A New Method of Extracting Chinese Term Based on Open Corpus

Abstract

Automatic Chinese Term Extraction is an important issue in Natural Language Processing. This paper has proposed a new method to extract terms from open corpus. We have used two improved traditional parameters: mutual information and log-likelihood ratio, and have increased the precision of the method to 75.4%. The results of the research indicate that this method is more efficient and robust than previous term-extraction methods.