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COMPACT REPRESENTATION AND TIME SERIES SEGMENT RETRIEVAL THROUGH DEEP LEARNING
COMPACT REPRESENTATION AND TIME SERIES SEGMENT RETRIEVAL THROUGH DEEP LEARNING
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机译:通过深度学习,紧凑的表示和时间序列段检索
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摘要
Systems and methods for retrieving similar multivariate time series segments are provided. The systems and methods include extracting a long feature vector and a short feature vector from a time series segment, converting the long feature vector into a long binary code, and converting the short feature vector into a short binary code. The systems and methods further include obtaining a subset of long binary codes from a binary dictionary storing dictionary long codes based on the short binary codes, and calculating similarity measure for each pair of the long feature vector with each dictionary long code. The systems and methods further include identifying a predetermined number of dictionary long codes having the similarity measures indicting a closest relationship between the long binary codes and dictionary long codes, and retrieving a predetermined number of time series segments associated with the predetermined number of dictionary long codes.
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