We present a Chinese word segmentation model learned from punctuation marks which are perfect word delimiters. The learning is aided by a manually segmented corpus. Our method is considerably more effective than previous methods in unknown word recognition. This is a step toward addressing one of the toughest problems in Chinese word segmentation. We call the first character of a Chinese word its left boundary L, and the last character its right boundary R. If we regard L and R as random events, then we can derive four events (or tags) from them:
REF used punctuation information in Chinese word segmentation by introducing extra labels 'L' and 'R'.
Punctuation as Implicit Annotations for Chinese Word Segmentation
Computational Linguistics
Computational Linguistics
Computer Science