This paper I)roI)oses two new methods to identify the correct meaning of Japanese honmnyms in text based on tile iloun:verb co-occIlrrenc( ~, ill a sentence which (:an be obtained easily from corpora. The first method uses the near co-occurrence data sets, which are constructed from the above (:o-occurrence relation, to select the most fe~Lsible word among homonyms in the s(:ol)e of a sea> tence. Tile se(:ond uses the flu' cooccurrence data sets, which are construtted dynamically fl'om the near

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... cooccurrence data sets in the course of processing input sentences, to select the most feasible word among homonyms ill the s(:ope of a sequence of sentences. An experiment of kana-to-kanfi(phonogran> to-ideograph) conversion has shown that the conversion is carried out at the accuracy rate of 79.6% per word by the first method. This accuracy rate of our method is 7.4% higher than that of the ordinary method based on the word occurrence frequency.