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@inproceedings{1536678, author = {Trang, Le Hong and Bangui, Hind and Ge, Mouzhi and Bühnová, Barbora}, address = {Prague, Czech Republic}, booktitle = {Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1}, doi = {http://dx.doi.org/10.5220/0007958803570363}, keywords = {Big Data; Classification; Coreset; Clustering; Sampling; Smart City}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Prague, Czech Republic}, isbn = {978-989-758-377-3}, pages = {357-363}, publisher = {SciTePress}, title = {Scaling Big Data Applications in Smart City with Coresets}, url = {http://dx.doi.org/10.5220/0007958803570363}, year = {2019} }
TY - JOUR ID - 1536678 AU - Trang, Le Hong - Bangui, Hind - Ge, Mouzhi - Bühnová, Barbora PY - 2019 TI - Scaling Big Data Applications in Smart City with Coresets PB - SciTePress CY - Prague, Czech Republic SN - 9789897583773 KW - Big Data KW - Classification KW - Coreset KW - Clustering KW - Sampling KW - Smart City UR - http://dx.doi.org/10.5220/0007958803570363 L2 - http://dx.doi.org/10.5220/0007958803570363 N2 - With the development of Big Data applications in Smart Cities, various Big Data applications are proposed within the domain. These are however hard to test and prototype, since such prototyping requires big computing resources. In order to save the effort in building Big Data prototypes for Smart Cities, this paper proposes an enhanced sampling technique to obtain a coreset from Big Data while keeping the features of the Big Data, such as clustering structure and distribution density. In the proposed sampling method, for a given dataset and an e > 0, the method computes an e-coreset of the dataset. The e-coreset is then modified to obtain a sample set while ensuring the separation and balance in the set. Furthermore, by considering the representativeness of each sample point, our method can helps to remove noises and outliers. We believe that the coreset-based technique can be used to efficiently prototype and evaluate Big Data applications in the Smart City. ER -
TRANG, Le Hong, Hind BANGUI, Mouzhi GE a Barbora BÜHNOVÁ. Scaling Big Data Applications in Smart City with Coresets. Online. In \textit{Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1}. Prague, Czech Republic: SciTePress, 2019, s.~357-363. ISBN~978-989-758-377-3. Dostupné z: https://dx.doi.org/10.5220/0007958803570363.
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