| 標題：Discovering Time-Interval Sequential Patterns by a Pattern Growth Approach with Confidence Constraints |
|---|
| 學年 | 104 |
|---|
| 學期 | 2 |
|---|
| 發表日期 | 2016/05/14 |
|---|
| 作品名稱 | Discovering Time-Interval Sequential Patterns by a Pattern Growth Approach with Confidence Constraints |
|---|
| 作品名稱（其他語言） | |
|---|
| 著者 | Huan-Jyh Shyur; Chi-Chang Jou; Chi-Bin Cheng; Chih-Yu Yen |
|---|
| 作品所屬單位 | |
|---|
| 出版者 | |
|---|
| 會議名稱 | 2016 The first PAS-TKU Symposium on Operations Research and Quantitative Analysis |
|---|
| 會議地點 | 淡水, 新北市, 台灣 |
|---|
| 摘要 | Sequential pattern mining is to discover frequent sequential patterns in a sequence database. The technique is applied to fields such as web click-stream mining, failure forecast, and traffic analysis. Conventional sequential pattern mining approaches generally focus only the orders of items; however, the time interval between two consecutive events can be a more valuable information when the time of the occurrence of an event is concerned. This study extends the concept of the well-known pattern growth approach, PrefixSpan algorithm, to propose a novel sequential pattern mining approach for sequential patterns with time intervals. The current study suggests that the confidence of the occurrence of a pattern is also important other than the frequency (i.e. support) of the pattern. Thus, the proposed approach extracts a pattern by first satisfying a minimum confidence constraint, and then finds out the least time interval that satisfies the minimum support constraint. Experiments are conducted to evaluate the performance of the proposed approach. |
|---|
| 關鍵字 | Sequential pattern mining;Time-interval sequential patterns;Pattern growth;Confidence |
|---|
| 語言 | 英文 |
|---|
| 收錄於 | |
|---|
| 會議性質 | 國際 |
|---|
| 校內研討會地點 | 淡水校園 |
|---|
| 研討會時間 | 20160514~20160514 |
|---|
| 通訊作者 | |
|---|
| 國別 | 中華民國 |
|---|
| 公開徵稿 | |
|---|
| 出版型式 | |
|---|
| 出處 | 論文集 |
|---|
| 相關連結 | |
|---|
|
Google+ 推薦功能，讓全世界都能看到您的推薦！
