書誌事項
- タイトル別名
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- Detecting Frequent Patterns in Time Series Data using Partly Locality Sensitive Hashing
- Partly Locality Sensitive Hashing オ モチイタ ジケイレツ データ カラ ノ コウヒンド パターン チュウシュツ
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抄録
Frequent patterns in time series data are useful clues to learn previously unknown events in an unsupervised way. In this paper, we propose a method for detecting frequent patterns in long time series data efficiently. The major contribution of the paper is two-fold: (1) Partly Locality Sensitive Hashing (PLSH) is proposed to find frequent patterns efficiently and (2) the problem of finding consecutive time frames that have a large number of frequent patterns is formulated as a combinatorial optimization problem which is solved via Dynamic Programming (DP) in polynomial time O (N 1+1/α) thanks to PLSH where N is the total amount of data. The proposed method was evaluated by detecting frequent whole body motions in a video sequence as well as by detecting frequent everyday manipulation tasks in motion capture data.
収録刊行物
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- 日本ロボット学会誌
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日本ロボット学会誌 29 (1), 67-76, 2011
一般社団法人 日本ロボット学会
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詳細情報 詳細情報について
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- CRID
- 1390282679701780096
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- NII論文ID
- 10027648570
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- NII書誌ID
- AN00141189
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- ISSN
- 18847145
- 02891824
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- NDL書誌ID
- 10956820
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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
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可