Abstract
Given the increasing popularity and availability of location tracking devices, large quantities of Spatio-Temporal data (ST-data) are available from many different sources. For the ST-data, reflecting the mobile characteristic of the world, it is essential to build a functional system to perform quickly interactive analysis. In this paper, we present an analysis and visualization system, NUPT ST-data Miner, which facilitates users to visualize and analyze ST-data. It (1) provides a flexible and extensible framework based on cloud computing platform, (2) is able to quickly retrieve specified ST-data, (3) integrated multiple functions for the ST-data. To demonstrate its efficiency, we validate our model and system on a real data set of Microsoft Research Asia. The results from extensive experiments demonstrate that NUPT ST-data Miner is an effective system for visually analyzing spatio-temporal data.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Zheng Y, Zhang L, Xie X, Ma WY (2009) Mining interesting locations and travel sequences from gps trajectories. In: International Conference on World Wide Web, pp 791–800
Wang F, Lu C-T, Qu Y, Philip SY (2017) Collective geographical embedding for geolocating social network users. In: Pacific-Asia conference on knowledge discovery and data mining, pp 599–611
Zheng Y, Li Q, Chen Y, Xie X, Ma WY (2008) Understanding mobility based on gps data. In: International Conference on Ubiquitous Computing, pp 312–321
Ertl T, Chae J, Maciejewski R, Bosch H, Thom D, Yun J, Ebert DS (2012) Spatiotemporal social media analytics for abnormal event detection and examination using seasonal-trend decomposition. In: IEEE conference on visual analytics science and technology, pp 143–152
Chandola V, Vatsavai RR, Bhaduri B (2011) Iglobe: an interactive visualization and analysis framework for geospatial data. In: International conference on computing for geospatial research applications, p 21
Nguyen H, Liu W, Rivera P, Chen F (2016) Trafficwatch: real-time traffic incident detection and monitoring using social media. In: Pacific-asia conference on knowledge discovery and data mining, pp 540–551
Wang X, Leckie C, Xie H, Vaithianathan T (2015) Discovering the impact of urban traffic interventions using contrast mining on vehicle trajectory data. In: Pacific-Asia conference on knowledge discovery and data mining, pp 486–497
Eagle N, Pentland A (2006) Reality mining: sensing complex social systems. Personal Ubiquitous Computing 10(4):255–268
Jendryke M, Balz T, Mcclure SC, Liao M (2017) Putting people in the picture: combining big location-based social media data and remote sensing imagery for enhanced contextual urban information in shanghai. Comput Environ Urban Syst 62:99–112
Yeon H, Yun J (2015) Predictive visual analytics using topic composition. In: International symposium on visual information communication and interaction, pp 1–8
Najm-Araghi M, Mansmann F, Krstaji M, Keim DA (2013) Story tracker: incremental visual text analytics of news story development. Inf Visual 12(3–4):308–323
Jiang Z, Yu S, Zhou M, Chen Y, Yi L (2017) Model study for intelligent transportation system with big data. Proced Comput Sci 107:418–426
Bryan C, Mniszewski S, Ma KL (2014) Integrating predictive visualization with the epidemic disease simulation system (episims). In: Proceedings of the IEEE VIS 2014 workshop visualization for predictive analytics
Schulz H-J, Hadlak S Schumann H (2013) A visualization approach forcross-level exploration of spatiotemporal data. In: International conference on knowledge management and knowledge technologies, p 2
Bo ̈gl M, Aigner W, Filzmoser P, Gschwandtner T, Lammarsch T, Miksch S, Rind A (2014) Visual analytics methods to guide diagnostics for time series model predictions. In: Proceedings of the IEEE VIS 2014 workshop visualization for predictive analytics, VPA,
He J, Chen C (2016) Spatiotemporal analytics of topic trajectory. In: International symposium on visual information communication and interaction, 112–116
Bosch H, Thom D, Heimerl F, Puttmann E, Koch S, Kruger R, Worner M, Ertl T (2013) Scatterblogs2: real-time monitoring of microblog messages through user-guided filtering. IEEE Trans Vis Comput Graph 19(12):2022–2031
Zou Z, Yu Z, Cao K (2016) An innovative gps trajectory data based model for geographic recommendation service. Trans Gis
Gao H, Liu H (2015) Mining human mobility in location-based social networks. Synth Lect Data Min Knowl Discov 7(2):1–115
Acknowledgements
This work is supported by the National Natural Science Foundation of P. R. China (No. 41571389, 61472193, 41501431), supported by Key Laboratory of Spatial Data Mining Information Sharing of Ministry of Education, Fuzhou University (No. 2016LSDMIS07), and the NJUPT Natural Science Foundation (No. NY215116). In addition, we are grateful to the anonymous reviewers for their insightful and constructive suggestions.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zou, Z., Xiong, J., He, X., Dai, H. (2019). NUPT ST-Data Miner: An Spatio-Temporal Data Analysis and Visualization System. In: Kim, K., Baek, N. (eds) Information Science and Applications 2018. ICISA 2018. Lecture Notes in Electrical Engineering, vol 514. Springer, Singapore. https://doi.org/10.1007/978-981-13-1056-0_5
Download citation
DOI: https://doi.org/10.1007/978-981-13-1056-0_5
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1055-3
Online ISBN: 978-981-13-1056-0
eBook Packages: EngineeringEngineering (R0)