摘要
Urban growth benefits significantly from local business development. However, factors like traffic and labor shortages sometimes cause companies to operate away from their registered addresses, resulting in governance challenges. This paper introduces "LocRecognizer,"a data mining method that leverages e-commerce data to pinpoint companies' real-world operational locations. Based on the principle that areas with a high concentration of company-related users likely indicate actual workplaces, LocRecognizer combines hierarchical clustering with a deep learning model for accurate detection. When tested on datasets from Beijing and Nantong, it outperformed six baselines. A practical implementation of this system has been operational in Nantong since September 2021, attesting to its effectiveness.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2023 |
| 编辑 | Maria Luisa Damiani, Matthias Renz, Ahmed Eldawy, Peer Kroger, Mario A. Nascimento |
| 出版商 | Association for Computing Machinery |
| ISBN(电子版) | 9798400701689 |
| DOI | |
| 出版状态 | 已出版 - 13 11月 2023 |
| 活动 | 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2023 - Hamburg, 德国 期限: 13 11月 2023 → 16 11月 2023 |
出版系列
| 姓名 | GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems |
|---|
会议
| 会议 | 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2023 |
|---|---|
| 国家/地区 | 德国 |
| 市 | Hamburg |
| 时期 | 13/11/23 → 16/11/23 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 11 可持续城市和社区
学术指纹
探究 'A Novel Approach for Company Real Workplace Identification via E-commercial Data' 的科研主题。它们共同构成独一无二的学术指纹。引用此
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