Method, apparatus and computer program for operating a machine learning framework with active learning technique

A method for analyzing a user in a data analysis server, the method comprising:

• step A of establishing a question database comprising a plurality of questions, of collecting solving result data of a user for the plurality of questions, and of learning the solving result data, thereby generating a data analysis model for modeling the user;
• step B of generating an expert model that operates independently of the data analysis model, that is learned based on data different from data for the data analysis model, and that recommends learning data necessary for the data analysis model to improve performance of the data analysis model at an arbitrary point in time;
• step C of extracting at least one question from the question database according to recommendation from the expert model, and of updating the data analysis model using solving result data of a user for the at least one extracted question;
• and
• step D of updating the expert model by applying, to update information of the data analysis model, a reward that is set in a direction to improve prediction accuracy of the data analysis model,
• wherein the step B comprises generating the expert model by learning information on a first state of the data analysis model, information on a second state of the data analysis model, and data information causing the first state to change into the second state.