Univariate time series segmentation using proxy variables and sparse graph recovery algorithms

Abstract

This disclosure relates to a time series segmentation system that efficiently and accurately segments univariate time series data. For example, the time series segmentation system utilizes proxy variable time series to identify distinct segments in a univariate time series. To illustrate, the time series segmentation system generates proxy variables that approximate a univariate time series and combine with the time series to generate a supplemented multivariate time series. The time series segmentation system then divides the supplemented multivariate time series into portions using time-based windows, converts the windowed subsequences into graph objects using a sparse graph recovery model, utilizes a conditional similarity model to determine segmentation timestamps from the graph objects, and generates a segmented univariate time series from the segmentation timestamps.