以Normalized Google Distance辨識學名與別名-以化學物質為例

Since Names of Chemical material can be very complex and lay people mostly do not have relevant expertise in chemicals, they usually find related information through search engines or look up an online chemical dictionary. However, the chemical material names used in academy usually translated from English, and the same chemicals often have many different aliases. This English Chinese translation creates many problems when querying information for chemicals. Recent studies have proposed to use NGD to determine semantic relevance between two words. Therefore, this study proposes to find alias based on NGD with two methods, namely, novel and category affixed methods. The Experimental results show that the latter method can derive better result.