Irrevocable-choice algorithms for sampling from a stream

• Autores: Yan Zhu, Eamonn Keogh
• Localización: Data mining and knowledge discovery, ISSN 1384-5810, Vol. 30, Nº 5, 2016, págs. 998-1023
• Idioma: inglés
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• Resumen

  • The problem of sampling from data streams has attracted significant interest in the last decade. Whichever sampling criteria is considered (uniformsample, maximally diversesample, etc.), the challenges stem from the relatively small amount of memory available in the face of unbounded streams. In this work we consider an interesting extension of this problem, the framework of which is stimulated by recent improvements in sensing technologies and robotics. In some situations it is not only possible to digitallysense some aspects of the world, but to physicallycapture a tangible aspect of that world. Currently deployed examples include devices that can capture water/air samples, and devices that capture individual insects or fish. Such devices create an interesting twist on the stream sampling problem, because in most cases, the decision to take a physical sample is irrevocable. In this work we show how to generalize diversification sampling strategies to the irrevocable-choice setting, demonstrating our ideas on several real world domains.