{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:19:18Z","timestamp":1767320358423,"version":"3.48.0"},"publisher-location":"Singapore","reference-count":34,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819550111","type":"print"},{"value":"9789819550128","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-5012-8_3","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:14:32Z","timestamp":1767320072000},"page":"35-50","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GCLP: Generative Contrastive Learning with\u00a0Adaptive Prompt-Guided Diffusion for\u00a0Temporal Reasoning over\u00a0Service Knowledge Graphs"],"prefix":"10.1007","author":[{"given":"Yukun","family":"Cao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lisheng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunfeng","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihao","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuefeng","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luobin","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zirui","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"3_CR1","doi-asserted-by":"crossref","unstructured":"Chen, Z., Xu, C., Su, F., Huang, Z., Dou, Y.: Temporal extrapolation and knowledge transfer for lifelong temporal knowledge graph reasoning. In: EMNLP, pp. 6736\u20136746, (2023)","DOI":"10.18653\/v1\/2023.findings-emnlp.448"},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Xia, Y., Wang, D., Liu, Q., Wang, L., Wu, S., Zhang, X.Y.: Chain-of-history reasoning for temporal knowledge graph forecasting. In: ACL (2024)","DOI":"10.18653\/v1\/2024.findings-acl.955"},{"key":"3_CR3","doi-asserted-by":"crossref","unstructured":"Chen, Q., Chen, L.: Decrl: a deep evolutionary clustering jointed temporal knowledge graph representation learning approach. In: NeurIPS, vol. 37, 55204\u201355227 (2024)","DOI":"10.52202\/079017-1752"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Sun, H., Geng, S., Zhong, J., Hu, H., He, K.: Graph Hawkes transformer for extrapolated reasoning on temporal knowledge graphs. In: EMNLP, pp. 7481\u20137493 (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.507"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Fang, Z.: Transformer-based reasoning for learning evolutionary chain of events on temporal knowledge graph. In: SIGIR, pp. 70\u201379 (2024)","DOI":"10.1145\/3626772.3657706"},{"key":"3_CR6","unstructured":"Wang, R., et al.: Learning to sample and aggregate: few-shot reasoning over temporal knowledge graphs. In: NeurIPS, vol. 35, pp. 16863\u201316876 (2022)"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Ding, Z., et al.: ZRLLM: zero-shot relational learning on temporal knowledge graphs with large language models. In: NAACL (2023)","DOI":"10.18653\/v1\/2024.naacl-long.104"},{"key":"3_CR8","unstructured":"Wang, Y., Zeqian, J., et al.: Audit: audio editing by following instructions with latent diffusion models. In: NeurIPS, vol. 36, pp. 71340\u201371357 (2023)"},{"key":"3_CR9","unstructured":"Ou, Y., Jian, P.: Effective integration of text diffusion and pre-trained language models with linguistic easy-first schedule. In: COLING, pp. 5551\u20135561 (2024)"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Miao, Z., Wang, J., et\u00a0al.: Training diffusion models towards diverse image generation with reinforcement learning. In: CVPR, pp. 10844\u201310853 (2024)","DOI":"10.1109\/CVPR52733.2024.01031"},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Cai, Y., Liu, Q., Gan, Y., et\u00a0al. Predicting the unpredictable: uncertainty-aware reasoning over temporal knowledge graphs via diffusion process. In: ACL, pp. 5766\u20135778 (2024)","DOI":"10.18653\/v1\/2024.findings-acl.343"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Cao, Y., Wang, L., Huang, L.: Dpcl-diff: Temporal knowledge graph reasoning based on graph node diffusion model with dual-domain periodic contrastive learning. In: AAAI, vol. 39, pp. 14806\u201314814 (2025)","DOI":"10.1609\/aaai.v39i14.33623"},{"key":"3_CR13","doi-asserted-by":"crossref","unstructured":"Ying, R., Hu, M., Wu, J., et\u00a0al.: Simple but effective compound geometric operations for temporal knowledge graph completion. In: ACL (2024)","DOI":"10.18653\/v1\/2024.acl-long.596"},{"key":"3_CR14","doi-asserted-by":"crossref","unstructured":"Li, J., Su, X., Gao, G.: Teast: temporal knowledge graph embedding via archimedean spiral timeline. In: ACL, pp. 15460\u201315474 (2023)","DOI":"10.18653\/v1\/2023.acl-long.862"},{"key":"3_CR15","doi-asserted-by":"crossref","unstructured":"Wang, K., \u00a0 Han, S.C., et\u00a0al.: Re-temp: relation-aware temporal representation learning for temporal knowledge graph completion. In: EMNLP (2023)","DOI":"10.18653\/v1\/2023.findings-emnlp.20"},{"key":"3_CR16","unstructured":"Trivedi, R., Dai, H., Wang, Y., Song, L., et\u00a0al.: Know-evolve: deep temporal reasoning for dynamic knowledge graphs. In: ICML, pp. 3462\u20133471. PMLR (2017)"},{"key":"3_CR17","doi-asserted-by":"crossref","unstructured":"Zhu, C., Chen, M., Fan, C., et al.: Learning from history: modeling temporal knowledge graphs with sequential copy-generation networks. In: AAAI, vol. 35, pp. 4732\u20134740 (2021)","DOI":"10.1609\/aaai.v35i5.16604"},{"key":"3_CR18","doi-asserted-by":"crossref","unstructured":"Yi, X., Junjie, O., Hui, X., Luoyi, F.: Temporal knowledge graph reasoning with historical contrastive learning. In: AAAI, vol. 37, pp. 4765\u20134773 (2023)","DOI":"10.1609\/aaai.v37i4.25601"},{"key":"3_CR19","unstructured":"Liu, X., Zhang, J., et\u00a0al.: Temporal knowledge graph reasoning with dynamic hypergraph embedding. In: COLING, pp. 15742\u201315751 (2024)"},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Pareja, A., Domeniconi, G., et al.: Evolvegcn: evolving graph convolutional networks for dynamic graphs. In: AAAI, vol. 34, pp. 5363\u20135370 (2020)","DOI":"10.1609\/aaai.v34i04.5984"},{"key":"3_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2023.102292","volume":"120","author":"R Liu","year":"2024","unstructured":"Liu, R., Yin, G., et al.: Reinforcement learning with time intervals for temporal knowledge graph reasoning. Inf. Syst. 120, 102292 (2024)","journal-title":"Inf. Syst."},{"key":"3_CR22","doi-asserted-by":"crossref","unstructured":"Wu, J., Cao, M., Cheung, J.C.K. and Hamilton, W.L.: Temp: temporal message passing for temporal knowledge graph completion. In: EMNLP (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.462"},{"key":"3_CR23","doi-asserted-by":"crossref","unstructured":"Khattak, M.U., Rasheed, H., Maaz, M., et\u00a0al. Maple: multi-modal prompt learning. In: CVPR, pp. 19113\u201319122 (2023)","DOI":"10.1109\/CVPR52729.2023.01832"},{"key":"3_CR24","doi-asserted-by":"crossref","unstructured":"Qu, B., Li, H., Gao, W.: Bringing textual prompt to ai-generated image quality assessment. In: ICME, pp. 1\u20136. IEEE (2024)","DOI":"10.1109\/ICME57554.2024.10688254"},{"key":"3_CR25","doi-asserted-by":"crossref","unstructured":"Jin, W., Qu, M., et\u00a0al. Recurrent event network: Autoregressive structure inference over temporal knowledge graphs. arXiv preprint arXiv:1904.05530 (2019)","DOI":"10.18653\/v1\/2020.emnlp-main.541"},{"key":"3_CR26","doi-asserted-by":"crossref","unstructured":"Leblay, J., Chekol, M.W.: Deriving validity time in knowledge graph. In: WWW, pp. 1771\u20131776 (2018)","DOI":"10.1145\/3184558.3191639"},{"key":"3_CR27","unstructured":"Mahdisoltani, F., Biega, J., Suchanek, F.M.: Yago3: a knowledge base from multilingual wikipedias. In: CIDR (2013)"},{"key":"3_CR28","doi-asserted-by":"crossref","unstructured":"Liang, K., Meng, L., et\u00a0al.: Learn from relational correlations and periodic events for temporal knowledge graph reasoning. In: SIGIR, pp. 1559\u20131568 (2023)","DOI":"10.1145\/3539618.3591711"},{"key":"3_CR29","unstructured":"Trouillon, T., Welbl, J., Riedel, S., et\u00a0al.: Complex embeddings for simple link prediction. In: ICML, pp. 2071\u20132080. PMLR (2016)"},{"key":"3_CR30","doi-asserted-by":"crossref","unstructured":"Schlichtkrull, M., Kipf, T.N., Bloem, P., et\u00a0al.: Modeling relational data with graph convolutional networks. In: ESWC, pp. 593\u2013607. Springer (2018)","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"3_CR31","doi-asserted-by":"crossref","unstructured":"Dettmers, T., Minervini, P., Stenetorp, P., Riedel, S.: Convolutional 2D knowledge graph embeddings. In: AAAI, vol.\u00a032, (2018)","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"3_CR32","unstructured":"Han, Z., Chen, P., Ma,\u00a0Y., Tresp, V.: Explainable subgraph reasoning for forecasting on temporal knowledge graphs. In: ICLR (2021)"},{"key":"3_CR33","doi-asserted-by":"crossref","unstructured":"Park, N., Liu, F., Mehta, P., Cristofor, D., Faloutsos, C., Dong, Y.: Evokg: jointly modeling event time and network structure for reasoning over temporal knowledge graphs. In: WSDM, pp. 794\u2013803, (2022)","DOI":"10.1145\/3488560.3498451"},{"key":"3_CR34","unstructured":"Lv, A., Huang, Y., et\u00a0al.: Rlgnet: Repeating-local-global history network for temporal knowledge graph reasoning. arXiv preprint arXiv:2404.00586 (2024)"}],"container-title":["Lecture Notes in Computer Science","Service-Oriented Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5012-8_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:14:36Z","timestamp":1767320076000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5012-8_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819550111","9789819550128"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5012-8_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSOC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Service-Oriented Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","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":"1 December 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icsoc2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icsoc2025.hit.edu.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}