期刊論文
| 學年 | 102 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2013-08-01 |
| 作品名稱 | A data mining approach to discovering reliable sequential patterns |
| 作品名稱（其他語言） | |
| 著者 | Shyur, Huan-Jyh; Jou, Chichang; Chang, Keng |
| 單位 | 淡江大學資訊管理學系 |
| 出版者 | New York: Elsevier Inc. |
| 著錄名稱、卷期、頁數 | The Journal of Systems and Software 86(8), pp.2196–2203 |
| 摘要 | Sequential pattern mining is a data mining method for obtaining frequent sequential patterns in a sequential database. Conventional sequence data mining methods could be divided into two categories: Apriori-like methods and pattern growth methods. In a sequential pattern, probability of time between two adjacent events could provide valuable information for decision-makers. As far as we know, there has been no methodology developed to extract this probability in the sequential pattern mining process. We extend the PrefixSpan algorithm and propose a new sequential pattern mining approach: P-PrefixSpan. Besides minimum support-count constraint, this approach imposes minimum time-probability constraint, so that fewer but more reliable patterns will be obtained. P-PrefixSpan is compared with PrefixSpan in terms of number of patterns obtained and execution efficiency. Our experimental results show that P-PrefixSpan is an efficient and scalable method for sequential pattern mining. |
| 關鍵字 | |
| 語言 | en_US |
| ISSN | 1873-1228 0164-1212 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | Shyur, Huan-Jyh |
| 審稿制度 | 是 |
| 國別 | USA |
| 公開徵稿 | |
| 出版型式 | 紙本,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/92477 ) |