A Comparative Study of Topic Modelling Approaches for User-generated Point of Interest Data
This study aims to enhance urban planning and management by harnessing the power of machine learning (ML) and big data. We focus on Urban Functional Zones (UFZs), the fundamental units for human socio-economic activities. Our methodology involves compiling Point of Interest (POI) data from various...
Saved in:
| Main Authors: | Ravi Satyappa Dabbanavar, Arindam Biswas |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Alanya Üniversitesi
2024-06-01
|
| Series: | Proceedings of the International Conference of Contemporary Affairs in Architecture and Urbanism-ICCAUA |
| Subjects: | |
| Online Access: | https://journal.iccaua.com/jiccaua/article/view/531 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research on the Method of Artificial Intelligence for Identifying Urban Land-Use Types Based on Areas of Interest (AOI) and Multi-Source Data
by: Miaoyi Li, et al.
Published: (2024-11-01) -
Unveiling intra-urban complexity and identifying urban cores through the lens of living structure using point-of-interest data
by: Zheng Ren, et al.
Published: (2025-07-01) -
Revealing social dimensions of urban mobility with big data: A timely dialogue
by: Jiangyue Wu, et al.
Published: (2023-11-01) -
Revealing social dimensions of urban mobility with big data: A timely dialogue
by: Jiangyue Wu, et al.
Published: (2023-11-01) -
Improving subpixel impervious surface estimation based on point of interest (POI) data
by: Junzhe Wang, et al.
Published: (2025-05-01)