Using n-grams for Korean text retrieval
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
A Syntax-Analysis Procedure for Unambiguous Context-Free Grammars
Journal of the ACM (JACM)
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Spelling correction using context
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
A stochastic finite-state word-segmentation algorithm for Chinese
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Korean POI word segmentation and tagging for speech interfac in-vehicle navigation system
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
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Compound noun segmentation is one of the crucial problems in Korean language processing because a series of nouns in Korean may appear without space in real text, which makes it difficult to identify its morphological constituents. This paper presents an effective method of Korean compound noun segmentation based on lexical data extracted from a corpus. The segmentation consists of two tasks: First, it uses a Hand-Build Segmentation Dictionary (HBSD) to segment compound nouns which frequently occur or need an exceptional process. Second, a segmentation algorithm using data from a corpus is proposed, where simple nouns and their frequencies are stored in a Simple Noun Dictionary (SND) for segmentation. The analysis is executed based on modified tabular parsing using min-max operation. Our experiments have shown a very effective accuracy rate of about 97.29%, which turns out to be very effective.