Big Data Stream Learning with SAMOA

被引:30
|
作者
Bifet, Albert [1 ]
De Francisci Morales, Gianmarco [2 ]
机构
[1] HUAWEI Noahs Ark Lab, Hong Kong, Hong Kong, Peoples R China
[2] Yahoo Labs, Barcelona, Spain
关键词
D O I
10.1109/ICDMW.2014.24
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Big data is flowing into every area of our life, professional and personal. Big data is defined as datasets whose size is beyond the ability of typical software tools to capture, store, manage and analyze, due to the time and memory complexity. Velocity is one of the main properties of big data. In this demo, we present SAMOA (Scalable Advanced Massive Online Analysis), an open-source platform for mining big data streams. It provides a collection of distributed streaming algorithms for the most common data mining and machine learning tasks such as classification, clustering, and regression, as well as programming abstractions to develop new algorithms. It features a pluggable architecture that allows it to run on several distributed stream processing engines such as Storm, S4, and Samza. SAMOA is written in Java and is available at http://samoa-project.net under the Apache Software License version 2.0.
引用
收藏
页码:1199 / 1202
页数:4
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