US Patent 11651249 Determining similarity between time series using machine learning techniques

Methods, apparatus, and processor-readable storage media for determining similarity between time series using machine learning techniques are provided herein. An example computer-implemented method includes obtaining a primary time series and a set of multiple candidate time series; calculating, using machine learning techniques, similarity measurements between the primary time series and each of the candidate time series; for each of the similarity measurements, assigning weights to the candidate time series based on similarity to the primary time series relative to the other candidate time series; generating, for each of the candidate time series, a similarity score based on the weights assigned to each of the candidate time series across the similarity measurements; and outputting, based on the similarity scores, identification of at least one candidate time series for use in one or more automated actions relating to at least one system.