教師資料查詢 | 類別: 期刊論文 | 教師: 陳以錚 YI-CHENG CHEN (瀏覽個人網頁)

標題:Incremental mining of temporal patterns in interval-based database
學年103
學期2
出版(發表)日期2015/02/27
作品名稱Incremental mining of temporal patterns in interval-based database
作品名稱(其他語言)
著者Hui, Lin; Chen, Yi-Cheng; Weng, Julia Tzu-Ya; Lee, Suh-Yin
單位
出版者
著錄名稱、卷期、頁數Knowledge and Information Systems 46(2), pp.423-448
摘要In several real-life applications, sequence databases, in general, are updated incrementally with time. Some discovered sequential patterns may be invalidated and some new ones may be introduced by the evolution of the database. When a small set of sequences grow, or when some new sequences are added into the database, re-mining sequential patterns from scratch each time is usually inefficient and thus not feasible. Although there have been several recent studies on the maintenance of sequential patterns in an incremental manner, these works only consider the patterns extracted from time point-based data. Few research efforts have been elaborated on maintaining time interval-based sequential patterns, also called temporal patterns, where each datum persists for a period of time. In this paper, an efficient algorithm, Inc_TPMiner (Incremental Temporal Pattern Miner) is developed to incrementally discover temporal patterns from interval-based data. Moreover, the algorithm employs some optimization techniques to reduce the search space effectively. The experimental results on both synthetic and real datasets indicate that Inc_TPMiner significantly outperforms re-mining with static algorithms in execution time and possesses graceful scalability. Furthermore, we also apply Inc_TPMiner on a real dataset to show the practicability of incremental mining of temporal patterns.
關鍵字Incremental mining;Dynamic representation;Sequential pattern;Temporal pattern
語言英文
ISSN0219-1377;0219-3116
期刊性質國外
收錄於SCI;EI;
產學合作
通訊作者Hui, Lin
審稿制度
國別英國
公開徵稿
出版型式,電子版,紙本
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