关联规则挖掘在游戏视频销售中的研究与应用  

Research and Application of Mining Association Rules in Game Sales

作　　者：闫东明 陈占芳[1] 姜晓明[1] YAN Dongming;CHEN Zhanfang;JIANG Xiaoming(School of Computer Science and Technology,Changchun University of Science and Technology,Changchun 130022,China)

机构地区：[1]长春理工大学计算机科学技术学院,吉林长春130022

出　　处：《软件工程》2018年第3期20-22,19,共4页Software Engineering

摘　　要：数据挖掘是一项热门技术,该技术融合了数据库、统计学等领域知识,关联规则的挖掘则能找出商品销售中商品之间的联系。本文针对Apriori算法,及其改进算法FP-Growth进行了研究,对比了Apriori算法与FPGrowth算法的效率,得出FP-Growth算法由于只需要对数据进行一次扫描即可生成相应的数据集,使其生成数据集的整体效率要高于Apriori算法。Data mining is a hot technology which comprises database,artificial intelligence,statistics,etc.The mining association rules can find out the relations among the selling commodities.This paper studies Apriori algorithm and its improved algorithm,FP-Growth,and compares the efficiency of them,where it is found that corresponding data set can be generated after only one data scanning based on FP-Growth algorithm,leading to higher overall efficiency of the generated data set than that of Apriori algorithm.

关 键 词：APRIORI算法 数据挖掘 FP-GROWTH算法 关联规则 游戏销售 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]