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- W2067708905 abstract "This paper presents a Chinese word segmentation system based on conditional random fields, which integrates the result information of N-gram model as features of conditional random fields. Since dictionary-based N-gram model can deal with in-vocabulary words very well, while conditional random fields have the advantage of recognizing out-of-vocabulary words. This approach is evaluated using the PKU data from Sighan Bakeoff 2005. The experimental results have proven that this method achieved an F-measure of 95.0% and higher R oov (85.2%) and R iv (97.9%)." @default.
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- W2067708905 date "2012-07-01" @default.
- W2067708905 modified "2023-09-25" @default.
- W2067708905 title "Integrating N-gram model information for Chinese word segmentation based on conditional random fields" @default.
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- W2067708905 doi "https://doi.org/10.1109/icmlc.2012.6359021" @default.
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