摘要
Abstract
The library is one of the main components of higher education institutions,providing sufficient book resources for students to acquire knowledge.With the expansion of the construction scale of universi-ty libraries,the types and quantities of books also show a sharp increase trend,but the means of book clas-sification is still backward,unable to meet the needs of book classification management,so this paper pro-poses a research on automatic classification methods of university library books based on keyword extrac-tion model and reinforcement learning.Build a book text keyword extraction model,accurately extract book text keywords,and represent books based on this.Based on the number of occurrences of keywords in the book text,the weight coefficient of keywords in the book text is measured.Based on this,keywords are ar-ranged in descending order,retaining a fixed number of keywords to obtain the final representation result of the book text.Based on the theory of reinforcement learning,the automatic book classification program is developed,and the rules of book classification are determined.The final results of automatic book classi-fication can be obtained by executing the program.The experimental data shows that under different exper-imental group backgrounds,the maximum sensitivity of book classification obtained after the application of the proposed method is 96%,and the maximum geometric average of book classification is 92%,fully con-firming that the proposed method has better book classification performance.关键词
强化学习/高校图书馆/关键词提取模型/图书分类/相似度计算/图书管理Key words
reinforcement learning/university libraries/keywords extraction model/book classification/sim-ilarity calculation/library management分类
信息技术与安全科学
