数据挖掘技术在图书馆流通日志信息挖掘中的应用
首发时间:2014-04-10
摘要:图书馆以现代化的方式提供服务的过程中产生了大量读者流通日志。数据挖掘作为一门新兴的多学科交叉的技术,就是专门用来解决"数据丰富但知识贫乏"的现象的。本文将图书馆的备份数据进行清洗、转换和筛选等预处理以建立本文所用的数据集市,并筛选出2011年工商管理系中五个专业的事务表。利用微软的SSAS数据挖掘产品对数据进行关联规则挖掘,并针对可视化挖掘结果对支持度、置信度和重要性等参数进行反复调整,整合出各专业高相关度图书推荐列表。希望通过"高相关度图书荐书架"服务能促进图书馆导读服务和图书采访工作的完善,以及馆员综合素质的提高。
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Application on Data Mining to Information Mining of the Library Circulation Logs
Abstract:The process of providing library services in the modern way has produced a large number of data from the readers' circulation logs. As a new technology of multidisciplinary cross, Data Mining is designed to solve the phenomenon of "data rich but poor knowledge". We preprocess the library backup data by doing the Data cleaning, converting and screening to establish the data mart used by this paper, and take five transaction tables which are screened out from the five specialties in 2011 the department of Business Administration. By using of SQL Server Analysis Service product in Microsoft we mine the data through the association rule algorithm, and finally integrate the high correlation book recommended list of different major by repeated adjustment to the parameters such as Support, Confidence, and Importance of the visual mining results. So we hope to improve the library reading service, the quality of the book acquisitioning work, and the comprehensive quality of librarians by means of the "high correlation book recommended shelf" service.
Keywords: Book recommendation Data mining Association rules High correlation
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No.4592282370116139****
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