Third-party load aggregation platform interaction data anomaly detection method and system

The invention discloses a third-party load aggregation platform interaction data anomaly detection method and system in the field of data anomaly detection, and the method comprises the steps: inputting interaction data into a pre-trained data anomaly detection model, and judging whether the interaction data is abnormal data or not through the data anomaly detection model; denoising the interactive initial data through discrete binary wavelet transform to obtain training interactive data; extracting k times of training interaction data in batches to form a data sample; performing spectral clustering algorithm processing on the data samples to obtain a candidate training data set; comparing the Jaccard similarity coefficient with a set threshold value to screen out abnormal data points and normal data points, and constructing a training data set; training the deep residual learning network by using the training data set to obtain a data anomaly detection model; according to the method, the third-party service