{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:21:37Z","timestamp":1775143297203,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":37,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T00:00:00Z","timestamp":1691107200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Hong Kong RGC TRS","award":["T41-603\/20-R"],"award-info":[{"award-number":["T41-603\/20-R"]}]},{"name":"National Science Foundation SWIFT","award":["Grant No. 2030249"],"award-info":[{"award-number":["Grant No. 2030249"]}]},{"DOI":"10.13039\/501100018542","name":"Natural Science Foundation of Sichuan Province","doi-asserted-by":"publisher","award":["Grant No. 2022NSFSC0505"],"award-info":[{"award-number":["Grant No. 2022NSFSC0505"]}],"id":[{"id":"10.13039\/501100018542","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grant No. 62176043 and 62072077"],"award-info":[{"award-number":["Grant No. 62176043 and 62072077"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,8,6]]},"DOI":"10.1145\/3580305.3599920","type":"proceedings-article","created":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T18:13:58Z","timestamp":1691172838000},"page":"4862-4871","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["TrustGeo: Uncertainty-Aware Dynamic Graph Learning for Trustworthy IP Geolocation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7364-8324","authenticated-orcid":false,"given":"Wenxin","family":"Tai","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0074-9117","authenticated-orcid":false,"given":"Bin","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8038-8150","authenticated-orcid":false,"given":"Fan","family":"Zhou","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8163-3146","authenticated-orcid":false,"given":"Ting","family":"Zhong","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8839-6278","authenticated-orcid":false,"given":"Goce","family":"Trajcevski","sequence":"additional","affiliation":[{"name":"Iowa State University, Ames, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8699-8355","authenticated-orcid":false,"given":"Yong","family":"Wang","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2587-6028","authenticated-orcid":false,"given":"Kai","family":"Chen","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,8,4]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.05.008"},{"key":"e_1_3_2_2_2_1","first-page":"14927","article-title":"Deep evidential regression","volume":"33","author":"Amini Alexander","year":"2020","unstructured":"Alexander Amini , Wilko Schwarting , Ava Soleimany , and Daniela Rus . 2020 . Deep evidential regression . Advances in Neural Information Processing Systems , Vol. 33 (2020), 14927 -- 14937 . Alexander Amini, Wilko Schwarting, Ava Soleimany, and Daniela Rus. 2020. Deep evidential regression. Advances in Neural Information Processing Systems, Vol. 33 (2020), 14927--14937.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_3_1","volume-title":"Arik and Tomas Pfister","author":"Sercan","year":"2021","unstructured":"Sercan \u00d6. Arik and Tomas Pfister . 2021 . TabNet: Attentive Interpretable Tabular Learning. In AAAI. 6679--6687. Sercan \u00d6. Arik and Tomas Pfister. 2021. TabNet: Attentive Interpretable Tabular Learning. In AAAI. 6679--6687."},{"key":"e_1_3_2_2_4_1","first-page":"2097","article-title":"Towards IP location estimation using the nearest common router","volume":"19","author":"Luo Xiangyang","year":"2018","unstructured":"Jing-ning Chen, Fen-lin Liu, Ya-feng Shi, and Xiangyang Luo . 2018 . Towards IP location estimation using the nearest common router . Journal of Internet Technology , Vol. 19 , 7 (2018), 2097 -- 2110 . Jing-ning Chen, Fen-lin Liu, Ya-feng Shi, and Xiangyang Luo. 2018. Towards IP location estimation using the nearest common router. Journal of Internet Technology, Vol. 19, 7 (2018), 2097--2110.","journal-title":"Journal of Internet Technology"},{"key":"e_1_3_2_2_5_1","unstructured":"Ovidiu Dan Vaibhav Parikh and Brian D Davison. 2021. IP Geolocation Using Traceroute Location Propagation and IP Range Location Interpolation. In WWW. 332--338. Ovidiu Dan Vaibhav Parikh and Brian D Davison. 