An End-to-end Tag-based Recommendation System for Verbal Reasoning Questions

Abstract

Developing a verbal reasoning question recommendation system is an ideal way to help the GRE® test takers improve their verbal reasoning abilities by practicing questions more efficiently. As there are a great number of verbal reasoning practice questions and limited practice time for test takers, it is impossible to practice all kinds of questions at the same time. Personalized referral systems should be built based on the characteristics of specific respondents, and forming professional recommendation systems for different questions. Based on the examinee's current practicing accuracy and fallible difficulties, we propose an End-to-end Tag-based Recommendation System (ETRS) for task takers to optimize practice effect. Code of this paper can be found on https://github.com/Oliver-Q/ETRS-for-Verbal-Reasoning-Questions.