期刊論文
| 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 | 否 |
| 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 ) |