A stochastic finite-state word-segmentation algorithm for Chinese
Computational Linguistics
Chinese word segmentation without using lexicon and hand-crafted training data
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
The application of kalman filter based human-computer learning model to chinese word segmentation
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
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We have proposed a method of word segmentation for non-segmented language using Inductive Learning. This method uses only surface information of a text, so that it has an advantage that is entirely not dependent on any specific language. In this method, we consider that a character string of appearing frequently in a text has a high possibility as a word. The method predicts unknown words by recursively extracting common character strings. With the proposed method, the segmentation results can adapt to different users and fields. To evaluate effectivety for Chinese word segmentation and adaptability for different fields, we have done the evaluation experiment with Chinese text of the two fields.