CNN-Based Model for Chinese Information Processing and Its Application in Large-Scale Book Purchasing
Chi Guo, Peilin Yu, Wenfei Guo, Xiaxian Wang · 2020
The demand for library books has been growing year by year, and manual methods for purchasing books have been unable to keep with these ever-increasing Chinese book demands. As deep learning techniques have developed, they have achieved remarkable results in various fields. In this study, we applied a convolution neural network (CNN)-based model to the book purchasing task. We also built a Chinese book dataset based on historical data from the Wuhan University Library. Experimental results on this dataset show that our CNN-BOOK model can reach an accuracy of 83% on the book purchasing task. This method greatly improves the efficiency of book purchases and can provide new ideas for how library purchasing is conducted in the future.