{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:39:11Z","timestamp":1757619551299,"version":"3.44.0"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819698806"},{"type":"electronic","value":"9789819698813"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-9881-3_13","type":"book-chapter","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T21:16:12Z","timestamp":1753391772000},"page":"147-158","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Combining Improved Relational Embedding and Multi-Hop Sampling for Temporal Knowledge Graph Reasoning"],"prefix":"10.1007","author":[{"given":"Jun","family":"Pang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuheng","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoli","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengxiang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,25]]},"reference":[{"issue":"1","key":"13_CR1","first-page":"277","volume":"34","author":"T Zhang","year":"2023","unstructured":"Zhang, T., Tian, X., Sun, X., et al.: Overview on knowledge graph embedding technology research. J. Softw. 34(1), 277\u2013311 (2023)","journal-title":"J. Softw."},{"issue":"08","key":"13_CR2","first-page":"3923","volume":"35","author":"Y Wang","year":"2024","unstructured":"Wang, Y., Chen, Z., Zhao, X., et al.: Research progress and trend of temporal knowledge graph representation and reasoning. J. Softw. 35(08), 3923\u20133951 (2024)","journal-title":"J. Softw."},{"issue":"06","key":"13_CR3","first-page":"1272","volume":"46","author":"Y Shen","year":"2023","unstructured":"Shen, Y., Jiang, X., Wang, Y., et al.: A survey of temporal knowledge graph reasoning. Chin. J. Comput. 46(06), 1272\u20131301 (2023)","journal-title":"Chin. J. Comput."},{"key":"13_CR4","unstructured":"Omran, P.G., et al: Learning temporal rules from knowledge graph streams. In: AAAI 2019 Spring Symposium: Combining Machine Learning with Knowledge Engineering, Palo Alto, California, USA, March 25\u201327 (2019)"},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Li, Z., et al.: Search from history and reason for future: two-stage reasoning on temporal knowledge graphs. In: ACL-IJCNLP 2021, Volume 1: Long Papers, pp. 4732\u20134743 (2021)","DOI":"10.18653\/v1\/2021.acl-long.365"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Liu, Y., Ma, Y., Hildebrandt, M., Joblin, M., Tresp, V.: TLogic: temporal logical rules for explainable link forecasting on temporal knowledge graphs. In: AAAI Conference on Artificial Intelligence, 36(4), 4120\u20134127 (2022)","DOI":"10.1609\/aaai.v36i4.20330"},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Sun, H., Zhong J., Ma, Y., Zhen, H., He, K.: TimeTraveler: reinforcement learning for temporal knowledge graph forecasting. In: The 2021 Conference on Empirical Methods in Natural Language Processing, pp. 8306\u20138319 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.655"},{"key":"13_CR8","unstructured":"Trivedi, R., Dai, H., Wang, Y., Song, L.: Know-evolve: deep temporal reasoning for dynamic knowledge graphs. In: The 34th International Conference on Machine Learning, PMLR, 70, 3462\u20133417 (2017)"},{"key":"13_CR9","doi-asserted-by":"crossref","unstructured":"Lu, Y., Wang, X., Shi, C., Yu, S., Ye, Y.: Temporal network embedding with micro- and macro-dynamics. In: The 28th ACM International Conference on Information and Knowledge Management, pp. 469\u2013478 (2019)","DOI":"10.1145\/3357384.3357943"},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Park, N., et al.: EvoKG: jointly modeling event time and network structure for reasoning over temporal knowledge graphs. In: The 15th ACM International Conference on Web Search and Data Mining, pp. 794\u2013803 (2022)","DOI":"10.1145\/3488560.3498451"},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Li, Z., et al.: Temporal knowledge graph reasoning based on evolutional representation learning. In: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 408\u2013417 (2021)","DOI":"10.1145\/3404835.3462963"},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Li, Y., Sun, S., Zhao, J.: TiRGN: time-guided recurrent graph network with local-global historical patterns for temporal knowledge graph reasoning. In: The 31st International Joint Conference on Artificial Intelligence, IJCAI, pp. 2152\u20132158 (2022)","DOI":"10.24963\/ijcai.2022\/299"},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Liu, K., Zhao, F., Xu, G., Wang, X., Jin, H.: RETIA: relation-entity twin-interact aggregation for temporal knowledge graph extrapolation. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp.1761\u20131774 (2023)","DOI":"10.1109\/ICDE55515.2023.00138"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Zhang, M., et al: Learning long- and short-term representations for temporal knowledge graph reasoning. In: ACM Web Conference, pp. 2412\u20132422 (2023)","DOI":"10.1145\/3543507.3583242"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Liang, K., et al.: Learn from relational correlations and periodic events for temporal knowledge graph reasoning. In: the 46th ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1559\u20131568 (2023)","DOI":"10.1145\/3539618.3591711"},{"issue":"11","key":"13_CR16","doi-asserted-by":"publisher","first-page":"7115","DOI":"10.1109\/TKDE.2024.3390683","volume":"36","author":"F Zhang","year":"2024","unstructured":"Zhang, F., et al.: Temporal knowledge graph reasoning with dynamic memory enhancement. IEEE Trans. Knowl. Data Eng. 36(11), 7115\u20137128 (2024)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"Geng, Y., et al.: Relational message passing for fully inductive knowledge graph completion. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 1221\u20131233 (2023)","DOI":"10.1109\/ICDE55515.2023.00098"},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Shang, C., et al.: End-to-end structure-aware convolutional networks for knowledge base completion. In: AAAI Conference on Artificial Intelligence, vol. 33(01), pp. 3060\u20133067 (2019)","DOI":"10.1609\/aaai.v33i01.33013060"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-Dur\u00e1n, A., Duman\u010di\u0107, S., Niepert, M.: Learning sequence encoders for temporal knowledge graph completion. In: The 2018 Conference on Empirical Methods in Natural Language Processing, pp. 4816\u20134821 (2018)","DOI":"10.18653\/v1\/D18-1516"},{"key":"13_CR20","unstructured":"Mahdisoltani, F., Biega, J., Suchanek, F.: Yago3: a knowledge base from multilingual wikipedias. In: CIDR 2015, pp.1\u201311 (2015)"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Leblay, J., Chekol, M.: Deriving validity time in knowledge graph. In: Companion proceedings of the The Web Conference, pp. 1771\u20131776 (2018)","DOI":"10.1145\/3184558.3191639"},{"key":"13_CR22","doi-asserted-by":"publisher","unstructured":"Huang, Y.\u00a0et al.: Feature Interaction for temporal knowledge graph extrapolation. In: Huang, DS., Chen, W., Zhang, Q. (eds.) ICIC 2024. LNCS, vol 14874, pp.379\u2013391. Springer, Singapore (2024). https:\/\/doi.org\/10.1007\/978-981-97-5618-6_32","DOI":"10.1007\/978-981-97-5618-6_32"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9881-3_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T22:21:50Z","timestamp":1757283710000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9881-3_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819698806","9789819698813"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9881-3_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"25 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}