The Research Of Association Rule Mining In Book Circulation Data And Its Application

For remedying the deficiency of data analysis ability in the existing library automated system, this paper introduces the data mining technology into the library personalized service system, the corresponding theories and applications are researched. Using the association rules technology in data minining and the Apriori algorithm, some valuable rules are discovered in the Anhui Province library borrowing database, and some meaningful information are given for the services for the readers of the library. And one kind of new book-recommending-model is proposed.The main content contains:(1) Using the method of data cleaning, data compressing and data returning in preprocessing of the books circulation data, we get further apprehending about the data preprocessing technology;(2)Via the connecting excavation of the readers'circulation data, the connection rule of various ages, occupations, educational levels and titles of readers are found, and one model of readers'interest is given;(3)Improve the APRIORI algorithm in the data minining process, produce two items of frequent items of collections, prune each candidate item of collection and produce the K frequent items of collection via the association rules;(4)According to the interest, further analyzes of the excavated connection rule are given, such as the positive association rules, the negative association rules, and the validity of the interest;(5)The mining tool for the readers' borrowing is designed based on the Apriori algorithm, the data' preprocessing based on the data compression technology and the associative rule's mining based on the Apriori algorithm are realized. Using this tool, we can analyse the readers' interest, hence provide the instruction for the individual services for the library's reader.