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 en
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 TWN
公開徵稿
出版型式
出處 論文集
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/108703 )