Library Reader Habit Analysis Based on KMeans Clustering Algorithm
In recent years,the reading behavior of readers in university libraries has undergone signifi-cant changes. In order to deeply analyze these changes,the article uses the K-Means clustering analysis algorithm,taking Anhui Mechanical and Electrical Vocational and Technical College as an example,and uses mature clustering models in SPSS tools for multi angle analysis,so as to more intuitively interpret the needs and habits of the interpreter. And point out the future development direction of book resource services in vocational colleges. This analysis helps us design more effective information push services,op-timize library resource allocation,and improve reader satisfaction.
万方数据
维普
