Abstract:

When dealing with the specific problem of a  Chinese organization′s full name and matching abbreviation,  the traditional string matching algorithm based on editdistance performs poorly. A new algorithm,  also based on editdistance, was provided. The improvements include the following steps: (1)  making the Chinese word segmentation  fit  the Chinese grammatical structure features, (2) modifying the editoperation weights with the redefined semantic similarity, (3) adjusting these weights by adaptive learning, and (4) choosing the full name with minimum edit-distance as the matching result. Experimental results show that our algorithm can effectively achieve higher abbreviationfull name matching accuracy.

Key words: text mining; machine learning; edit distance; organization name; abbreviation-full name match