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江苏省仪征技师学院师生总计人数接近六千人,其中学生有三年中专层次与五年大专层次,不同专业和年级中男女比例也各有差异,所以图书馆的读者需求各式各样。不同的读者对图书馆的图书利用各不相同,通过对读者借阅行为进行聚类分析,可以将数量众多的读者进行相似分类,从而针对每一类的读者提供有针对性的个性化服务。本文通过k-means算法,挖掘分析了不同的专业及性别对借阅图书的影响,在图书配置上为决策者提供更好的建议,从而达到为不同
The total number of teachers and students in Yizheng Technician College of Jiangsu Province is nearly 6,000, of which there are three years of secondary school and five years of junior college level. There are also differences between male and female in different majors and grades. Therefore, there are various needs for library readers. Different readers make different use of library books, and through the cluster analysis of readers’ borrowing behavior, a large number of readers can be similarly classified to provide targeted personalized service for each type of readers. This paper analyzes the influence of different professions and gender on lending books through the k-means algorithm, and provides better advice to decision-makers in the book configuration so as to achieve different