{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T04:04:29Z","timestamp":1750737869103,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819665815","type":"print"},{"value":"9789819665822","type":"electronic"}],"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\/978-981-96-6582-2_19","type":"book-chapter","created":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T14:40:15Z","timestamp":1750689615000},"page":"271-285","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unsupervised Robust Hypergraph Correlation Hashing for\u00a0Multimedia Retrieval"],"prefix":"10.1007","author":[{"given":"Yunfei","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongyu","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Long","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,6,24]]},"reference":[{"key":"19_CR1","doi-asserted-by":"crossref","unstructured":"Cai, D., Song, M., Sun, C., Zhang, B., Hong, S., Li, H.: Hypergraph structure learning for hypergraph neural networks. In: Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22, pp. 1923\u20131929 (2022)","DOI":"10.24963\/ijcai.2022\/267"},{"key":"19_CR2","doi-asserted-by":"crossref","unstructured":"Ding, G., Guo, Y., Zhou, J.: Collective matrix factorization hashing for multimodal data. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2083\u20132090 (2014)","DOI":"10.1109\/CVPR.2014.267"},{"issue":"4","key":"19_CR3","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1109\/TMM.2018.2866771","volume":"21","author":"D Hu","year":"2018","unstructured":"Hu, D., Nie, F., Li, X.: Deep binary reconstruction for cross-modal hashing. IEEE Trans. Multimedia 21(4), 973\u2013985 (2018)","journal-title":"IEEE Trans. Multimedia"},{"issue":"4","key":"19_CR4","doi-asserted-by":"publisher","first-page":"4389","DOI":"10.1007\/s40747-022-00964-7","volume":"9","author":"J Huang","year":"2023","unstructured":"Huang, J., Lei, F., Jiang, J., Zeng, X., Ma, R., Dai, Q.: Multi-order hypergraph convolutional networks integrated with self-supervised learning. Complex Intell. Syst. 9(4), 4389\u20134401 (2023)","journal-title":"Complex Intell. Syst."},{"issue":"1","key":"19_CR5","doi-asserted-by":"publisher","first-page":"576","DOI":"10.1109\/TCSVT.2023.3285266","volume":"34","author":"Y Huo","year":"2024","unstructured":"Huo, Y., et al.: Deep semantic-aware proxy hashing for multi-label cross-modal retrieval. IEEE Trans. Cir. Syst. Video Technol. 34(1), 576\u2013589 (2024)","journal-title":"IEEE Trans. Cir. Syst. Video Technol."},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Li, L., Zheng, B., Sun, W.: Adaptive structural similarity preserving for unsupervised cross modal hashing. In: Proceedings of the 30th ACM International Conference on Multimedia, pp. 3712\u20133721 (2022)","DOI":"10.1145\/3503161.3548431"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Liu, S., Qian, S., Guan, Y., Zhan, J., Ying, L.: Joint-modal distribution-based similarity hashing for large-scale unsupervised deep cross-modal retrieval. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1379\u20131388 (2020)","DOI":"10.1145\/3397271.3401086"},{"issue":"4","key":"19_CR8","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1109\/TBDATA.2024.3350541","volume":"10","author":"X Liu","year":"2024","unstructured":"Liu, X., Li, J., Nie, X., Zhang, X., Wang, S., Yin, Y.: Scalable unsupervised hashing via exploiting robust cross-modal consistency. IEEE Trans. Big Data 10(4), 514\u2013527 (2024)","journal-title":"IEEE Trans. Big Data"},{"key":"19_CR9","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.neunet.2023.05.035","volume":"165","author":"H Ni","year":"2023","unstructured":"Ni, H., et al.: Cross-modal hashing with missing labels. Neural Netw. 165, 60\u201376 (2023)","journal-title":"Neural Netw."},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Song, J., Yang, Y., Yang, Y., Huang, Z., Shen, H.T.: Inter-media hashing for large-scale retrieval from heterogeneous data sources. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pp. 785\u2013796 (2013)","DOI":"10.1145\/2463676.2465274"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Su, S., Zhong, Z., Zhang, C.: Deep joint-semantics reconstructing hashing for large-scale unsupervised cross-modal retrieval. In: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 3027\u20133035 (2019)","DOI":"10.1109\/ICCV.2019.00312"},{"issue":"8","key":"19_CR12","doi-asserted-by":"publisher","first-page":"2765","DOI":"10.1007\/s11263-024-02009-7","volume":"132","author":"J Wang","year":"2024","unstructured":"Wang, J., et al.: Hugs bring double benefits: Unsupervised cross-modal hashing with multi-granularity aligned transformers. Int. J. Comput. Vis. 132(8), 2765\u20132797 (2024)","journal-title":"Int. J. Comput. Vis."