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Real-Time Clustering of Large Geo-Referenced Data for Visualizing on MapREZAEI, M. , FRANTI, P. |
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Author keywords
data visualization, clustering methods, web services, client-server systems, Internet
References keywords
visualization(21), data(17), clustering(13), information(12), graphics(8), tvcg(6), large(6), visual(5), mining(5), algorithm(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2018-11-30
Volume 18, Issue 4, Year 2018, On page(s): 63 - 74
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.04008
Web of Science Accession Number: 000451843400008
SCOPUS ID: 85058811278
Abstract
Displaying geo-referenced data in web mapping systems has become popular. However, most existing systems suffer from three annoying problems: (1) clutter when trying to visualize large amount of data; (2) slowness of transferring data over internet; (3) lack of support for dynamic queries. To solve these problems, we propose a real-time system using server-side clustering, transferring only the clustered data, and client-side visualization using existing map tools. As far as we know, there is no other scientific paper describing such real-time system that allows dynamic database queries without limiting to predefined queries. Experiments show that it can handle up to 1 million objects whereas all existing systems are either limited to pre-defined queries, or they support only a very small number of free parameters in the query whereas the proposed system has no such limitations. |
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[1] Visualizing Imitation of Typical Intense X-ray Radiation Processes, LIU, H., YANG, S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 20, 2020.
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[2] La géovisualisation de données massives sur le Web : entre avancées technologiques et évolutions cartographiques, Mericskay, Boris, Mappemonde, ISSN 0764-3470, Volume , 2021.
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[3] Activity event recommendation and attendance prediction, Mariescu-Istodor, Radu, Sayem, Abu S. M., Fränti, Pasi, Journal of Location Based Services, ISSN 1748-9725, Issue 4, Volume 13, 2019.
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[4] Solutions and approaches analysis for geospatial data clustering to optimize performance and user experience of web maps, Arzubov, M. V., Batyuk, A. Ye., Ukrainian Journal of Information Technology, ISSN 2707-1898, Issue 2, Volume 5, 2023.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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