Estimating user suitability for collecting application QoE feedback

An apparatus, comprising:

• one or more network interfaces;
• a processor coupled to the one or more network interfaces and configured to execute one or more processes;
• and
• a memory configured to store a process that is executable by the processor, the process when executed configured to:
• obtain telemetry data regarding an interaction between a user and an online application that includes performance metrics for network traffic associated with the interaction;
• obtain a satisfaction rating provided by the user regarding the interaction;
• make, based on the telemetry data and the satisfaction rating, a suitability assessment as to how suitable the interaction is for training a machine learning model to predict a quality of experience metric for the online application;
• and
• prevent the telemetry data and satisfaction rating from being used to train the machine learning model, when the suitability assessment indicates that the interaction is unsuitable for training the machine learning model.

A tangible, non-transitory, computer-readable medium storing program instructions that cause a device to execute a process comprising:

• obtaining, by the device, telemetry data regarding an interaction between a user and an online application that includes performance metrics for network traffic associated with the interaction;
• obtaining, by the device, a satisfaction rating provided by the user regarding the interaction;
• making, by the device and based on the telemetry data and the satisfaction rating, a suitability assessment as to how suitable the interaction is for training a machine learning model to predict a quality of experience metric for the online application;
• and
• preventing, by the device, the telemetry data and satisfaction rating from being used to train the machine learning model, when the suitability assessment indicates that the interaction is unsuitable for training the machine learning model.