Automatic Access to Legal Terminology Applying Two Different Automatic Term Recognition Methods

Automatic term recognition (ATR) methods help to identify the most representative terms in a corpus automatically, saving time and allowing managing large amounts of data that could not be dealt with manually. This paper presents the evaluation of two ATR methods implemented on a 2.6 million-word legal corpus designed and compiled ad hoc: Keywords (Scott, 2008) and Chung's method (2003). Both techniques have been assessed as regards precision and recall. The results clearly show that Keywords is, by far, the most efficient one achieving to recognize 62% true terms out of the 2,000 items evaluated in this study.