Abstract
With the diversification of readers’ preferences, the continuous growth of book price and the shortage fund for purchasing books, it becomes increasingly important to explore reads’ real needs and spend limited money on those needed books. In this context, Chinese Word Segmentation technology combined with Chinese Library Classification are used to explore readers’ reading preferences by using news, management and finance disciplines’ borrowing data of Jinan University in the year of 2015. Results showed that readers showed remarkable preferences for books of a specific subcategory or theme. Meanwhile the hot borrowed books often gathered in a few core publishing house, with the core publishing house books accounting for 70%, 63% and 76% of the total sampling books for news, management and finance discipline respectively. All in all, this research is of great significance for the book procurement job of the high school library.
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