C96-2154 are parameters involved in the similarity calculation , the size of the sublanguage
C04-1138 seven days . The input for the similarity calculation is the cluster vector produced
C96-2191 scores to each candidate using a similarity calculation . The scores realize " deter
C04-1005 the method for monolingual word similarity calculation . This method calculates word
D08-1062 larity . The features used in this similarity calculation are based on the surrounding
C04-1005 word alignment results . F F Word Similarity Calculation This section describes the method
C02-1041 stop-words ) are extracted and used for similarity calculation . We give different weights to
C92-2115 most similar one . Note that this similarity calculation was done for all rules , including
C04-1138 considerable weight in the cross-lingual similarity calculation is given to the countries that
C02-1083 experiment , we have adopted a semantic similarity calculation method for measuring the similarity
C02-1162 has been in monolingual semantic similarity calculation . Our problem is more complicated
C00-1047 stop-word list and improvement of similarity calculation of documents . An important finding
A94-1007 semantic features and semantic similarity calculation . We are introducing some semantic
C04-1138 . The output for each pairwise similarity calculation is a similarity value between
C94-2169 categories in BGIt , the results of the similarity calculation are sim . . ( Se ~ nh ~ , Semhe
C04-1138 significantly improves document similarity calculation and cluster - ing . Hyland et
C92-2115 , which combines I ~ CT with a similarity calculation method . RCT has powerful correspondences
C02-1107 consideration , and thus the result of similarity calculation may become large even if they
C92-2115 , I will introduce RCT and the similarity calculation method used in SimTran . The
C92-2115 SimTran is RCT coupled with a similarity calculation method . In tbis paper , I will
hide detail