Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/18963
Title: | Comparing data distribution using fading histograms |
Author: | Sebastião, Raquel Gama, João Mendonça, Teresa |
Keywords: | Change detection Data distribution Dynamic scenarios Kullback Leibler divergence Online monitoring |
Issue Date: | 2014 |
Publisher: | IOS Press |
Abstract: | The emergence of real temporal applications under non-stationary scenarios has drastically altered the ability to generate and gather information. Nowadays, under dynamic scenarios, potentially unbounded and massive amounts of information are generated at high-speed rate, known as data streams. Dealing with evolving data streams imposes the online monitoring of data in order to detect changes. The contribution of this paper is to present the advantage of using fading histograms to compare data distribution for change detection purposes. In an windowing scheme, data distributions provided by the fading histograms are compared using the Kullback-Leibler divergence. The experimental results support that the detection delay time is smaller when using fading histograms to represent data instead of standard histograms. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/18963 |
DOI: | 10.3233/978-1-61499-419-0-1095 |
Appears in Collections: | IEETA - Capítulo de livro |
Files in This Item:
File | Description | Size | Format | |
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ECAI-361.pdf | post-print | 95.36 kB | Adobe PDF | View/Open |
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