Using Group Cluster Association Rule for Retail Industrial Application

• Main Authors: Hsiao-Chuan Lin, 林小絹
• Other Authors: Chung-Min Wu
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/60773312204717086643

碩士 === 國立臺北科技大學 === 商業自動化與管理研究所 === 92 === In nowadays, when information technology and Database know-how is getting popularizing, the situation we faces is a lack of the knowledge instead of data overwhelming. Due to the traditional statistics argumentation bases on the limited assumption and nun big questions, it’s quietly difficult to deal with the mass and complicated data. The technology of Data Mining comes out from the artificial intelligence and database technology developing. Data Mining names Knowledge Discovery in Database (KDD),it abstracts and re-analyze the useful and reliable knowledge from the implied and unclear data. Also, it’s more reality than the study based on the narrow hypothesis. Association Rules is the hottest technology in data mining. the big matter in digging data is efficiency. For the developing of internet and database application, most study is limited by the ram and process time. According to this, the study based on the retail’s trading data applies the association rule and develops the Group Clustering Association Rule. With basic computer hardware and software, we create the association rule information application system for enterprise and present the result from the rule to affirm the study.