教師資料查詢 | 類別: 期刊論文 | 教師: 廖述賢 LIAO SHU-HSIEN (瀏覽個人網頁)

標題:A rough set-based association rule approach implemented on a brand trust evaluation model
學年105
學期1
出版(發表)日期2016/12/26
作品名稱A rough set-based association rule approach implemented on a brand trust evaluation model
作品名稱(其他語言)
著者Shu-Hsien Liao; Yin-Ju Chen
單位
出版者
著錄名稱、卷期、頁數Journal of Experimental & Theoretical Artificial Intelligence 29(4), p.911–927
摘要In commerce, businesses use branding to differentiate their product and service offerings from those of their competitors. The brand incorporates a set of product or service features that are associated with that particular brand name and identifies the product/service segmentation in the market. This study proposes a new data mining approach, a rough set-based association rule induction, implemented on a brand trust evaluation model. In addition, it presents as one way to deal with data uncertainty to analyse ratio scale data, while creating predictive if–then rules that generalise data values to the retail region. As such, this study uses the analysis of algorithms to find alcoholic beverages brand trust recall. Finally, discussions and conclusion are presented for further managerial implications.
關鍵字Data mining;rough set theory;association rule;ratio scale data processing;brand trust evaluation model
語言英文
ISSN0952-813X; 1362-3079
期刊性質國外
收錄於SCI;EI;
產學合作
通訊作者Shu-Hsien Liao
審稿制度
國別英國
公開徵稿
出版型式,電子版,紙本
相關連結
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