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題名 | Discovering Time-Interval Sequential Patterns by a Pattern Growth Approach with Confidence Constraints=利用考量信賴度限制的樣式成長方法發掘具時間間隔循序特徵樣式 |
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作者 | 徐煥智; 周清江; 鄭啓斌; 顏志祐; Shyur, Huan-jyh; Jou, Chichang; Cheng, Chi-bin; Yen, Chih-yu; |
期刊 | International Journal of Information and Management Sciences |
出版日期 | 20160600 |
卷期 | 27:2 2016.06[民105.06] |
頁次 | 頁a9+129-145 |
分類號 | 028.7 |
語文 | eng |
關鍵詞 | 循序樣式探勘; 時間區間循序式; 樣式成長; 信賴度; Sequential pattern mining; Time-interval sequential patterns; Pattern growth; Confidence; |
英文摘要 | 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 traf- fic analysis. Conventional sequential pattern-mining approaches generally focus only the orders of items; however, the time interval between two consecutive events can be a 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. Unlike the other time-interval sequential pattern-mining algorithms, the approach concerns the time for the next event to occur more than the timing information with its precedent events. To obtain a more reliable sequential pattern, a new measure of the confidence of a sequential pattern is defined. Experiments are conducted to evaluate the performance of the proposed approach. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。