期刊論文

學年 100
學期 2
出版(發表)日期 2012-02-15
作品名稱 Mining customer knowledge for exploring online group buying behavior
作品名稱(其他語言)
著者 Liao, Shu-hsien; Chu, Pei-hui; Chen, Yin-ju; Chang, Chia-Chen
單位 淡江大學管理科學學系
出版者 Kidlington: Pergamon Press
著錄名稱、卷期、頁數 Expert Systems with Applications 39(3), pp.3708-3716
摘要 Online group buying is an effective marketing method. By using online group buying, customers get unbelievable discounts on premium products and services. This not only meets customer demand, but also helps sellers to find new ways to sell products sales and open up new business models, all parties benefit in these transactions. During these bleak economic times, group buying has become extremely popular. Therefore, this study proposes a data mining approach for exploring online group buying behavior in Taiwan. Thus, this study uses the Apriori algorithm as an association rules approach, and clustering analysis for data mining, which is implemented for mining customer knowledge among online group buying customers in Taiwan. The results of knowledge extraction from data mining are illustrated as knowledge patterns, rules, and knowledge maps in order to propose suggestions and solutions to online group buying firms for future development.
關鍵字 Data mining; Association rules; Cluster analysis; Online group buying; Online group buying behavior
語言 en_US
ISSN 0957-4174
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Liao, Shu-hsien
審稿制度
國別 GBR
公開徵稿
出版型式 紙本
相關連結

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