闭合项目集格空间理论在期刊销售中的应用  

The Application of the Lattice of Closed Item Sets Theory in the Periodical Market

作　　者：林钢[1] 崔洁[2] 

机构地区：[1]无锡商业职业技术学院,江苏无锡214063 [2]泰州职业技术学院,江苏泰州225300

出　　处：《泰州职业技术学院学报》2005年第6期1-3,共3页Journal of Taizhou Polytechnic College

摘　　要：数据挖掘是一种在繁多无序单个数据中寻找出有用信息的一个过程,通过数据之间的联系来解释现在和预测未来。随着数据库容量的不断增大,持续重复地访问数据库势必将导致效率和性能的低下,因此探求出一种新的理论方法来减少对数据库的扫描次数已成为近年来国内外的研究热点之一。闭合项目集格空间理论突破了Apriori算法逐层生成k-频繁集和裁减项目集空间的模式,利用新的理论生成新的算法,寻求期刊销售中的潜在规律,从而有效地提高销售量。Data mining is the process of finding useful information in many disordered and individual data. The purpose of data mining is to use discovered relationships to explain the current or to predict the future. With the enlarging size of database, the continuous visiting to it is sure to bring down the effectiveness, so to work out a new theoretical methodology to reduce the times of scanning is becoming a hot researching spot in no matter civil or abroad. The lattice of closed item sets theory has broken the mode of forming the k frequent item sets one by one, instead, utilizing a new theory to bring out a new algorithm. The article tends to utilize a new theory to solve the problem happened in the book market so as to improve to situation.

关 键 词：数据挖掘 close算法 项目集 项目序列集 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]