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Journal of Information & Systems Management (JISM)

Big Data Analysis of Spatio-temporal Data

Aleksandra Stojnev, Dragan Stojanovic
Faculty of Electronic Engineering at University of NiÃ…Â¡ Aleksandra Medvedeva 14, 18000 NiÃ…Â¡, Serbia

Abstract: Currently a large number of people involve in the process of analysing and mining big amount of spatio-temporal data. This process has been applied in many disciplines and it involves interdisciplinary approach. In this process, it is essential to modify and change the datasets used for mining work. To understand the mined data, it is also required to use different models and systems for the analysis. In this work, we have proposed the model of mining process and explain the telecom data used.

Keywords: Big Spatio-temporal Data, Spatio-temporal Data Mining, Telecom Data

DOI:https://doi.org/10.6025/jism/2021/11/1/7-13

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References:

[1] Stojnev, A., Stojanovic, D. (2016). Sparkle – A Framework for Spatial Analysis on Apache Spark Platform, IcETRAN 2016 Conference, Zlatibor.
[2] Stojnev, A., Stojanovic, D. (2016). Real-time Processing of Big Geospatial Data based on Spark Streaming, SAUM 2016 Conference, Niš.
[3] Andrienko, N., Andrienko, G. (2013). A Visual Analytics Framework for Spatio-Temporal Analysis and Modelling, Data Mining and Knowledge Discovery, p. 1-29.
[4] Cibulski, L., Gracanin, D., Diehl, A., Splechtna, R., Elshehaly, M., Delrieux, C., Matkovic, K. (2016). ITEA—Interactive 32 (6-8) 847-857.
[5] Mamoulis, N., Cao, H., Kollios, G., Hadjieleftheriou, M., Tao, Y., Cheung, D. W. (2004). Mining, Indexing, and Querying Historical Spatiotemporal Data, ACM SIGKDD 2004 Conference, Seattle, WA, USA.
[6] Dos Santos, R. F., Boedihardjo, A., Shah, S., Chen, F., Lu, C., Ramakrishnan, N. (2016). The Big Data of Violent Events: Algorithms for Association Analysis Using Spatio-Temporal Storytelling, GeoInformatica, 20 (4) 879-921.
[7] Huang, Y., Chen, C., Dong, P. (2008). Modeling Herds and Their Evolvements from Trajectory Data, Geographic Information Science, vol. 5266, p. 90-105.
[8] Xu, J., Deng, D., Demiryurek, U., Shahabi, C., van der Schaar, M. (2015). Mining the Situation: Spatiotemporal Traffic Prediction With Big Data, Journal of Selected Topics in Signal Processing, 9 (4) 702–715.
[9] Ferreira, N., Poco, J., Vo, H. T., Freire, J., Silva, C. T. (2013). Visual Exploration of Big Spatio-Temporal Urban Data: A Study of New York City Taxi Trips, IEEE Trans. Vis. Comput. Graph., 19 (12) 2149-2158.
[10] Cheng, T., Haworth, J., Anbaroglu, B., Tanaksaranond, G., Wang, J. (2014). Spatiotemporal Data Mining, Handbook of Regional Science, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, p. 1173-1193.
[11] Vatsavai, R. R., Bhaduri, B. (2013). Geospatial Analytics for Big Spatiotemporal Data: Algorithms, Applications, and Challenges, In: NSF Workshop on Big Data and Extreme-Scale Computing, Charleston, SC.
[12] Shekhar, S., Jiang, Z., Ali, R. Y., Eftelioglu, E., Tang, X., Gunturi, V., Zhou, X. (2015). Spatiotemporal Data Mining: A Computational Perspective, ISPRS International Journal of Geo-Information, 4 (4) 2306-2338.
[13] Rao, K. V., Govardhan, A., Rao, K. V. C. (2012). Spatiotemporal Data Mining: Issues, Tasks and Applications, International Journal of Computer Science & Engineering Survey, 3 (1) 39-52.

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