Scaling Big Data Applications in Smart City with Coresets

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F19%3A00109826" target="_blank" >RIV/00216224:14610/19:00109826 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.5220/0007958803570363" target="_blank" >http://dx.doi.org/10.5220/0007958803570363</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0007958803570363" target="_blank" >10.5220/0007958803570363</a>

Result language
angličtina
Original language name
Scaling Big Data Applications in Smart City with Coresets
Original language description
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.
Czech name
—
Czech description
—

Project
<a href="/en/project/EF16_013%2F0001802" target="_blank" >EF16_013/0001802: CERIT Scientific Cloud</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1
ISBN
9789897583773
ISSN
—
e-ISSN
—
Number of pages
7
Pages from-to
357-363
Publisher name
SciTePress
Place of publication
Prague, Czech Republic
Event location
Prague, Czech Republic
Event date
Jan 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000570730200042

Similar results(10)