A Study On Application Of Data Mining Technique In Library

With the development of information technology, libraries need to store and spread more and more large quantities of information, so the forms and types of information have become more and more abundant. Due to the various and extensive requirements of clients for information and documents data, the personalized information service has become a new development trend. The personalized service needs supports such as customer's interests, the association between books and information and etc., which can be collected from daily data analysis and data mining.The object of the study is the library's data, on the basis of analysis of which features the algorithms fit for the data mining– FP-growth algorithm and cluster algorithm are chosen and the FP-growth algorithm is improved. Take the library in Beijing forestry for example, this paper mines its reading requirement data and applies the association algorithm in the library to optimize the management of the bookshelves and stack, find the hidden association between the disciplines, instruct the readers'reading activities and supply the personalized service. The cluster algorithm is applied in the library to analyze the reader's lending rule and grasp and judge the books'quality. Both of applications get the positive information. At the same time, the paper proves the algorithm's validity and feasibility. In the end, the data mining information system in the library is designed and realized. The system will improve the quality and level of the personalized service in the library, and meet the reader's reading requirement.