Patent ID: 11860721
Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. A device, comprising: one or more memories; and one or more processors, coupled to the one or more memories, configured to: receive historical software data identifying logs and events associated with software products utilized by an entity; process the historical software data with a data labelling model to generate historical health scores, historical sentiment scores, and historical dissimilarity scores for the software products; train a machine learning model based on the historical software data and based on a combination of the historical health scores, the historical sentiment scores, and the historical dissimilarity scores, wherein the training comprises: determining, based on supervised learning of the machine learning model and based on new input, a prediction; implementing a feedback loop to train the machine learning model; and determining whether the prediction satisfies a threshold level of accuracy, and wherein new historical software data is processed with the trained machine learning model instead of the data labeling model when the prediction satisfies the threshold level of accuracy; receive software data identifying current logs and events associated with software products utilized by the entity; process the software data with the trained machine learning model to generate error severity scores associated with the software products; process the error severity scores, with a prioritization model, to generate prioritized error scores; process the error severity scores and the prioritized error scores, with a root cause analysis model, to generate root cause data identifying root causes associated with the error severity scores; perform one or more actions based on the root cause data; receive feedback via the feedback loop; and retrain, based on the feedback, the trained machine learning model.