Visa International Service Association

Mengting Gu

Wei Zhang

Liang Wang

Michael Yeh

Yan Zheng

Zhongfang Zhuang

Jiarui Sun

Described are a system, method, and computer program product for dynamic node classification in temporal-based machine learning classification models. The method includes receiving graph data of a discrete time dynamic graph including graph snapshots, and node classifications associated with all nodes in the discrete time dynamic graph. The method includes converting the discrete time dynamic graph to a time-augmented spatio-temporal graph and generating an adjacency matrix based on a temporal walk of the time-augmented spatio-temporal graph. The method includes generating an adaptive information transition matrix based on the adjacency matrix and determining feature vectors based on the nodes and the node attribute matrix of each graph snapshot. The method includes generating and propagating initial node representations across information propagation layers using the adaptive information transition matrix and classifying a node of the discrete time dynamic graph subsequent to the first time period based on final node representations.

System, method, and computer program product for dynamic node classification in temporal-based machine learning classification models

Provided is a system for analyzing a multivariate time series that includes at least one processor programmed or configured to receive a time series of historical data points, determine a historical time period, determine a contemporary time period, determine a first time series of data points associated with a historical transaction metric from the historical time period, determine a second time series of data points associated with a historical target transaction metric from the historical time period, determine a third time series of data points associated with a contemporary transaction metric from the contemporary time period, and generate a machine learning model, wherein the machine learning model is configured to provide an output that comprises a predicted time series of data points associated with a contemporary target transaction metric. Methods and computer program products are also provided.

System, method, and computer program product for analyzing multivariate time series using a convolutional Fourier network

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Stanford, CA, United States of America

Mengting Gu