A variable-length motifs discovery method in time series using hybrid approach

Chaw Thet Zan, Hayato Yamana

    研究成果: Conference contribution

    抜粋

    Discovery of repeated patterns, known as motifs, from long time series is essential for providing hidden knowledge to real-world applications like medical, financial and weather analysis. Motifs can be discovered on raw time series directly or on their transformed abstract representation alternatively. Most of time series motif discovery methods require predefined motif length, which results in long execution time because we have to vary the length to discover motifs with different lengths. To solve the problem, we propose an efficient method for discovering variable length motifs in combination of approximate method with exact verification. First, symbolic representation is adopted to discover motifs roughly followed by exact examination of the found motifs with original real-valued data to achieve fast and exact discovery. The experiments show that our proposed method successfully discovered significant motifs efficiently in comparison with state-of-the-art methods: MK and SBF.

    元の言語English
    ホスト出版物のタイトル19th International Conference on Information Integration and Web-Based Applications and Services, iiWAS2017 - Proceedings
    出版者Association for Computing Machinery
    ページ49-57
    ページ数9
    Part F134476
    ISBN(電子版)9781450352994
    DOI
    出版物ステータスPublished - 2017 12 4
    イベント19th International Conference on Information Integration and Web-Based Applications and Services, iiWAS2017 - Salzburg, Austria
    継続期間: 2017 12 42017 12 6

    Other

    Other19th International Conference on Information Integration and Web-Based Applications and Services, iiWAS2017
    Austria
    Salzburg
    期間17/12/417/12/6

      フィンガープリント

    ASJC Scopus subject areas

    • Human-Computer Interaction
    • Computer Networks and Communications
    • Computer Vision and Pattern Recognition
    • Software

    これを引用

    Zan, C. T., & Yamana, H. (2017). A variable-length motifs discovery method in time series using hybrid approach. : 19th International Conference on Information Integration and Web-Based Applications and Services, iiWAS2017 - Proceedings (巻 Part F134476, pp. 49-57). Association for Computing Machinery. https://doi.org/10.1145/3151759.3151781