AI RESEARCH
Deep Distance Measurement Method for Unsupervised Multivariate Time Series Similarity Retrieval
arXiv CS.LG
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ArXi:2603.12544v1 Announce Type: new We propose the Deep Distance Measurement Method (DDMM) to improve retrieval accuracy in unsupervised multivariate time series similarity retrieval. DDMM enables learning of minute differences within states in the entire time series and thereby recognition of minute differences between states, which are of interest to users in industrial plants.