A Study of Dynamic Word Sense Disambiguation Base don Full-sentence Co-occurrence of Node Word

Based on the property that word sense disambiguation is the return of word sense to context, we propose a dynamic word sense disambiguation method based on full sentence co occur rence of node word. The method firstly uses the full sentence as a window to limit the node word us age context, secondly uses statistical methods such as mutual information, chi square test and ratio of relative word rank to extract semantically related words, and builds a related semantic category data base by referring to "Tongyici Cilin" (A Dictionary of Synonyms), and finally uses the co occurrence frequency as a weighting factor to disambiguate the low and medium frequency co occurring multi sense words by relying on the distribution rate of single sense word meaning clusters. The method is used to disambiguate 1030 multiple meaning words with less than 7 meaning categories that co oc curred with "meili" (beautiful), and a correct rate of 85.2% is achieved in the test.