隠れ状態の継続時間長を考慮した確率モデルに関する調査
書誌事項
- タイトル別名
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- A Survey of Probabilistic Modeling Techniques of Hidden States and their Duration Distributions
説明
<p>Human activity data, so-called "life-log data", has underlying contexts such as sleeping, driving a car, eating. In order to analyse and predict such data, the hidden Markov model is often used. However, the duration time of the hidden context state of HMM distributes exponentially and this is not suited for modeling the above contexts. In order for modeling these context flexibly, we introduce and compare probabilistic modeling techniques of of hidden states with general duration distributions.</p>
収録刊行物
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- 人工知能学会第二種研究会資料
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人工知能学会第二種研究会資料 2009 (DMSM-A902), 04-, 2009-10-18
一般社団法人 人工知能学会
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詳細情報 詳細情報について
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- CRID
- 1390007750044974720
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- NII論文ID
- 130008079601
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- ISSN
- 24365556
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用可
