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AssigneeVerint Americas Inc.
InventorsHamed Janani, Anirudh Challa, Hong Wang, Mohamad Al-Sharara, José R. Benkí, Zealand Cooley
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An anomaly detection system using machine learning to generate predicted survey scores for a given duration and a given metric based on historic survey score data. The system compares a predicted survey score to the actual survey score and identifies anomalous actual survey scores. The anomaly detection system trains a plurality of survey score prediction models using historic survey score data. Each survey score prediction model is based on a specific survey score metric and a specific duration. The survey score prediction models generate expected survey score results for the given duration and the given metric. Based on the user-determined filtering and tolerances, the system determines if the actual survey score result is anomalous. The system generates reports for the detected anomalies and continually updates the survey score prediction models with newly obtained actual survey results, thereby improving the anomaly detection accuracy over time.
A method for detecting anomalies in actual survey score results, the method comprising:
A system for detecting anomalies in actual survey score results, the system comprising:
A non-transitory computer readable medium comprising computer readable code to detect anomalies in actual survey score results on a system that when executed by a processor, causes the system to:
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