Presentation | 2007-07-02 Trend Detection under the Time Warping Machiko TOYODA, Toshikazu ICHIKAWA, Yasushi SAKURAI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Data stream is becoming increasingly important in several domains such as finance, sensor network environment, manufacture, network monitoring. The most fundamental support needed in these applications is efficient monitoring of time series data streams, and a subsequece-matching mechanism is required. In this paper, we propose a new function to recognize the similarity between subsequences, and then present an efficient sequence matching algorithm for data streams. Several experiments with synthetic and real data sets show that our algorithm works well as expected ; it can efficiently detect sequence trends in the data sets. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Data Stream / Time Warping / Trend Detection / Subsequence Matching |
Paper # | DE2007-28 |
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Committee | DE |
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Conference Date | 2007/6/25(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Data Engineering (DE) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Trend Detection under the Time Warping |
Sub Title (in English) | |
Keyword(1) | Data Stream |
Keyword(2) | Time Warping |
Keyword(3) | Trend Detection |
Keyword(4) | Subsequence Matching |
1st Author's Name | Machiko TOYODA |
1st Author's Affiliation | NTT Information Sharing Platform laboratories, NTT Corpration() |
2nd Author's Name | Toshikazu ICHIKAWA |
2nd Author's Affiliation | NTT Information Sharing Platform laboratories, NTT Corpration |
3rd Author's Name | Yasushi SAKURAI |
3rd Author's Affiliation | NTT Communication Science Laboratories, NTT Corporation |
Date | 2007-07-02 |
Paper # | DE2007-28 |
Volume (vol) | vol.107 |
Number (no) | 131 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |