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Segmentation of Compound Nouns using Composite Mutual Information

In Korean, a compound noun may be freely formed with or without spaces between simple nouns. The exible word formation rule of Korean raises a serious problem in processing compound nouns with computers, in particular, in searching a dictionary with the compound noun as a search key. This paper describes a corpus-based method for segmenting a compound noun into simple nouns. Segmentation is performed with the composite of four types of mutual information, each calculated from two adjacent syllables. Experiments with a test data set of 1,458 compound nouns show that the correct segmentation rate of the proposed method is 98.3%. A text corpus of 1.1 million words (4.9 million syllables) is used for the calculation of composite mutual information.