期刊論文
| 學年 | 98 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2009-11-01 |
| 作品名稱 | The Cyclic Model Analysis on Sequential Patterns |
| 作品名稱（其他語言） | |
| 著者 | Chiang, Ding-An; Wang, Cheng-Tzu; Chen, Shao-Ping; Chen, Chun-Chi |
| 單位 | 淡江大學資訊工程學系 |
| 出版者 | Piscataway: Institute of Electrical and Electronics Engineers |
| 著錄名稱、卷期、頁數 | Knowledge and Data Engineering, IEEE Transactions on 21(11), pp.1617-1628 |
| 摘要 | Sequential pattern mining has been used to predict various aspects of customer buying behavior for a long time. Discovered sequence reveals the chronological relation between items and provides valuable information to aid in developing marketing strategies. Nevertheless, we can hardly know whether the buying is cyclic and how long the interval between the two consecutive items in the sequential pattern is. To solve this problem, in this paper, data mining skills and the fundamentals of statistics are combined to develop a set of algorithms to unearth the cyclic properties of discovered sequential patterns. The algorithms, coupled with the sequential pattern mining process, constitute a thorough scheme to analyze and predict likely consumer behavior. The proposed algorithms are implemented and applied to test against real data collected from a consumer goods company. The experimental results illustrate how the model can be used to predict likely purchases within a certain time frame. Consequently, marketing professionals can execute campaigns to favorably impact customers' behaviors. |
| 關鍵字 | Association rules; data mining; frequency; sequential pattern; polynomial regression |
| 語言 | en |
| ISSN | 1041-4347 |
| 期刊性質 | 國外 |
| 收錄於 | SCI EI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | |
| 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/987654321/90596 ) |