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  • 标题:Using Association Rule Mining for Extracting Product Sales Patterns in Retail Store Transactions
  • 本地全文:下载
  • 作者:Pramod Prasad ; Dr. Latesh Malik
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2011
  • 卷号:3
  • 期号:5
  • 页码:2177-2182
  • 出版社:Engg Journals Publications
  • 摘要:Computers and software play an integral part in the working of businesses and organisations. An immense amount of data is generated with the use of software. These large datasets need to be analysed for useful information that would benefit organisations, businesses and individuals by supporting decision making and providing valuable knowledge. Data mining is an approach that aids in fulfilling this requirement. Data mining is the process of applying mathematical, statistical and machine learning techniques on large quantities of data (such as a data warehouse) with the intention of uncovering hidden patterns, often previously unknown. Data mining involves three general approaches to extracting useful information from large data sets, namely, classification, clustering and association rule mining. This paper elaborates upon the use of association rule mining in extracting patterns that occur frequently within a dataset and showcases the implementation of the Apriori algorithm in mining association rules from a dataset containing sales transactions of a retail store.
  • 关键词:data mining; association rules; apriori algorithm
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