Visualization in Big Data: a tool for pattern recognition in data stream
The development of new technologies is responsible for the generation and storage of continuous and massive amounts of data. Such type of data is known as data stream. The analysis of data streams may be advantageous in many fields, like bioinformatics, medicine, companies and others, as it may resu...
| Autores: | , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | Brasil |
| Recursos: | Universidade Federal de Viçosa (UFV) |
| Repositorio: | LOCUS Repositório Institucional da UFV |
| Idioma: | inglés |
| OAI Identifier: | oai:locus.ufv.br:123456789/23856 |
| Acesso em linha: | https://doaj.org/article/312c47b382184147bf589646b05e02d5 http://www.locus.ufv.br/handle/123456789/23856 |
| Access Level: | acceso abierto |
| Palavra-chave: | Data mining Data streams Data visualization |
| Resumo: | The development of new technologies is responsible for the generation and storage of continuous and massive amounts of data. Such type of data is known as data stream. The analysis of data streams may be advantageous in many fields, like bioinformatics, medicine, companies and others, as it may result in important information about the data. In this work, we propose a new software tool for Data Visualization that permits the analysis of the evolution of clusters in real time during the data streaming. The proposed visualization tool is add-on for SAMOA, a new variant of MOA (Massive Online Analysis) for massive data streams mining and processing distribution. |
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