Extracting Chinese abbreviation-definition pairs from anchor texts

Abstract

This paper proposes an automatic scheme to extract Chinese abbreviations and their corresponding definitions from large-scale anchor texts. This method is motivated by the observation that the more frequently two anchor texts point to the same web page, the more related they are. Since abbreviation-definition pairs are highly related, they can be extracted from these related words. Our method involves three steps. Firstly we utilize external statistical features to extract candidate abbreviation-definition pairs from anchor texts. Secondly we extract internal features from candidate pairs and adopt Conditional Random Fields (CRFs) to compute a score for each candidate pair. Finally we combine external and internal features to generate the final pairs. Experimental results show that this method can accurately extract Chinese abbreviation-definition pairs from anchor texts and combining both external and internal features is effective for extracting abbreviation-definition pairs.