{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T18:03:00Z","timestamp":1764784980397,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":26,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T00:00:00Z","timestamp":1665964800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["DE190100663"],"award-info":[{"award-number":["DE190100663"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2021R1A2C3004345"],"award-info":[{"award-number":["2021R1A2C3004345"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,17]]},"DOI":"10.1145\/3511808.3557605","type":"proceedings-article","created":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T01:29:57Z","timestamp":1665883797000},"page":"4374-4378","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["GradAlign+: Empowering Gradual Network Alignment Using Attribute Augmentation"],"prefix":"10.1145","author":[{"given":"Jin-Duk","family":"Park","sequence":"first","affiliation":[{"name":"Yonsei University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Tran","sequence":"additional","affiliation":[{"name":"Posts and Telecommunications Institute of Technology, Hanoi, Vietnam"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Won-Yong","family":"Shin","sequence":"additional","affiliation":[{"name":"Yonsei University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Cao","sequence":"additional","affiliation":[{"name":"The University of New South Wales, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,10,17]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46128-1_29"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/BFb0017012"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412136"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2849727"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/3367243.3367352"},{"key":"e_1_3_2_1_6_1","first-page":"3","article-title":"Cross-network skip-gram embedding for joint network alignment and link prediction","volume":"34","author":"Du Xingbo","year":"2020","unstructured":"Xingbo Du , Junchi Yan , Rui Zhang , and Hongyuan Zha . 2020 . Cross-network skip-gram embedding for joint network alignment and link prediction . IEEE Trans. Knowl. Data Eng. , Vol. 34 , 3 (Mar. 2020), 1080--1095. Xingbo Du, Junchi Yan, Rui Zhang, and Hongyuan Zha. 2020. Cross-network skip-gram embedding for joint network alignment and link prediction. IEEE Trans. Knowl. Data Eng., Vol. 34, 3 (Mar. 2020), 1080--1095.","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.01.074"},{"key":"e_1_3_2_1_8_1","volume-title":"Proc. 28th Int. Conf. Neural Inf. Process. Syst. (NIPS'17)","author":"Hamilton Will","year":"2017","unstructured":"Will Hamilton , Zhitao Ying , and Jure Leskovec . 2017 . Inductive representation learning on large graphs . In Proc. 28th Int. Conf. Neural Inf. Process. Syst. (NIPS'17) . Long Beach, CA, 1024--1034. Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. In Proc. 28th Int. Conf. Neural Inf. Process. Syst. (NIPS'17). Long Beach, CA, 1024--1034."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271788"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018668"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF02289026"},{"volume-title":"Proc. 3rd Int. Conf. Learn. Representations (ICLR'15)","author":"Diederik","key":"e_1_3_2_1_12_1","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: A method for stochastic optimization . In Proc. 3rd Int. Conf. Learn. Representations (ICLR'15) . San Diego, CA, 1--15. Diederik P. Kingma and Jimmy Ba. 2015. Adam: A method for stochastic optimization. In Proc. 3rd Int. Conf. Learn. Representations (ICLR'15). San Diego, CA, 1--15."},{"volume-title":"Proc. 5th Int. Conf. Learning Rep. (ICLR'17)","author":"Thomas","key":"e_1_3_2_1_13_1","unstructured":"Thomas N. Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks . In Proc. 5th Int. Conf. Learning Rep. (ICLR'17) . Toulon, France, 1--14. Thomas N. Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks. In Proc. 5th Int. Conf. Learning Rep. (ICLR'17). Toulon, France, 1--14."},{"key":"e_1_3_2_1_14_1","volume-title":"Proc. 25th Int. Joint Conf. Artif. Intell. (IJCAI'16)","author":"Liu Li","year":"2016","unstructured":"Li Liu , William K Cheung , Xin Li , and Lejian Liao . 2016 . Aligning users across social networks using network embedding . In Proc. 25th Int. Joint Conf. Artif. Intell. (IJCAI'16) . New York City, NY, 1774--1780. Li Liu, William K Cheung, Xin Li, and Lejian Liao. 2016. Aligning users across social networks using network embedding. In Proc. 25th Int. Joint Conf. Artif. Intell. (IJCAI'16). New York City, NY, 1774--1780."},{"key":"e_1_3_2_1_15_1","volume-title":"Proc. 25th Int. Joint Conf. Artif. Intell. (IJCAI'16)","author":"Man Tong","year":"2016","unstructured":"Tong Man , Huawei Shen , Shenghua Liu , Xiaolong Jin , and Xueqi Cheng . 2016 . Predict anchor links across social networks via an embedding approach . In Proc. 25th Int. Joint Conf. Artif. Intell. (IJCAI'16) . New York City, NY , 1823--1829. Tong Man, Huawei Shen, Shenghua Liu, Xiaolong Jin, and Xueqi Cheng. 2016. Predict anchor links across social networks via an embedding approach. In Proc. 25th Int. Joint Conf. Artif. Intell. (IJCAI'16). New York City, NY, 1823--1829."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/GLOCOM.2014.7037257"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i11.21650"},{"key":"e_1_3_2_1_18_1","volume-title":"On the power of gradual network alignment using dual-perception similarities. arXiv preprint arXiv:2201.10945","author":"Park Jin-Duk","year":"2022","unstructured":"Jin-Duk Park , Cong Tran , Won-Yong Shin , and Xin Cao . 2022b. On the power of gradual network alignment using dual-perception similarities. arXiv preprint arXiv:2201.10945 ( 2022 ). Jin-Duk Park, Cong Tran, Won-Yong Shin, and Xin Cao. 2022b. On the power of gradual network alignment using dual-perception similarities. arXiv preprint arXiv:2201.10945 (2022)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00174"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9277"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE48307.2020.00015"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.84.4.327"},{"key":"e_1_3_2_1_23_1","volume-title":"Proc. 7th Int. Conf. Learning Rep. (ICLR'19)","author":"Xu Keyulu","year":"2019","unstructured":"Keyulu Xu , Weihua Hu , Jure Leskovec , and Stefanie Jegelka . 2019 . How powerful are graph neural networks? . In Proc. 7th Int. Conf. Learning Rep. (ICLR'19) . New Orleans, LA, 1--17. Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2019. How powerful are graph neural networks?. In Proc. 7th Int. Conf. Learning Rep. (ICLR'19). New Orleans, LA, 1--17."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939766"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339641"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2018.8486231"}],"event":{"name":"CIKM '22: The 31st ACM International Conference on Information and Knowledge Management","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Atlanta GA USA","acronym":"CIKM '22"},"container-title":["Proceedings of the 31st ACM International Conference on Information & Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3511808.3557605","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3511808.3557605","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:09Z","timestamp":1750182669000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3511808.3557605"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,17]]},"references-count":26,"alternative-id":["10.1145\/3511808.3557605","10.1145\/3511808"],"URL":"https:\/\/doi.org\/10.1145\/3511808.3557605","relation":{},"subject":[],"published":{"date-parts":[[2022,10,17]]},"assertion":[{"value":"2022-10-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}