},{"issue":"10","key":"19_CR13","doi-asserted-by":"publisher","first-page":"6159","DOI":"10.1109\/TCSVT.2023.3263054","volume":"33","author":"T Wang","year":"2023","unstructured":"Wang, T., Zhu, L., Zhang, Z., Zhang, H., Han, J.: Targeted adversarial attack against deep cross-modal hashing retrieval. IEEE Trans. Cir. Syst. Video Technol. 33(10), 6159\u20136172 (2023)","journal-title":"IEEE Trans. Cir. Syst. Video Technol."},{"issue":"3","key":"19_CR14","first-page":"5","volume":"1","author":"G Wu","year":"2018","unstructured":"Wu, G., et al.: Unsupervised deep hashing via binary latent factor models for large-scale cross-modal retrieval. IJCAI 1(3), 5 (2018)","journal-title":"IJCAI"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Wu, R., Zhu, X., Yi, Z., Zou, Z., Liu, Y., Zhu, L.: Multi-grained similarity preserving and updating for unsupervised cross-modal hashing. Appl. Sci. 14(2) (2024)","DOI":"10.3390\/app14020870"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Yang, C., Ding, S., Li, L., Guo, J.: Graph attention hashing via contrastive learning for unsupervised cross-modal retrieval. In: Neural Information Processing, pp. 497\u2013509 (2024)","DOI":"10.1007\/978-981-99-8181-6_38"},{"key":"19_CR17","doi-asserted-by":"publisher","unstructured":"Yu, H., Ma, R., Su, M., An, P., Li, K.: A novel deep translated attention hashing for cross-modal retrieval. In: Multimedia Tools and Applications, pp. 1\u201319 (2022). https:\/\/doi.org\/10.1007\/s11042-022-12860-w","DOI":"10.1007\/s11042-022-12860-w"},{"issue":"3","key":"19_CR18","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1007\/s12559-021-09847-4","volume":"14","author":"J Yu","year":"2022","unstructured":"Yu, J., Wu, X.J., Zhang, D.: Unsupervised multi-modal hashing for cross-modal retrieval. Cogn. Comput. 14(3), 1159\u20131171 (2022)","journal-title":"Cogn. Comput."},{"issue":"10","key":"19_CR19","doi-asserted-by":"publisher","first-page":"3437","DOI":"10.1007\/s13042-023-01842-5","volume":"14","author":"X Zeng","year":"2023","unstructured":"Zeng, X., Xu, K., Xie, Y.: Pseudo-label driven deep hashing for unsupervised cross-modal retrieval. Int. J. Mach. Learn. Cybern. 14(10), 3437\u20133456 (2023)","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"19_CR20","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1109\/TMM.2021.3053766","volume":"24","author":"PF Zhang","year":"2021","unstructured":"Zhang, P.F., Li, Y., Huang, Z., Xu, X.S.: Aggregation-based graph convolutional hashing for unsupervised cross-modal retrieval. IEEE Trans. Multimedia 24, 466\u2013479 (2021)","journal-title":"IEEE Trans. Multimedia"},{"key":"19_CR21","first-page":"521","volume":"2022","author":"Y Zhao","year":"2023","unstructured":"Zhao, Y., Yu, J., Liao, S., Zhang, Z., Zhang, H.: From sparse to dense: semantic graph evolutionary hashing for unsupervised cross-modal retrieval. Comput. Vis. ACCV 2022, 521\u2013536 (2023)","journal-title":"Comput. Vis. ACCV"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Zhou, J., Ding, G., Guo, Y.: Latent semantic sparse hashing for cross-modal similarity search. In: Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, pp. 415\u2013424 (2014)","DOI":"10.1145\/2600428.2609610"},{"issue":"5","key":"19_CR23","doi-asserted-by":"publisher","first-page":"4915","DOI":"10.1007\/s11760-024-03126-z","volume":"18","author":"K Zhou","year":"2024","unstructured":"Zhou, K., Hassan, F.H., Gan, K.H.: Pretrained models for cross-modal retrieval: experiments and improvements. SIViP 18(5), 4915\u20134923 (2024)","journal-title":"SIViP"},{"issue":"9","key":"19_CR24","doi-asserted-by":"publisher","first-page":"8838","DOI":"10.1109\/TKDE.2022.3218656","volume":"35","author":"L Zhu","year":"2023","unstructured":"Zhu, L., Wu, X., Li, J., Zhang, Z., Guan, W., Shen, H.T.: Work together: correlation-identity reconstruction hashing for unsupervised cross-modal retrieval. IEEE Trans. Knowl. Data Eng. 35(9), 8838\u20138851 (2023)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"19_CR25","doi-asserted-by":"crossref","unstructured":"Zhu, X., Yi, Z., Ouyang, N., Zhang, H., Zou, Z., Yi, Z.: Multi-label contrastive semantics preserving based cross-modal hashing. In: 2023 International Conference on Cyber-Physical Social Intelligence (ICCSI), pp. 162\u2013167 (2023)","DOI":"10.1109\/ICCSI58851.2023.10303943"}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-6582-2_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T14:40:21Z","timestamp":1750689621000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-6582-2_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819665815","9789819665822"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-6582-2_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"24 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Auckland","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"New Zealand","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 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iconip2024.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}