| 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。 |
| 关键词: Apriori算法；数据挖掘；FP-Growth算法；关联规则；游戏销售 |
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中图分类号: TP391
文献标识码: A
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| Research and Application of Mining Association Rules in Game Sales |
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YAN Dongming,CHEN Zhanfang,JIANG Xiaoming
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( School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China)
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| Abstract: 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. |
| Keywords: Apriori algorithm;data mining;FP-Growth algorithm;association rules;game sale |
