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Hazy: Making It Easier to Build and Maintain Big-Data Analytics.

The article discusses the construction and maintenance of Big-Data analytics systems as of March 2013, focusing on machine-learning methods and statistical methods while describing the Hazy project for algorithm management. Topics include trained systems, interfaces between algorithms and systems, t...

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Publicado en:Communications of the ACM Vol. 56; no. 3; pp. 40 - 50
Autores principales: KUMAR, ARUN, NIU, FENG, RÉ, CHRISTOPHER
Formato: Artículo
Publicado: Association for Computing Machinery Mar2013
Materias:
Big data
Machine learning
Algorithms
Systems design
Computer programming
System analysis
Acceso en línea:Ver este registro en EBSCOhost
Sumario:The article discusses the construction and maintenance of Big-Data analytics systems as of March 2013, focusing on machine-learning methods and statistical methods while describing the Hazy project for algorithm management. Topics include trained systems, interfaces between algorithms and systems, the GeoDeepDive application for the statistical analysis of geological research papers, and the Bismarck project for infrastructure abstractions. Data sets, probabilistic logic programming, debugging, convex programming, and scalability are mentioned.