The Application Of Association Rule In Library

As the rapid development of information and network technology, the library needs to store an increasing amount of information, which has more types and forms. Demands of information and documentation become more complicated. To do a better library administration and provide readers with better service, we need to develop personalized information services. Personalized service requires the support of information on users' interest and linkages between books, which can be gotten from the library's daily operations data by analysis and mining.This paper describes the history and development of data mining technology, domestic and international research status, and analyzes the feasibility and the future of applying data mining technology in library. We take Zaozhuang College Library as an example, and basing on its loan data, apply association rules algorithm to following application aspects, library optimal collection management, discovering hidden connection between subjects, guiding the reader's borrowing behavior and providing personalized services.This article has the following points.(1) Investigate the work of circulation department and consulting department in the library through the author's job. Contact with readers, to collect their demands and thoughts.(2) Research and compare different data mining algorithms, to select the appropriate library data processing algorithms.(3) Give a detailed study of our library books database management systems, and collate the relevant data filtering.(4) Analyze the association rules in the Apriori algorithm and FP-growth algorithm, and use them to mine lending data. Analyze the results and obtain the information needed to optimize collection and realize personalized recommendation services.(5) Using c# programming, design and realize a data mining system for the library information, which can improve library's personalized service to meet the demands of readers.