2021. IP Geolocation Using Traceroute Location Propagation and IP Range Location Interpolation. In WWW. 332--338."},{"key":"e_1_3_2_2_6_1","volume-title":"Aleatory or epistemic? Does it matter? Structural safety","author":"Kiureghian Armen Der","year":"2009","unstructured":"Armen Der Kiureghian and Ove Ditlevsen . 2009. Aleatory or epistemic? Does it matter? Structural safety , Vol. 31 , 2 ( 2009 ), 105--112. Armen Der Kiureghian and Ove Ditlevsen. 2009. Aleatory or epistemic? Does it matter? Structural safety, Vol. 31, 2 (2009), 105--112."},{"key":"e_1_3_2_2_7_1","volume-title":"GNN-Geo: A Graph Neural Network-based Fine-grained IP Geolocation Framework. arXiv preprint arXiv:2112.10767","author":"Ding Shichang","year":"2022","unstructured":"Shichang Ding , Fan Zhang , Xiangyang Luo , and Fenlin Liu . 2022. GNN-Geo: A Graph Neural Network-based Fine-grained IP Geolocation Framework. arXiv preprint arXiv:2112.10767 ( 2022 ). Shichang Ding, Fan Zhang, Xiangyang Luo, and Fenlin Liu. 2022. GNN-Geo: A Graph Neural Network-based Fine-grained IP Geolocation Framework. arXiv preprint arXiv:2112.10767 (2022)."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2011.08.011"},{"key":"e_1_3_2_2_9_1","volume-title":"international conference on machine learning. PMLR, 1050--1059","author":"Gal Yarin","year":"2016","unstructured":"Yarin Gal and Zoubin Ghahramani . 2016 . Dropout as a bayesian approximation: Representing model uncertainty in deep learning . In international conference on machine learning. PMLR, 1050--1059 . Yarin Gal and Zoubin Ghahramani. 2016. Dropout as a bayesian approximation: Representing model uncertainty in deep learning. In international conference on machine learning. PMLR, 1050--1059."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2006.886332"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"crossref","unstructured":"Chuanxiong Guo Yunxin Liu Wenchao Shen Helen J Wang Qing Yu and Yongguang Zhang. 2009. Mining the web and the internet for accurate ip address geolocations. In INFOCOM. 2841--2845. Chuanxiong Guo Yunxin Liu Wenchao Shen Helen J Wang Qing Yu and Yongguang Zhang. 2009. Mining the web and the internet for accurate ip address geolocations. In INFOCOM. 2841--2845.","DOI":"10.1109\/INFCOM.2009.5062243"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1080\/17489725.2018.1508763"},{"key":"e_1_3_2_2_13_1","volume-title":"ACM Comput. Surv.","volume":"54","author":"Jiang Hongbo","year":"2021","unstructured":"Hongbo Jiang , Jie Li , Ping Zhao , Fanzi Zeng , Zhu Xiao , and Arun Iyengar . 2021 . Location Privacy-preserving Mechanisms in Location-based Services: A Comprehensive Survey . ACM Comput. Surv. , Vol. 54 , 1 (2021). Hongbo Jiang, Jie Li, Ping Zhao, Fanzi Zeng, Zhu Xiao, and Arun Iyengar. 2021. Location Privacy-preserving Mechanisms in Location-based Services: A Comprehensive Survey. ACM Comput. Surv., Vol. 54, 1 (2021)."},{"key":"e_1_3_2_2_14_1","volume-title":"INFOCOM Workshops. 170--175","author":"Jiang Hao","year":"2009","unstructured":"Hao Jiang , Yaoqing Liu , and Jeanna N Matthews . 2009 . IP geolocation estimation using neural networks with stable landmarks . In INFOCOM Workshops. 170--175 . Hao Jiang, Yaoqing Liu, and Jeanna N Matthews. 2009. IP geolocation estimation using neural networks with stable landmarks. In INFOCOM Workshops. 170--175."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1389-1286(02)00310-9"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"Ethan Katz-Bassett John P John Arvind Krishnamurthy David Wetherall Thomas Anderson and Yatin Chawathe. 2006. Towards IP geolocation using delay and topology measurements. In SIGCOMM. 71--84. Ethan Katz-Bassett John P John Arvind Krishnamurthy David Wetherall Thomas Anderson and Yatin Chawathe. 2006. Towards IP geolocation using delay and topology measurements. In SIGCOMM. 71--84.","DOI":"10.1145\/1177080.1177090"},{"key":"e_1_3_2_2_17_1","unstructured":"Guolin Ke Qi Meng Thomas Finley Taifeng Wang Wei Chen Weidong Ma Qiwei Ye and Tie-Yan Liu 2017. Lightgbm: A highly efficient gradient boosting decision tree. In NeurIPS. 3146--3154. Guolin Ke Qi Meng Thomas Finley Taifeng Wang Wei Chen Weidong Ma Qiwei Ye and Tie-Yan Liu 2017. Lightgbm: A highly efficient gradient boosting decision tree. In NeurIPS. 