Abstract
This paper presents an alternative method to measure word association strength on predicative patterns in order to automatically extract predicative frozen patterns and idioms from a corpus. For this aim, mutual information is traditionally used. We improve the method on mutual information from a view of linguistics. The proposed method are realized by following steps. First, a verb (or noun) is fixed. Next, the set of nouns (or verbs) which associates the verb (or noun) is built up. Last, nouns (or verbs) which have peculiar frequency are chosen from this set. The peculiarity is confirmed from two characteristics, which are ratio of the word frequency for total frequency of the set, and the number of kind of word in the set. Predicative frozen patterns are constructed from chosen words and the fixed word. The advantage of this method is that patterns extracted by fixing a verb and patterns extracted by fixing a noun have few common patterns, and each extraction has equivalent ratio of correctness to extraction by mutual information. Therefore, extracting same number patterns, this method can get more correct patterns than mutual information.
