{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T15:51:26Z","timestamp":1774021886499,"version":"3.50.1"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"14","license":[{"start":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:00:00Z","timestamp":1647907200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:00:00Z","timestamp":1647907200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2022,11]]},"DOI":"10.1007\/s10489-022-03216-w","type":"journal-article","created":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T06:02:50Z","timestamp":1647928970000},"page":"16310-16333","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Social network alignment: a bi-layer graph attention neural networks based method"],"prefix":"10.1007","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2199-2195","authenticated-orcid":false,"given":"Meilian","family":"Lu","sequence":"first","affiliation":[]},{"given":"Yinlong","family":"Dai","sequence":"additional","affiliation":[]},{"given":"Zhiqiang","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,3,22]]},"reference":[{"key":"3216_CR1","doi-asserted-by":"crossref","unstructured":"Kong X, Zhang J, Yu PS (2013) Inferring anchor links across multiple heterogeneous social networks. In: Proc. of the 22nd ACM CIKM, pp. 179\u2013188","DOI":"10.1145\/2505515.2505531"},{"key":"3216_CR2","doi-asserted-by":"crossref","unstructured":"Zhang J, Chen J, Zhi S, Chang Y, Yu PS, Han J (2017) Link prediction across aligned networks with sparse and low rank matrix estimation. In: IEEE 33rd ICDE, pp. 971\u2013982","DOI":"10.1109\/ICDE.2017.144"},{"key":"3216_CR3","unstructured":"Lu C-T, Xie S, Shao W, He L, Yu PS (2016) Item recommendation for emerging online businesses. In: Proc. of the 25th IJCAI, pp. 3797\u20133803"},{"key":"3216_CR4","doi-asserted-by":"crossref","unstructured":"Zhan Q, Zhang J, Wang S, Yu PS, Xie J (2015) Influence maximization across partially aligned heterogeneous social networks. In: Proc. of Advances in Knowledge Discovery and Data Mining. Springer International Publishing, pp 58\u201369","DOI":"10.1007\/978-3-319-18038-0_5"},{"key":"3216_CR5","doi-asserted-by":"crossref","unstructured":"Wu J, Zhao Z, Sun Q, Hamido F (2021) A maximum self-esteem degree based feedback mechanism for group consensus reaching with the distributed linguistic trust propagation in social network. Inf Fusion 67:80\u201393","DOI":"10.1016\/j.inffus.2020.10.010"},{"key":"3216_CR6","unstructured":"Zhang J, Yu PS (2015) Integrated anchor and social link predictions across social networks. In: Proc. of the 24th International Conference on Artificial Intelligence, Buenos Aires, Argentina, pp. 2125\u20132131"},{"key":"3216_CR7","doi-asserted-by":"crossref","unstructured":"Zhang J, Yu PS (2015) Multiple anonymized social networks alignment. In: Proc. of the 2015 ICDM, Washington, DC, USA, pp. 599\u2013608","DOI":"10.1109\/ICDM.2015.114"},{"key":"3216_CR8","doi-asserted-by":"crossref","unstructured":"Liu J, Zhang F, Song X, Song Y-I, Lin C-Y, Hon H-W (2013) What\u2019s in a name?: An unsupervised approach to link users across communities. In: Proc. of the Sixth ACM WSDM, New York, NY, USA, pp. 495\u2013504","DOI":"10.1145\/2433396.2433457"},{"key":"3216_CR9","doi-asserted-by":"crossref","unstructured":"Liu S, Wang S, Zhu F, Zhang J, Krishnan R (2014) HYDRA: Large-scale social identity linkage via heterogeneous behavior modeling. In: Proc. of the 2014 ACM SIGMOD, New York, NY, USA, pp. 51\u201362","DOI":"10.1145\/2588555.2588559"},{"key":"3216_CR10","doi-asserted-by":"crossref","unstructured":"Tan S, Guan Z, Cai D, Qin X, Bu J, Chen C (2014) Mapping users across networks by manifold alignment on hypergraph. In: Proc. of the 28th AAAI, Qu\u00e9bec city, Qu\u00e9bec, Canada, pp. 159\u2013165","DOI":"10.1609\/aaai.v28i1.8720"},{"key":"3216_CR11","doi-asserted-by":"crossref","unstructured":"Zhang