Mining Temporal Patterns in Time Interval-Based Data
學年 104
學期 2
發表日期 2016-05-16
作品名稱 Mining Temporal Patterns in Time Interval-Based Data
作品名稱（其他語言）
著者 Yi-Cheng Chen; Wen-Chih Peng; Suh-Yin Lee
作品所屬單位
出版者
會議名稱 The 32nd IEEE International Conference on Data Engineering (ICDE 2016)
會議地點 Helsinki, Finland
摘要 Sequential pattern mining is an important subfield in data mining. Recently, discovering patterns from interval events has attracted considerable efforts due to its widespread applications. However, due to the complex relation between two intervals, mining interval-based sequences efficiently is a challenging issue. In this paper, we develop a novel algorithm, P-TPMiner, to efficiently discover two types of interval-based sequential patterns. Some pruning techniques are proposed to further reduce the search space of the mining process. Experimental studies show that proposed algorithm is efficient and scalable. Furthermore, we apply proposed method to real datasets to demonstrate the practicability of discussed patterns.
關鍵字 data mining;interval-based event;representation;sequential pattern;temporal pattern
語言 en
收錄於
會議性質 國際
校內研討會地點 無
研討會時間 20160516~20160520
通訊作者
國別 FIN
公開徵稿
出版型式
出處 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 27(12), pp.3318-3331
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/107145 )