Accelerating Sequence Operator with Reduced Expression

Hideyuki Kawashima, Osamu Tatebe

研究成果: Conference contribution

抜粋

Sequence operators are effective for efficiently combining multiple events when state recognition is performed by combining time series events. Since sensor data are inherently noisy, one can take a strict attitude to deal with them: It is conceivable that all of time series events are regarded as false positives. Then, all complex events should be constructed carefully. Such an attitude is called the skip-till-any-match model in the sequence operator. When using this model, huge amounts of potential complex events are generated. A sequence operator usually supports both Kleene closure and non-Kleene closure. While efficient methods have been studied for Kleene closure so far, that for non-Kleene closure have been still explored. In this paper, we propose the reduced expression method to improve the efficiency of sequence operator processing for the skip-till-any-match model. Experimental results showed that the processing time and memory size were more efficient compared with SASE, which is the conventional method, and that degree is up to several thousand times.

元の言語English
ホスト出版物のタイトルInformation Modelling and Knowledge Bases XXXI
編集者Ajantha Dahanayake, Janne Huiskonen, Yasushi Kiyoki, Bernhard Thalheim, Hannu Jaakkola, Naofumi Yoshida
出版者IOS Press
ページ71-82
ページ数12
ISBN(電子版)9781643680446
DOI
出版物ステータスPublished - 2019 12 13
イベント29th International Conference on Information Modeling and Knowledge Bases, EJC 2019 - Lappeenranta, Finland
継続期間: 2019 6 32019 6 7

出版物シリーズ

名前Frontiers in Artificial Intelligence and Applications
321
ISSN(印刷物)0922-6389

Conference

Conference29th International Conference on Information Modeling and Knowledge Bases, EJC 2019
Finland
Lappeenranta
期間19/6/319/6/7

ASJC Scopus subject areas

  • Artificial Intelligence

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  • これを引用

    Kawashima, H., & Tatebe, O. (2019). Accelerating Sequence Operator with Reduced Expression. : A. Dahanayake, J. Huiskonen, Y. Kiyoki, B. Thalheim, H. Jaakkola, & N. Yoshida (版), Information Modelling and Knowledge Bases XXXI (pp. 71-82). (Frontiers in Artificial Intelligence and Applications; 巻数 321). IOS Press. https://doi.org/10.3233/FAIA200007