摘要
Spatio-temporal data intelligence, which includes sensing, managing, and mining large-scale data across space and time, plays a pivotal role in understanding complex systems in real-world applications, such as urban computing and smart cities. With the rapid evolution of foundation models and their growing potential to transform spatio-temporal analytics, we propose a comprehensive half-day workshop (with at least 5 accepted papers, 3 keynote talks, 1 panel discussion, and over 50 attendees) at CIKM 2025, catering to professionals, researchers, and practitioners who are interested in spatio-temporal data intelligence and foundation models to address real-world challenges. The workshop will not only offer a platform for knowledge exchange but also acknowledge outstanding contributions through a distinguished Best Paper Award. A dedicated panel discussion will explore recent advances, emerging trends, and open challenges in integrating spatio-temporal data and emerging machine learning techniques, fostering dialogue between academia and industry. Note that this will be the eleventh time that our core members have organized a similar workshop. The previous 10 workshops were hosted in top-tier data mining and management venues, e.g., SIGKDD, WWW, and IJCAI, each of which attracted over 60 participants and 25 submissions on average.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | CIKM 2025 - Proceedings of the 34th ACM International Conference on Information and Knowledge Management |
| 出版商 | Association for Computing Machinery, Inc |
| 页 | 6920-6922 |
| 页数 | 3 |
| ISBN(电子版) | 9798400720406 |
| DOI | |
| 出版状态 | 已出版 - 10 11月 2025 |
| 活动 | 34th ACM International Conference on Information and Knowledge Management, CIKM 2025 - Seoul, 韩国 期限: 10 11月 2025 → 14 11月 2025 |
出版系列
| 姓名 | CIKM 2025 - Proceedings of the 34th ACM International Conference on Information and Knowledge Management |
|---|
会议
| 会议 | 34th ACM International Conference on Information and Knowledge Management, CIKM 2025 |
|---|---|
| 国家/地区 | 韩国 |
| 市 | Seoul |
| 时期 | 10/11/25 → 14/11/25 |
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
指纹
探究 'The International Workshop on Spatio-Temporal Data Intelligence and Foundation Models' 的科研主题。它们共同构成独一无二的指纹。引用此
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