Application of Text Analysis Methods to Recommend Student Choices

Abstract

The paper considers the use of natural language processing methods to recommend student choices. Descriptions of subjects taken by the student serve as the basis for compiling the student profile. This profile is used to rate available side projects as most corresponding to that student’s educational history. The quality of recommendations is evaluated based on the data from the "Individual Educational Trajectories" system.