Mining Customer Knowledge for a Recommendation System in Convenience Stores
學年 102
學期 2
出版（發表）日期 2014-06-01
作品名稱 Mining Customer Knowledge for a Recommendation System in Convenience Stores
作品名稱（其他語言）
著者 Liao, S. H.; Wen, C. H.; Hsiao, P.Y.; Li, C. W.; Hsu, C. W.
單位 淡江大學管理科學學系
出版者 Hershey: I G I Global
著錄名稱、卷期、頁數 International Journal of Data Warehousing and Mining 10(2), pp.55-86
摘要 Taiwan's rapid economic growth with increasing personal income leads increasing numbers of young unmarried people to eat out, and shopping at convenience stores for food is indispensable to the lives of these people. Thus, it is an essential issue for convenience store owners to know how to accurately market appropriate products and to choose effective endorsers for brands or products in order to attract target consumers. Data mining is a business intelligence analysis approach with great potential to help businesses focus on the most important business information contained in a database. Therefore, this study uses the Apriori algorithm as an association rules approach, and clustering analysis for data mining. The authors divide consumers into three groups by their consumer profiles and then find each group's product preference mixes, product endorsers, and product/brand line extensions for new product development. These are developed as a recommendation system for 7-11 convenience stores in Taiwan.
關鍵字
語言 en_US
ISSN 1548-3924
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/99933 )

機構典藏連結
SDGS 產業創新與基礎設施