Presentation 2009-07-16
Applying a Probabilistic Inference Stream Processing Engine to a Camera Sensor Network
Ryo SATO, Hideyuki KAWASHIMA, Hiroyuki KITAGAWA,
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Abstract(in English) The purpose of this paper is to appropriately incorporate Bayesian networks into a relational stream processing system in the form of abstract data type. To achieve it, we propose two mechanisms. The first proposal is a mechanism to associate an input relation with an internal relation which has Bayesian networks. We refer to it as ASSOC, and show its processing mechanism and interface as a data definition language. The second proposal is a new state management mechanism with lifespan concept for Bayesian network operator, revising our previous work. The proposal includes counting of event sets and event based invocation. of probability propagation, which realizes appropriate event detections.
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Keyword(in English) Bayesian Network / Stream Data Processing / Camera Sensor Network / Event Window Operator
Paper # USN2009-20
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Conference Date 2009/7/9(1days)
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Registration To Ubiquitous and Sensor Networks(USN)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Applying a Probabilistic Inference Stream Processing Engine to a Camera Sensor Network
Sub Title (in English)
Keyword(1) Bayesian Network
Keyword(2) Stream Data Processing
Keyword(3) Camera Sensor Network
Keyword(4) Event Window Operator
1st Author's Name Ryo SATO
1st Author's Affiliation Graduate School of Systems and Information Engineering, University of Tsukuba()
2nd Author's Name Hideyuki KAWASHIMA
2nd Author's Affiliation Graduate School of Systems and Information Engineering, University of Tsukuba:Center for Computational Sciences, University of Tsukuba
3rd Author's Name Hiroyuki KITAGAWA
3rd Author's Affiliation Graduate School of Systems and Information Engineering, University of Tsukuba:Center for Computational Sciences, University of Tsukuba
Date 2009-07-16
Paper # USN2009-20
Volume (vol) vol.109
Number (no) 131
Page pp.pp.-
#Pages 6
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