Method and system for generating synchronized labelled training dataset for building a learning model

Abstract

Disclosed subject matter relates to supervised machine learning including a method and system for generating synchronized labelled training dataset for building a learning model. The training data generation system determines a timing advance factor to achieve time synchronization between User Equipment (UE) and network nodes, by signalling the UE to initiate playback of the multimedia content based on the timing advance factor. The training data generation system receives network Key Performance Indicator (KPI) data from the network nodes and a user experience data from the UE, concurrently, for the streamed multimedia content, and performs timestamp based correlation to generate a synchronized labelled training dataset for building a learning model. The learning model is further deployed in external analytics system to act as a non-intrusive passive probe to predict real-time user experience, without intruding into the UE, thereby sustaining privacy of the user and eliminating additional computing load on the UE.