Predicting data incompleteness using a neural network model

A device, comprising:

• one or more memories;
• and
• one or more processors, coupled to the one or more memories, configured to:
• train a machine learning model to analyze data to predict sentiments associated with the data and a measure of incompleteness of the data;
• obtain communication data generated during a communication session between a first device and a second device,
• wherein the communication data is obtained via a network;
• provide the communication data as an input to the trained machine learning model;
• determine, using the trained machine learning model, a first set of sentiments associated with the first device and a second set of sentiments associated with the second device;
• determine one or more matches between the first set of sentiments and the second set of sentiments;
• determine, using the trained machine learning model, a measure of incompleteness of the communication data based on the one or more matches between the first set of sentiments and the second set of sentiments;
• and
• perform an action based on the measure of incompleteness of the communication data.

A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:

• one or more instructions that, when executed by one or more processors of a prediction system, cause the prediction system to:
• train a machine learning model to analyze data to predict sentiments associated with the data and a measure of incompleteness of the data;
• obtain communication data generated during a communication session between a first device and a second device,
• wherein the communication data is obtained via a network;
• provide the communication data as an input to the trained machine learning model;
• determine, using the trained machine learning model, a first set of sentiments associated with the first device and a second set of sentiments associated with the second device;
• determine one or more matches between the first set of sentiments and the second set of sentiments;
• determine, using the trained machine learning model, a measure of incompleteness of the communication data based on the one or more matches between the first set of sentiments and the second set of sentiments;
• and
• perform an action based on the measure of incompleteness of the communication data.