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Mostrando ítems 1-10 de 2024
Obtenção de padrões sequenciais em data streams atendendo requisitos do Big Data
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Ciência da Computação - PPGCCCâmpus São Carlos, 2016-06-06)
The growing amount of data produced daily, by both businesses and individuals in the web, increased the demand for analysis and extraction of knowledge of this data. While the last two decades the solution was to store and ...
Visualization in Big Data: a tool for pattern recognition in data stream
(Revista de Sistemas de Informação da FSMA, 2019)
’HALITE IND. DS’: fast and scalable subspace clustering for multidimensional data streams
(Society for Industrial and Applied Mathematics - SIAMMiami, 2016-05)
Given a data stream with many attributes and high frequency of events, how to cluster similar events? Can it be done in real time? For example, how to cluster decades of frequent measurements of tens of climatic attributes ...
Data stream treatment using sliding windows with MapReduce
(Universidad Nacional de La Plata. Facultad de Informática, 2016-11)
Knowledge Discovery in Databases (KDD) techniques present limitations when the volume of data to process is very large. Any KDD algorithm needs to do several iterations on the complete set of data in order to carry out its ...
How Do Developers Use the Java Stream API
(2021)
Java 8 marked a shift in the Java development landscape by introducing functional-like concepts in its stream library. Java developers can now rely on stream pipelines to simplify data processing, reduce verbosity, easily ...
A survey on machine learning for recurring concept drifting data streams
The problem of concept drift has gained a lot of attention in recent years. This aspect is key in many domains exhibiting non-stationary as well as cyclic patterns and structural breaks affecting their generative processes. ...