Abstract
While various techniques for chance (or risk) discovery have been proposed so far, they mainly analyze symbolized time-series data such as text or monthly sales amounts. On the other hand, we can easily access to unlabeled digitized data such as audio or video signal owing to the recent development of networks, computers and video devices. In this paper, we focus on pattern retrieval methods, which enable us to discover chances directly from such raw data.
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© 2001 Springer-Verlag Berlin Heidelberg
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Nishimura, T., Oka, R. (2001). Retrieval of Similar Time-Series Patterns for Chance Discovery. In: Terano, T., Ohsawa, Y., Nishida, T., Namatame, A., Tsumoto, S., Washio, T. (eds) New Frontiers in Artificial Intelligence. JSAI 2001. Lecture Notes in Computer Science(), vol 2253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45548-5_67
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DOI: https://doi.org/10.1007/3-540-45548-5_67
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