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We present a syllable bigram model forsegmentingaKoreansentenceinto words and correcting word-spacing errors in the spelling checker. We evaluated the system's performance for automatic word segmentation, word-spacing error detection, and the word-splitting problem of the characterrecognitionsystemattheend ofaline.
1 Document clustering is an aggregation of related documents to a cluster based on the similarity evaluation task between documents and the representatives of clusters. Terms and their discriminating features of terms are the clue to the clustering and the discriminating features are based on the term and document frequencies. Feature selection method on… (More)
This paper describes a syllable-based computational model for the Korean morphology. In this model, morpholovical analysis is considered as a process of candidate Generation and candidate selection. In order to increase tile performance of the system, the number of candidates is highly reduced and tim system require.s small number of dictionary accesses.… (More)
It is common that representative words in a document are identified and discriminated by their statistical distribution of their frequency statistics. We assume that evaluating the confidence measure of terms through contentbased document analysis leads to a better performance than the parametric assumptions of the standard frequency-based method. In this… (More)