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发表时间：2007-01-01

发表刊物：大连理工大学学报

期号：1

页面范围：131-135

ISSN号：1000-8608

摘要：In the text mining, the technology of Chinese automatic word segmentation is a difficult problem that the computer science has to face. Aiming at the characteristics of Chinese writing, such as no space between words, continuous writing in sentences and difficulty of segmenting the ambiguous words, the grammatical phenomena are summarized which lie in the typical ambiguity, and the codes library of different parts of speech used for coding is built up. On this basis, words in ambiguity fields with special grammatical rules are set with codes and transformed to the representation form of inputting vector which can be accepted by the neural network. Then the samples are trained and the grammatical rules can be obtained by improving the self-learning of BP neural network. After a lot of training through adopting the BP network, the algorithm reaches 93.13% of training precision and 92.50% of test precision on ambiguous words segmentation.

备注：新增回溯数据