{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T11:59:58Z","timestamp":1768305598973,"version":"3.49.0"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032093172","type":"print"},{"value":"9783032093189","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T00:00:00Z","timestamp":1762646400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T00:00:00Z","timestamp":1762646400000},"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\/978-3-032-09318-9_12","type":"book-chapter","created":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T06:22:05Z","timestamp":1762582925000},"page":"167-182","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Privacy-Aware Knowledge Transfer for\u00a0Cross-Domain Recommender System"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7082-561X","authenticated-orcid":false,"given":"Pham Minh Thu","family":"Do","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0690-4732","authenticated-orcid":false,"given":"Jie","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9977-8418","authenticated-orcid":false,"given":"Qian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3960-0583","authenticated-orcid":false,"given":"Guangquan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,11,9]]},"reference":[{"key":"12_CR1","doi-asserted-by":"crossref","unstructured":"Lu, J., Xuan, J., Zhang, G., Luo, x.: Structural property-aware multilayer network embedding for latent factor analysis. Pattern Recognition, 76, 228-241 (2018)","DOI":"10.1016\/j.patcog.2017.11.004"},{"key":"12_CR2","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1016\/j.ins.2018.07.029","volume":"471","author":"M Mao","year":"2019","unstructured":"Mao, M., Lu, J., Han, J., Zhang, G.: Multiobjective e-commerce recommendations based on hypergraph ranking. Inf. Sci. 471, 269\u2013287 (2019)","journal-title":"Inf. Sci."},{"key":"12_CR3","unstructured":"Zhang, Q., Lu, J., Zhang, G.: Recommender systems in e-learning. J. Smart Environ. Green Comput. 1(2), 76-89,"},{"key":"12_CR4","doi-asserted-by":"crossref","unstructured":"Zhao, C., Li, C., Fu, C.: Cross-domain recommendation via preference propagation GraphNet. In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 2165-2168, (2019)","DOI":"10.1145\/3357384.3358166"},{"key":"12_CR5","unstructured":"Zhang, Q., Liao, W., Zhang, G., Yuan, B., Lu, J.: A deep dual adversarial network for cross-domain recommendation. IEEE Trans. Knowl. Data Eng. (2021)"},{"key":"12_CR6","doi-asserted-by":"crossref","unstructured":"Liu, M., Li, J., Li, G., Pan, P.: Cross domain recommendation via bi-directional transfer graph collaborative filtering networks. In: Proceedings of the 29th ACM International Conference on Information and Knowledge management, pp. 885-894, (2020)","DOI":"10.1145\/3340531.3412012"},{"key":"12_CR7","doi-asserted-by":"crossref","unstructured":"Cao, J., Lin, X., Cong, X., Ya, J., Liu, T., Wang, B.: DisenCDR: learning disentangled representations for cross-domain recommendation. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 267-277, (2022)","DOI":"10.1145\/3477495.3531967"},{"key":"12_CR8","doi-asserted-by":"crossref","unstructured":"Zhu, F., Wang, Y., Chen, C., Zhou, J., Li, L., Liu, G.: Cross-domain recommendation: challenges, progress, and prospects. In: 30th International Joint Conference on Artificial Intelligence, IJCAI, pp. 4721-4728, (2021)","DOI":"10.24963\/ijcai.2021\/639"},{"issue":"5","key":"12_CR9","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/MIS.2020.3014880","volume":"36","author":"D Chai","year":"2020","unstructured":"Chai, D., Wang, L., Chen, K., Yang, Q.: Secure federated matrix factorization. IEEE Intell. Syst. 36(5), 11\u201320 (2020)","journal-title":"IEEE Intell. Syst."},{"issue":"4","key":"12_CR10","first-page":"1","volume":"13","author":"C Wu","year":"2020","unstructured":"Wu, C., Wu, F., Lyu, L., Huang, Y., Xie, X.: FedCTR: federated native ad CTR prediction with cross-platform user behavior data. ACM Trans. Intell. Syst. Technol. (TIST) 13(4), 1\u201319 (2020)","journal-title":"ACM Trans. Intell. Syst. Technol. (TIST)"},{"key":"12_CR11","doi-asserted-by":"crossref","unstructured":"Chen, C., Wu, H., Su, J., Lyu, L., Zheng, X., Wang, L.: Differential private knowledge transfer for privacy-preserving cross-domain recommendation. In: Proceedings of the ACM Web Conference, pp. 1455-1465, (2022)","DOI":"10.1145\/3485447.3512192"},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"Liu, W., et al.: Differentially private sparse mapping for privacy-preserving cross domain recommendation. In: Proceedings of the 31st ACM International Conference on Multimedia, pp. 6243-6252, (2023)","DOI":"10.1145\/3581783.3611924"},{"key":"12_CR13","doi-asserted-by":"crossref","unstructured":"Meihan, W., Li, L., Tao, C., Rigall, E., Xiaodong, W., Cheng-Zhong, X.: Fedcdr: federated cross-domain recommendation for privacy-preserving rating prediction. In: Proceedings of the 31st ACM International Conference on Information and Knowledge Management, pp. 2179-2188, (2022)","DOI":"10.1145\/3511808.3557320"},{"issue":"4","key":"12_CR14","first-page":"4149","volume":"37","author":"G Chen","year":"2023","unstructured":"Chen, G., et al.: Win-win: a privacy-preserving federated framework for dual-target cross-domain recommendation. Proc. AAAI Conf. Artif. Intell. 