A rough set-based association rule approach for a recommendation system for online consumers
學年 105
學期 1
出版(發表)日期 2016-11-01
作品名稱 A rough set-based association rule approach for a recommendation system for online consumers
作品名稱(其他語言)
著者 Liao, Shu-hsien; ChangHsiao-ko
單位
出版者
著錄名稱、卷期、頁數 Information Processing & Management 52(6), p.1142–1160
摘要 Increasing use of the Internet gives consumers an evolving medium for the purchase of products and services and this use means that the determinants for online consumers’ purchasing behaviors are more important. Recommendation systems are decision aids that analyze a customer's prior online purchasing behavior and current product information to find matches for the customer's preferences. Some studies have also shown that sellers can use specifically designed techniques to alter consumer behavior. This study proposes a rough set based association rule approach for customer preference analysis that is developed from analytic hierarchy process (AHP) ordinal data scale processing. The proposed analysis approach generates rough set attribute functions, association rules and their modification mechanism. It also determines patterns and rules for e-commerce platforms and product category recommendations and it determines possible behavioral changes for online consumers.
關鍵字 Data mining;Rough set;Association rule;Rough set association rule;Analytic hierarchy process;Recommendation systems
語言 en
ISSN 0306-4573 1873-5371
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度
國別 GBR
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/107001 )