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数据挖掘技术在图书馆中的应用研究

A Study on Application of Data Mining Technique in Library

【作者】 王路漫

【导师】 宋铁英; 齐建东;

【作者基本信息】 北京林业大学 , 管理科学与工程, 2008, 硕士

【摘要】 随着信息技术的发展,图书馆中需要存储和传播的信息量越来越大,信息的种类和形式越来越丰富。由于用户对信息和文献资料类型的需求越来越多样化、越来越广泛,因此个性化的信息服务成为了新的发展趋势。个性化服务需要用户的兴趣、图书间的关联等信息的支持,而这些信息能够通过对图书馆的日常业务数据分析和挖掘获得。本文以图书馆借阅数据为对象,在对其特点分析的基础上,选择适用于图书馆数据的挖掘算法——关联规则中的FP-growth算法和聚类算法,并对FP-growth算法进行了减化;以北京林业大学图书馆为例,对其借阅数据进行挖掘,应用关联规则算法在图书馆优化书架书库的管理、发现学科间的隐性关联、指导读者的借阅行为和提供个性化服务等方面,应用聚类算法在图书馆对读者借阅规律的分析和把握、馆藏图书质量判断等方面均获得了具有积极意义的信息。同时,也证明所采用的算法的有效性与可行性;最后,设计和实现了图书馆数据挖掘信息系统,该系统将提高图书馆个性化服务的质量和水平,更好地满足读者的借阅需求。

【Abstract】 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.

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