This paper reviews the technical progress of Chinese word segmentation in 2007-2017 for ten years, especially since the deep penetration of deep learning into natural language processing. Our basic conclusion is that the supervised machine learning method of Chinese word segmentation has not shown obvious technical advantages in the migration from non-neural network method to neural network method. The construction of the machine learning model of Chinese word segmentation still needs to balance the recognition problem of known words and unregistered words.
