Predictive analysis visualization component in simulated data streams
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| Publicat a: | Information Retrieval vol. 27, no. 1 (Dec 2024), p. 12 |
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| Publicat: |
Springer Nature B.V.
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| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text - PDF |
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MARC
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| 001 | 3068280852 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1386-4564 | ||
| 022 | |a 1573-7659 | ||
| 024 | 7 | |a 10.1007/s10791-024-09447-4 |2 doi | |
| 035 | |a 3068280852 | ||
| 045 | 2 | |b d20241201 |b d20241231 | |
| 084 | |a 53339 |2 nlm | ||
| 245 | 1 | |a Predictive analysis visualization component in simulated data streams | |
| 260 | |b Springer Nature B.V. |c Dec 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a One of the most significant problems related to Big Data is their analysis with the use of various methods from the area of descriptive statistics or machine and deep learning. This process is interesting in both—static datasets containing various data sources which do not change over time, and dynamic datasets collected with the use of ambient data sources, which measure a number of attribute values over long periods. Since access to actual dynamic data systems is demanding, the focus of this work is put on the design and implementation of a framework usable in a simulation of data streams, their processing and subsequent dynamic predictive and visual analysis. The proposed system is experimentally verified in the context of a case study conducted on an environmental variable dataset, which was measured with the use of a real-life sensor network. | |
| 653 | |a Big Data | ||
| 653 | |a Machine learning | ||
| 653 | |a Simulation | ||
| 653 | |a Software | ||
| 653 | |a Datasets | ||
| 653 | |a User behavior | ||
| 653 | |a Computer science | ||
| 653 | |a Data sources | ||
| 653 | |a Sensors | ||
| 653 | |a Data systems | ||
| 653 | |a Data processing | ||
| 653 | |a Design | ||
| 653 | |a Data analysis | ||
| 653 | |a Data collection | ||
| 653 | |a Data transmission | ||
| 653 | |a Visualization | ||
| 653 | |a Case studies | ||
| 773 | 0 | |t Information Retrieval |g vol. 27, no. 1 (Dec 2024), p. 12 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3068280852/abstract/embedded/Y2VX53961LHR7RE6?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3068280852/fulltextPDF/embedded/Y2VX53961LHR7RE6?source=fedsrch |