3146--3154."},{"key":"e_1_3_2_2_18_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2015","unstructured":"Diederik P. Kingma and Jimmy Ba . 2015 . Adam : A Method for Stochastic Optimization. In ICLR. Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In ICLR."},{"key":"e_1_3_2_2_19_1","volume-title":"Spotter: A model based active geolocation service","author":"Laki S\u00e1ndor","year":"2011","unstructured":"S\u00e1ndor Laki , P\u00e9ter M\u00e1tray , P\u00e9ter H\u00e1ga , Tam\u00e1s SebHok , Istv\u00e1n Csabai , and G\u00e1bor Vattay . 2011 . Spotter: A model based active geolocation service . In IEEE INFOCOM. S\u00e1ndor Laki, P\u00e9ter M\u00e1tray, P\u00e9ter H\u00e1ga, Tam\u00e1s SebHok, Istv\u00e1n Csabai, and G\u00e1bor Vattay. 2011. Spotter: A model based active geolocation service. In IEEE INFOCOM."},{"key":"e_1_3_2_2_20_1","volume-title":"Simple and scalable predictive uncertainty estimation using deep ensembles. Advances in neural information processing systems","author":"Lakshminarayanan Balaji","year":"2017","unstructured":"Balaji Lakshminarayanan , Alexander Pritzel , and Charles Blundell . 2017. Simple and scalable predictive uncertainty estimation using deep ensembles. Advances in neural information processing systems , Vol. 30 ( 2017 ). Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell. 2017. Simple and scalable predictive uncertainty estimation using deep ensembles. Advances in neural information processing systems, Vol. 30 (2017)."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"crossref","unstructured":"Hao Liu Yaoxue Zhang Yuezhi Zhou Di Zhang Xiaoming Fu and KK Ramakrishnan. 2014. Mining checkins from location-sharing services for client-independent ip geolocation. In INFOCOM. 619--627. Hao Liu Yaoxue Zhang Yuezhi Zhou Di Zhang Xiaoming Fu and KK Ramakrishnan. 2014. Mining checkins from location-sharing services for client-independent ip geolocation. In INFOCOM. 619--627.","DOI":"10.1109\/INFOCOM.2014.6847987"},{"key":"e_1_3_2_2_22_1","first-page":"6881","article-title":"Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions","volume":"34","author":"Ma Huan","year":"2021","unstructured":"Huan Ma , Zongbo Han , Changqing Zhang , Huazhu Fu , Joey Tianyi Zhou , and Qinghua Hu . 2021 . Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions . Advances in Neural Information Processing Systems , Vol. 34 (2021), 6881 -- 6893 . Huan Ma, Zongbo Han, Changqing Zhang, Huazhu Fu, Joey Tianyi Zhou, and Qinghua Hu. 2021. Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions. Advances in Neural Information Processing Systems, Vol. 34 (2021), 6881--6893.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_23_1","volume-title":"Predictive uncertainty estimation via prior networks. Advances in neural information processing systems","author":"Malinin Andrey","year":"2018","unstructured":"Andrey Malinin and Mark Gales . 2018. Predictive uncertainty estimation via prior networks. Advances in neural information processing systems , Vol. 31 ( 2018 ). Andrey Malinin and Mark Gales. 2018. Predictive uncertainty estimation via prior networks. Advances in neural information processing systems, Vol. 31 (2018)."},{"key":"e_1_3_2_2_24_1","volume-title":"Packet audio playout delay adjustment: performance bounds and algorithms. Multimedia systems","author":"Moon Sue B","year":"1998","unstructured":"Sue B Moon , Jim Kurose , and Don Towsley . 1998. Packet audio playout delay adjustment: performance bounds and algorithms. Multimedia systems , Vol. 6 , 1 ( 1998 ), 17--28. Sue B Moon, Jim Kurose, and Don Towsley. 1998. Packet audio playout delay adjustment: performance bounds and algorithms. Multimedia systems, Vol. 6, 1 (1998), 17--28."},{"key":"e_1_3_2_2_25_1","unstructured":"David Moore Ram Periakaruppan Jim Donohoe and Kimberly Claffy. 2000. Where in the world is netgeo.caida.org?. In INET. David Moore Ram Periakaruppan Jim Donohoe and Kimberly Claffy. 2000. Where in the world is netgeo.caida.org?. In INET."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Venkata N Padmanabhan and Lakshminarayanan Subramanian. 2001. An investigation of geographic mapping techniques for Internet hosts. In SIGOMM. 