TY - GEN
T1 - SALON
T2 - 29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
AU - Hu, Yue
AU - Ruan, Sijie
AU - Ni, Yuting
AU - He, Huajun
AU - Bao, Jie
AU - Li, Ruiyuan
AU - Zheng, Yu
N1 - Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/11/2
Y1 - 2021/11/2
N2 - The prevalence of positioning technologies has fostered massive trajectory data. Stay points from trajectories indicate the visiting of moving objects to locations, which provide an opportunity to understand the locations comprehensively. Many existing works rely on stay points to analyze locations. However, they are ad-hoc solutions to tackle specific problems, and it is time-consuming and tedious to develop each application. In this paper, we propose a universal StAy point-based LOcation aNalysis platform, i.e., SALON, with the characteristics of universality, efficiency and flexibility. It can retrieve stay points using flexible conditions, associate stay points with locations, extract comprehensive location profiles and visualize the analysis results to users. Based on the combination of these functions, we demonstrate three different location analysis scenarios, i.e., illegal location discovery, popular location ranking, location temporal analysis to show its characteristics.
AB - The prevalence of positioning technologies has fostered massive trajectory data. Stay points from trajectories indicate the visiting of moving objects to locations, which provide an opportunity to understand the locations comprehensively. Many existing works rely on stay points to analyze locations. However, they are ad-hoc solutions to tackle specific problems, and it is time-consuming and tedious to develop each application. In this paper, we propose a universal StAy point-based LOcation aNalysis platform, i.e., SALON, with the characteristics of universality, efficiency and flexibility. It can retrieve stay points using flexible conditions, associate stay points with locations, extract comprehensive location profiles and visualize the analysis results to users. Based on the combination of these functions, we demonstrate three different location analysis scenarios, i.e., illegal location discovery, popular location ranking, location temporal analysis to show its characteristics.
KW - Interactive Exploration
KW - Location Analysis
KW - Spatio-temporal Data Mining
UR - https://www.scopus.com/pages/publications/85119206198
U2 - 10.1145/3474717.3483991
DO - 10.1145/3474717.3483991
M3 - Conference contribution
AN - SCOPUS:85119206198
T3 - GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
SP - 407
EP - 410
BT - 29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
A2 - Meng, Xiaofeng
A2 - Wang, Fusheng
A2 - Lu, Chang-Tien
A2 - Huang, Yan
A2 - Shekhar, Shashi
A2 - Xie, Xing
PB - Association for Computing Machinery
Y2 - 2 November 2021 through 5 November 2021
ER -