Applying Ontology and Probabilistic Model to Human Activity Recognition from Surrounding Things(Mobile Computing)
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概要
- 論文の詳細を見る
This paper proposes human activity recognition based on the actual semantics of the human's current location. Since no predefined semantics of location can adequately identify human activity, we automatically identify the semantics from things by focusing on the association between things and human activities with the things. Ontology is used to deal with the various possible representations (terms) of each thing, identified by a RFID tag, and a multi-class Naive Bayesian approach is applied to detect multiple actual semantics from the terms. Our approach is suitable for automatically detecting possible activities even given a variety of object characteristics including multiple representations and variability. Simulations with actual thing datasets and experiments in an actual environment demonstrate its noise tolerance and ability to rapidly detect multiple actual semantics from existing things.
- 一般社団法人情報処理学会の論文
- 2007-08-15
著者
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Sakamoto Kenji
Ntt Docomo Inc.
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YAMADA NAOHARU
NTT DoCoMo, Inc.
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KUNITO GORO
NTT DoCoMo, Inc.
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ISODA YOSHINORI
NTT DoCoMo, Inc.
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YAMAZAKI KENICHI
NTT DoCoMo, Inc.
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TANAKA SATOSHI
DoCoMo Technology, Inc.
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Sakamoto K
National Inst. Materials Sci. Ibaraki Jpn
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Sakamoto K
Laboratory Of Pharmacology And Toxicology Graduate School Of Pharmaceutical Sciences The University
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Yamazaki Kenichi
Ntt Docomo Inc.
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Sakamoto Kenji
Research Institute Of Marine Bioresources Fukuyama University
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Kunito Goro
Ntt Docomo Inc.
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Yamada Naoharu
Ntt Docomo Inc.
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Isoda Yoshinori
Ntt Docomo Inc.
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Sakamoto Kenji
Laboratory Of Pharmacology And Toxicology Graduate School Of Pharmaceutical Sciences The University
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Tanaka Satoshi
Docomo Technology Inc.
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Yamazaki Kenichi
Research Laboratories, NTT DoCoMo, Inc., Yokosuka Research Park (YRP)
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