K., Merrienboer, B, V., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014)","DOI":"10.3115\/v1\/D14-1179"},{"key":"9_CR23","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., et al.: Attention is all you need. arXiv preprint arXiv:1706.03762 (2017)"}],"container-title":["Lecture Notes in Computer Science","Web Information Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-20309-1_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,24]],"date-time":"2023-01-24T20:04:07Z","timestamp":1674590647000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20309-1_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031203084","9783031203091"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20309-1_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"8 December 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WISA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Web Information Systems and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dalian","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wisa22022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conf.ccf.org.cn\/web\/html7\/index.html?globalId=m9475032704175349761645943983427&type=1","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":"212","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":"45","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":"19","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":"21% - 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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}