Feature extraction of private-sector English tests using data mining

Abstract

In this study, English sentences of several private-sector English tests that the Japan’s education ministry has been considering to introduce as part of the university entrance common test are examined in terms of metrical linguistics. In short, frequency characteristics of character and word-appearance are investigated using a program written in C++. These characteristics are approximated by an exponential function. Furthermore, the percentage of Japanese junior high school required vocabulary and American basic vocabulary is calculated to obtain the difficulty-level of each material.