H, Kan M-Y, Liu Y, Ma S (2014) Online social network profile linkage. In: Asia Information Retrieval Symposium. Springer International Publishing, pp 197\u2013208","DOI":"10.1007\/978-3-319-12844-3_17"},{"issue":"2","key":"3216_CR12","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1109\/TKDE.2015.2485222","volume":"28","author":"X Zhou","year":"2016","unstructured":"Zhou X, Liang X, Zhang H, Ma Y (Feb. 2016) Cross-platform identification of anonymous identical users in multiple social media networks. IEEE Trans Knowl Data Eng 28(2):411\u2013424","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3216_CR13","unstructured":"Liu L, Cheung WK, Li X, Liao L (2016) Aligning users across social networks using network embedding. In: Proc. of the 25th IJCAI, New York, USA, pp. 1774\u20131780"},{"key":"3216_CR14","unstructured":"Zhang W, Shu K, Liu H, Wang Y (2019) Graph neural networks for user identity linkage, ArXiv190302174 Cs"},{"issue":"12","key":"3216_CR15","doi-asserted-by":"publisher","first-page":"5834","DOI":"10.1109\/TNNLS.2018.2812888","volume":"29","author":"W Zhao","year":"2018","unstructured":"Zhao W, Tan S, Guan Z, Zhang B, Gong M, Cao Z, Wang Q (Dec. 2018) Learning to map social network users by unified manifold alignment on hypergraph. IEEE Trans Neural Netw Learn Syst 29(12):5834\u20135846","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"3216_CR16","doi-asserted-by":"crossref","unstructured":"Zhang Y, Tang J, Yang Z, Pei J, Yu PS (2015) COSNET: Connecting heterogeneous social networks with local and global consistency. In: Proc. of the 21th ACM SIGKDD, New York, USA, pp. 1485\u20131494","DOI":"10.1145\/2783258.2783268"},{"issue":"6","key":"3216_CR17","doi-asserted-by":"publisher","first-page":"1178","DOI":"10.1109\/TKDE.2017.2784430","volume":"30","author":"X Zhou","year":"2018","unstructured":"Zhou X, Liang X, Du X, Zhao J (Jun. 2018) Structure based user identification across social networks. IEEE Trans Knowl Data Eng 30(6):1178\u20131191","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3216_CR18","doi-asserted-by":"crossref","unstructured":"Xie W, Mu X, Lee RK-W, Zhu F, Lim E-P (2018) Unsupervised user identity linkage via factoid embedding. In: 2018 ICDM, pp. 1338\u20131343","DOI":"10.1109\/ICDM.2018.00182"},{"issue":"2","key":"3216_CR19","doi-asserted-by":"publisher","first-page":"16:1","DOI":"10.1145\/2747880","volume":"10","author":"R Zafarani","year":"2015","unstructured":"Zafarani R, Tang L, Liu H (Oct. 2015) User identification across social media. ACM Trans Knowl Discov Data 10(2):16:1\u201316:30","journal-title":"ACM Trans Knowl Discov Data"},{"key":"3216_CR20","doi-asserted-by":"publisher","first-page":"17340","DOI":"10.1109\/ACCESS.2018.2814000","volume":"6","author":"S Feng","year":"2018","unstructured":"Feng S, Shen D, Nie T, Kou Y, He J, Yu G (2018) Inferring anchor links based on social network structure. IEEE Access 6:17340\u201317353","journal-title":"IEEE Access"},{"key":"3216_CR21","doi-asserted-by":"crossref","unstructured":"Qu Y, Sun Z, Hu W, Zhang Q (2018) Bootstrapping entity alignment with knowledge graph embedding. In: 2018 IJCAI, pp. 4396\u20134402","DOI":"10.24963\/ijcai.2018\/611"},{"key":"3216_CR22","doi-asserted-by":"crossref","unstructured":"Cheng A, Liu C-Y, Zhou C, Tan J, Guo L (2018) User alignment via structural interaction and propagation. In: 2018 IJCNN, pp. 1\u20138","DOI":"10.1109\/IJCNN.2018.8489228"},{"key":"3216_CR23","doi-asserted-by":"crossref","unstructured":"Huynh TT, Tong VV, Duong CT, Huynh Quyet T, Nguyen QVH, Sattar A (2019) Network alignment by representation learning on structure and attribute. In: PRICAI 2019: Trends in Artificial Intelligence, Cham, pp. 698\u2013711","DOI":"10.1007\/978-3-030-29911-8_54"},{"key":"3216_CR24","doi-asserted-by":"publisher","first-page":"105301","DOI":"10.1016\/j.knosys.2019.105301","volume":"193","author":"S