Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery

Tong Li; Shiduo Xin; Yanxin Xi; Sasu Tarkoma; Pan Hui; Yong Li

doi:10.1145/3511808.3557153

Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery

Tong Li, Shiduo Xin, Yanxin Xi, Sasu Tarkoma, Pan Hui, Yong Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Original language	English
Title of host publication	CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management
Number of pages	10
Publisher	Association for Computing Machinery
Publication date	17 Oct 2022
Pages	3282-3291
ISBN (Electronic)	978-1-4503-9236-5
DOIs	https://doi.org/10.1145/3511808.3557153
Publication status	Published - 17 Oct 2022
MoE publication type	A4 Article in conference proceedings
Event	31st ACM International Conference on Information and Knowledge Management, CIKM 2022 - Atlanta, United States Duration: 17 Oct 2022 → 21 Oct 2022

Publication series

Name	International Conference on Information and Knowledge Management, Proceedings

Bibliographical note

Funding Information:
This research has been supported in part by the National Key Research and Development Program of China under Grant 2020YFB2104005; in part by the National Natural Science Foundation of China under Grant U20B2060, and Grant U21B2036; in part by the International Postdoctoral Exchange Fellowship Program (Talent-Introduction Program) under YJ20210274; and in part by the Academy of Finland under Project 319669, Project 319670, Project 325570, Project 326305, Project 325774, and Project 335934.

Publisher Copyright:
© 2022 Owner/Author.

Fields of Science

socioeconomic indicators
sustainable development
urban imagery
113 Computer and information sciences

Access to Document

10.1145/3511808.3557153Licence: CC BY

3511808.3557153Final published version, 6.91 MBLicence: CC BY

Cite this

Li, T., Xin, S., Xi, Y., Tarkoma, S., Hui, P., & Li, Y. (2022). Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery. In CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management (pp. 3282-3291). (International Conference on Information and Knowledge Management, Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3511808.3557153

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title = "Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery",

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author = "Tong Li and Shiduo Xin and Yanxin Xi and Sasu Tarkoma and Pan Hui and Yong Li",

note = "Funding Information: This research has been supported in part by the National Key Research and Development Program of China under Grant 2020YFB2104005; in part by the National Natural Science Foundation of China under Grant U20B2060, and Grant U21B2036; in part by the International Postdoctoral Exchange Fellowship Program (Talent-Introduction Program) under YJ20210274; and in part by the Academy of Finland under Project 319669, Project 319670, Project 325570, Project 326305, Project 325774, and Project 335934. Publisher Copyright: {\textcopyright} 2022 Owner/Author.; 31st ACM International Conference on Information and Knowledge Management, CIKM 2022 ; Conference date: 17-10-2022 Through 21-10-2022",

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month = oct,

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doi = "10.1145/3511808.3557153",

language = "English",

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Li, T, Xin, S, Xi, Y , Tarkoma, S , Hui, P & Li, Y 2022, Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery. in CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. International Conference on Information and Knowledge Management, Proceedings, Association for Computing Machinery, pp. 3282-3291, 31st ACM International Conference on Information and Knowledge Management, CIKM 2022, Atlanta, United States, 17/10/2022. https://doi.org/10.1145/3511808.3557153

Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery. / Li, Tong; Xin, Shiduo; Xi, Yanxin et al.
CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, 2022. p. 3282-3291 (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AU - Li, Tong

AU - Xin, Shiduo

AU - Xi, Yanxin

AU - Tarkoma, Sasu

AU - Hui, Pan

AU - Li, Yong

N1 - Funding Information: This research has been supported in part by the National Key Research and Development Program of China under Grant 2020YFB2104005; in part by the National Natural Science Foundation of China under Grant U20B2060, and Grant U21B2036; in part by the International Postdoctoral Exchange Fellowship Program (Talent-Introduction Program) under YJ20210274; and in part by the Academy of Finland under Project 319669, Project 319670, Project 325570, Project 326305, Project 325774, and Project 335934. Publisher Copyright: © 2022 Owner/Author.

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KW - socioeconomic indicators

KW - sustainable development

KW - urban imagery

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T3 - International Conference on Information and Knowledge Management, Proceedings

SP - 3282

EP - 3291

BT - CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management

PB - Association for Computing Machinery

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Li T, Xin S, Xi Y , Tarkoma S , Hui P, Li Y. Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery. In CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery. 2022. p. 3282-3291. (International Conference on Information and Knowledge Management, Proceedings). doi: 10.1145/3511808.3557153

Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery

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Bibliographical note

Fields of Science

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