Based University Library Management Of Data Mining Algorithms Application

In recent years,with the development of China's information and the improvement of science and technology,more and more industry has opened up the information management system.The information technology of university library has benefited from the progress of science and technology,and has been rapid development.But at the same time,it also exposes many problems,such as low utilization rate of library literature resources,insufficient collection resources,low service level,little amount of readers'reading.In order to provide technical support for the construction of library information management system,it has become an urgent problem to be solved for the construction of library information management system.Data mining technology is a new hot spot in data processing,which plays a very important role in the data information.At present,the data information is simply stored in the library management system,there is no in-depth analysis and research.In the face of a large number of books and literature resources to borrow data information,the need for a thorough study of these data,analysis,the value of the law of the tool,in order to better guide the work of the library.The application of data mining technology in university library management system,to create a library management system based on data mining technology,through the identification and analysis of historical data information in the course of the book,to find out the value of the library management,to find out the reasons for the library management,to stimulate students' reading interest,improve the library collection resource utilization,provide scientific basis for different readers,and provide decision-making basis for the library.In the present library management system of Dalian science and Technology Institute,the paper takes the historical data information as the research object,and applies the data mining technology to the work of the library information.Specific methods for:1.Improved K-means mining algorithm,the use of clustering method to achieve the reader's clustering analysis,to understand the relevant readers of the book literature resource utilization,according to the results of the clustering analysis to guide the library management and different professional grade readers to provide active personalized service.2.Improved Apriori algorithm,the use of association rules to analyze the reader to borrow information,to help the library administrator for readers to borrow and to carry out personalized services,guide readers to borrow books and other work.