{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T02:06:52Z","timestamp":1769566012995,"version":"3.49.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686448","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T00:00:00Z","timestamp":1769472000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,27]]},"abstract":"<jats:p>China\u2019s rapid urbanization has created a significant misalignment with the slower, policy-oriented allocation of educational resources, yet a critical barrier to studying this spatial inequality is the lack of high-quality, fine-grained data on different schools. This study proposes a novel multi-agent AI (Artificial Intelligence) framework to automate the construction of a standardized geospatial dataset for schools, demonstrated through a case study of Chaozhou where data from diverse sources were integrated, validated, and annotated to create a verified dataset of 638 K-12 institutions. The resulting dataset enabled the estimation of school land area, analysis of morphological characteristics, and comparison of school distribution against population density, thereby providing a robust methodology and evidence base to inform data-driven policy on educational resource allocation and advance educational equity.<\/jats:p>","DOI":"10.3233\/faia251690","type":"book-chapter","created":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T13:19:59Z","timestamp":1769519999000},"source":"Crossref","is-referenced-by-count":0,"title":["A Multi-Agent AI Framework for Mapping School Locations: A Case Study in Chaozhou, China"],"prefix":"10.3233","author":[{"given":"Wanyi","family":"Li","sequence":"first","affiliation":[{"name":"School of Computer Information Engineering, Hanshan Normal University, Chaozhou, China"}]},{"given":"Zhongxing","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer Information Engineering, Hanshan Normal University, Chaozhou, China"}]},{"given":"Wei","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Information Engineering, Hanshan Normal University, Chaozhou, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining XI"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251690","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T13:20:00Z","timestamp":1769520000000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251690"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,27]]},"ISBN":["9781643686448"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251690","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,27]]}}}