173--185. Venkata N Padmanabhan and Lakshminarayanan Subramanian. 2001. An investigation of geographic mapping techniques for Internet hosts. In SIGOMM. 173--185.","DOI":"10.1145\/964723.383073"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1214\/17-BA1083"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICWS55610.2022.00055"},{"key":"e_1_3_2_2_29_1","volume-title":"Tracking Human Mobility Using WiFi Signals. PLoS ONE","volume":"10","author":"Sapiezynski P.","year":"2015","unstructured":"P. Sapiezynski , A. Stopczynski , R. Gatej , and S. Lehmann . 2015 . Tracking Human Mobility Using WiFi Signals. PLoS ONE , Vol. 10 , 7 ( 2015 ). P. Sapiezynski, A. Stopczynski, R. Gatej, and S. Lehmann. 2015. Tracking Human Mobility Using WiFi Signals. PLoS ONE, Vol. 10, 7 (2015)."},{"key":"e_1_3_2_2_30_1","volume-title":"Bayesian optimization with robust Bayesian neural networks. Advances in neural information processing systems","author":"Springenberg Jost Tobias","year":"2016","unstructured":"Jost Tobias Springenberg , Aaron Klein , Stefan Falkner , and Frank Hutter . 2016. Bayesian optimization with robust Bayesian neural networks. Advances in neural information processing systems , Vol. 29 ( 2016 ). Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, and Frank Hutter. 2016. Bayesian optimization with robust Bayesian neural networks. Advances in neural information processing systems, Vol. 29 (2016)."},{"key":"e_1_3_2_2_31_1","unstructured":"Yong Wang Daniel Burgener Marcel Flores Aleksandar Kuzmanovic and Cheng Huang. 2011. Towards street-Level client-Independent IP geolocation. In NSDI. Yong Wang Daniel Burgener Marcel Flores Aleksandar Kuzmanovic and Cheng Huang. 2011. Towards street-Level client-Independent IP geolocation. In NSDI."},{"key":"e_1_3_2_2_32_1","volume-title":"XLBoost-Geo: An IP Geolocation System Based on Extreme Landmark Boosting. arXiv preprint arXiv:2010.13396","author":"Wang Yucheng","year":"2020","unstructured":"Yucheng Wang , Hongsong Zhu , Jinfa Wang , Jie Liu , Yong Wang , and Limin Sun . 2020b. XLBoost-Geo: An IP Geolocation System Based on Extreme Landmark Boosting. arXiv preprint arXiv:2010.13396 ( 2020 ). Yucheng Wang, Hongsong Zhu, Jinfa Wang, Jie Liu, Yong Wang, and Limin Sun. 2020b. XLBoost-Geo: An IP Geolocation System Based on Extreme Landmark Boosting. arXiv preprint arXiv:2010.13396 (2020)."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"crossref","unstructured":"Zhihao Wang Qiang Li Jinke Song Haining Wang and Limin Sun. 2020a. Towards IP-based geolocation via fine-grained and stable webcam landmarks. In WWW. 1422--1432. Zhihao Wang Qiang Li Jinke Song Haining Wang and Limin Sun. 2020a. Towards IP-based geolocation via fine-grained and stable webcam landmarks. In WWW. 1422--1432.","DOI":"10.1145\/3366423.3380216"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"crossref","unstructured":"Zhiyuan Wang Fan Zhou Wenxuan Zeng Goce Trajcevski Xiao Chunjing Wang Yong and Chen Kai. 2022. Connecting the Hosts: Street-Level IP Geolocation with Graph Neural Networks. In SIGKDD. Zhiyuan Wang Fan Zhou Wenxuan Zeng Goce Trajcevski Xiao Chunjing Wang Yong and Chen Kai. 2022. Connecting the Hosts: Street-Level IP Geolocation with Graph Neural Networks. In SIGKDD.","DOI":"10.1145\/3534678.3539049"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13640-020-00504-8"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.5555\/1648530.1648734"}],"event":{"name":"KDD '23: The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Long Beach CA USA","acronym":"KDD '23","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3580305.3599920","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3580305.3599920","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:41Z","timestamp":1750178261000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3580305.3599920"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,4]]},"references-count":37,"alternative-id":["10.1145\/3580305.3599920","10.1145\/3580305"],"URL":"https:\/\/doi.org\/10.1145\/3580305.3599920","relation":{},"subject":[],"published":{"date-parts":[[2023,8,4]]},"assertion":[{"value":"2023-08-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}