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Data compression by volume prototypes for streaming data

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/43802

Title: Data compression by volume prototypes for streaming data
Authors: Tabata, Kenji Browse this author
Sato, Maiko Browse this author
Kudo, Mineichi Browse this author →KAKEN DB
Keywords: Volume prototypes
One-pass algorithm
Streaming data
Concept drift
Issue Date: Sep-2010
Publisher: Elsevier
Journal Title: Pattern Recognition
Volume: 43
Issue: 9
Start Page: 3162
End Page: 3176
Publisher DOI: 10.1016/j.patcog.2010.03.012
Abstract: In these years, we often deal with an enormous amount of data in a large variety of pattern recognition tasks. Such data require a huge amount of memory space and computation time for processing. One of the approaches to cope with these problems is using prototypes. We propose volume prototypes as an extension of traditional point prototypes. A volume prototype is defined as a geometric configuration that represents some data points inside. A volume prototype is akin to a data point in the usage rather than a component of a mixture model. We show a one-pass algorithm to have such prototypes for data stream, along with an application for classification. An oblivion mechanism is also incorporated to adapt concept drift.
Type: article (author version)
URI: http://hdl.handle.net/2115/43802
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 工藤 峰一

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