Fu","year":"2020","unstructured":"Fu S, Wang G, Xia S, Liu L (2020) Deep multi-granularity graph embedding for user identity linkage across social networks. Knowl-Based Syst 193:105301","journal-title":"Knowl-Based Syst"},{"key":"3216_CR25","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/s11280-020-00833-8","volume":"24","author":"X Li","year":"2021","unstructured":"Li X, Cao Y, Shang Y, Li Y, Liu Y, Tan J (2021) RLINK: deep reinforcement learning for user identity linkage. World Wide Web 24:85\u2013103","journal-title":"World Wide Web"},{"key":"3216_CR26","doi-asserted-by":"crossref","unstructured":"Zhang J et al (2018) MEgo2Vec: Embedding matched ego networks for user alignment across social networks. In: Proc. of the 27th ACM CIKM, New York, NY, USA, pp. 327\u2013336","DOI":"10.1145\/3269206.3271705"},{"key":"3216_CR27","doi-asserted-by":"crossref","unstructured":"Zhou F, Wen Z, Zhong T, Trajcevski G, Liu L (2020) Unsupervised user identity linkage via graph neural networks. In: Proc. 2020 IEEE global communications conference. IEEE","DOI":"10.1109\/GLOBECOM42002.2020.9322311"},{"key":"3216_CR28","unstructured":"Bahdanau D, Cho K, Bengio Y (May 2016) Neural machine translation by jointly learning to align and translate. ArXiv14090473 Cs stat"},{"key":"3216_CR29","doi-asserted-by":"crossref","unstructured":"Hu H, Zhang Z, Xie Z, Lin S (Apr. 2019) Local relation networks for image recognition, ArXiv190411491 Cs","DOI":"10.1109\/ICCV.2019.00356"},{"key":"3216_CR30","doi-asserted-by":"crossref","unstructured":"Yu S, Wang Y, Yang M, Li B, Qu Q, Shen J (2019) NAIRS: A neural attentive interpretable recommendation system. In: Proc. of the 12th ACM WSDM, New York, NY, USA, pp. 790\u2013793","DOI":"10.1145\/3289600.3290609"},{"key":"3216_CR31","unstructured":"J. Lu, J. Yang, D. Batra, and D. Parikh, (2016) Hierarchical question-image co-attention for visual question answering, in advances in neural information processing systems 29, Eds. Curran Associates, Inc., pp. 289\u2013297"},{"key":"3216_CR32","unstructured":"Le QV, Mikolov T (May 2014) Distributed representations of sentences and documents. In: 2014 International Conference on Machine Learning, pp. 1188\u20131196"},{"key":"3216_CR33","unstructured":"Veli\u010dkovi\u0107 P, Cucurull G, Casanova A, Romero A, Li\u00f2 P, Bengio Y (Feb. 2018) Graph attention networks, ArXiv171010903 Cs stat"},{"key":"3216_CR34","doi-asserted-by":"crossref","unstructured":"Wang D, Cui P, Zhu W (2016) Structural deep network embedding, In: Proc. of the 22nd ACM SIGKDD, New York, NY, USA, pp. 1225\u20131234","DOI":"10.1145\/2939672.2939753"},{"key":"3216_CR35","doi-asserted-by":"crossref","unstructured":"Heimann M, Shen H, Safavi T, Koutra D (2018) REGAL: Representation learning-based graph alignment. In: Proc. 27th ACM \u2013CIKM, pp. 117\u2013126","DOI":"10.1145\/3269206.3271788"},{"key":"3216_CR36","unstructured":"Man T, Shen H, Liu S, Jin X, Cheng X (2016) Predict anchor links across social networks via an embedding approach. In: Proc. of the 25th IJCAI, New York, USA, pp. 1823\u20131829"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03216-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-03216-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03216-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T19:28:47Z","timestamp":1668022127000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-03216-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,22]]},"references-count":36,"journal-issue":{"issue":"14","published-print":{"date-parts":[[2022,11]]}},"alternative-id":["3216"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-03216-w","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,22]]},"assertion":[{"value":"30 December 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 March 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}