A Chinese word segmentation method and apparatus based on deep learning. The method comprises: converting training corpus data into character-level data; converting the character-level data into sequence data; segmenting the sequence data according to pre-set symbols to obtain a plurality of pieces of sub-sequence data, and grouping the plurality of pieces of sub-sequence data according to the lengths of the sub-sequence data to obtain K data sets; according to the K data sets, obtaining K trained time sequence convolutional neural network-conditional random field models; and inputting data obtained after the processing of target corpus data into at least one of the K trained time sequence convolutional neural network-conditional random field models to obtain a word segmentation result for the target corpus data. Therefore, the method can solve the problem of the low accuracy of Chinese word segmentation in the prior art.
CHINESE WORD SEGMENTATION METHOD AND APPARATUS BASED ON DEEP LEARNING, AND STORAGE MEDIUM AND COMPUTER DEVICE