37(4), 4149\u20134156 (2023)","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"issue":"5","key":"12_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3653448","volume":"42","author":"C Tian","year":"2024","unstructured":"Tian, C., Xie, Y., Chen, X., Li, Y., Zhao, X.: Privacy-preserving cross-domain recommendation with federated graph learning. ACM Trans. Inf. Syst. 42(5), 1\u201329 (2024)","journal-title":"ACM Trans. Inf. Syst."},{"key":"12_CR16","unstructured":"Cui, Q., Wei, T., Zhang, Y., Zhang, Q.: HeroGRAPH: a heterogeneous graph framework for multi-target cross-domain recommendation,ORSUM@ RecSys, (2020)"},{"key":"12_CR17","doi-asserted-by":"crossref","unstructured":"Zhu, F., Wang, Y., Chen, C., Liu, G., Zheng, X.: A graphical and attentional framework for dual-target cross-domain recommendation. In: Proceedings of the 29th International Joint Conference on Artificial Intelligence, pp. 3001\u20133008, (2020)","DOI":"10.24963\/ijcai.2020\/415"},{"key":"12_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1007\/11681878_14","volume-title":"Theory of Cryptography","author":"C Dwork","year":"2006","unstructured":"Dwork, C., McSherry, F., Nissim, K., Smith, A.: Calibrating Noise to Sensitivity in Private Data Analysis. In: Halevi, S., Rabin, T. (eds.) TCC 2006. LNCS, vol. 3876, pp. 265\u2013284. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11681878_14"},{"key":"12_CR19","doi-asserted-by":"crossref","unstructured":"Liao, X., Liu, W., Zheng, X., Yao, B., Chen, C.: Ppgencdr: a stable and robust framework for privacy-preserving cross-domain recommendation. In: Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 37, No. 4, pp. 4453-4461, (2023)","DOI":"10.1609\/aaai.v37i4.25566"},{"key":"12_CR20","unstructured":"Sun, Z., et al.: A survey on federated recommendation systems. IEEE Trans. Neural Netw. Learn. Syst. (2024)"},{"key":"12_CR21","doi-asserted-by":"crossref","unstructured":"He, X., Deng, K., Wang, X., Li, Y., Zhang, Y., Wang, M.: Lightgcn: simplifying and powering graph convolution network for recommendation. In: Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, pp. 639-648, (2020)","DOI":"10.1145\/3397271.3401063"},{"key":"12_CR22","unstructured":"Van der Maaten, L., Hinton, G.: Visualizing data using t-SNE. J. Mach. Learn. Res. 9(11), (2008)"},{"key":"12_CR23","unstructured":"Vaswani, A.: Attention is all you need. Adv. Neural Inf. Proc. Syst. (2017)"},{"key":"12_CR24","doi-asserted-by":"crossref","unstructured":"Song, W., et al.: Session-based social recommendation via dynamic graph attention networks. In: Proceedings of the ACM international conference on web search and data mining ,pp. 555-563, (2019)","DOI":"10.1145\/3289600.3290989"},{"key":"12_CR25","doi-asserted-by":"crossref","unstructured":"He, X., Liao, L., Zhang, H., Nie, L., Hu, X., Chua, T.S.: Neural collaborative filtering. In: Proceedings of the 26th International Conference on World Wide Web, pp. 173-182, (2017)","DOI":"10.1145\/3038912.3052569"}],"container-title":["Lecture Notes in Computer Science","Computational Collective Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-09318-9_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T05:02:33Z","timestamp":1768280553000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-09318-9_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,9]]},"ISBN":["9783032093172","9783032093189"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-09318-9_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,9]]},"assertion":[{"value":"9 November 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCCI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Collective Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ho Chi Minh City","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","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":"12 November 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 November 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccci2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iccci.pwr.edu.pl\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}