Classification, Similarity Search, and Labeling of Time Series Data
Project/Area Number |
20500139
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Intelligent informatics
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Research Institution | Hiroshima City University |
Principal Investigator |
HAYASHI Akira Hiroshima City University, 情報科学研究科, 教授 (60240909)
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Project Period (FY) |
2008 – 2010
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Project Status |
Completed (Fiscal Year 2010)
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Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2010: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2009: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2008: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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Keywords | 時系列データ / カーネル法 / DTW / 正定値計画法 / 隠れマルコフモデル / CRF / ラベルづけ / 条件付き確率場 / 階層隠れCRF / 識別モデル / 情報抽出 / 固有表現抽出 / 半正定計画法 / 条件付確率場 / スポーツビデオ |
Research Abstract |
1. We have developed kernels for time series data using dynamic time warping (DTW) distances. We use semidefinite programming to guarantee the positive definiteness of a kernel matrix. We use two applications, time series classification and time series embedding for similarity search to validate our approach. 2. We have proposed HHCRFs (hierarchical hidden CRFs). In the experiment, we show that HHCRFs perform better than HHMMs (hierarchical hidden Markov models) in state sequence estimation, as the training set size becomes larger and the data source becomes non-Markovian.
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Report
(4 results)
Research Products
(24 results)
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[Journal Article] 階層隠れCRF2010
Author(s)
玉田寛尚, 林朗, 末松伸朗, 岩田一貴
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Journal Title
電子情報通信学会論文誌D
Volume: J-93D(12)
Pages: 2610-2619
NAID
Related Report
Peer Reviewed
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