期刊論文
| 學年 | 98 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2010-01-01 |
| 作品名稱 | Rough-Set-Based Association Rules Applied to Brand Trust Evaluation Model |
| 作品名稱（其他語言） | |
| 著者 | Liao, Shu-hsien; Lin, Hwei-jen |
| 單位 | 淡江大學經營決策學系 |
| 出版者 | Heidelberg: Springer |
| 著錄名稱、卷期、頁數 | Lecture Notes in Computer Science 6443, p.634-641 |
| 摘要 | The Internet has emerged as the primary database, and technological platform for electronic business (EB), including the emergence of online retail concerns. Knowledge collection, verification, distribution, storage, and re-use are all essential elements in retail. They are required for decision-making or problem solving by expert consultants, as well as for the accumulation of customers and market knowledge for use by managers in their attempts to increase sales. Previous data mining algorithms usually assumed that input data was precise and clean, this assumes would be eliminated if the best rule for each particular situation. The Algorithm we used in this study however, proved to function even when the input data was vague and unclean. We provided an assessment model of brand trust as an example, to show that the algorithm was able to provide decision makers additional reliable information, in the hope of building a rough set theoretical model and base of resources that would better suit user demand. |
| 關鍵字 | Machine Learning;Knowledge Representation;Knowledge-Based Systems;Rough sets; Association rules |
| 語言 | en |
| ISSN | 1611-3349 |
| 期刊性質 | 國外 |
| 收錄於 | EI |
| 產學合作 | |
| 通訊作者 | Liao Shu-Hsien; Chen Yin-Ju; Chu, Pei-Hui |
| 審稿制度 | 否 |
| 國別 | DEU |
| 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/987654321/65018 ) |