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

標題:Incrementally Mining Temporal Patterns in Interval-based Databases
學年103
學期1
發表日期2014/10/30
作品名稱Incrementally Mining Temporal Patterns in Interval-based Databases
作品名稱(其他語言)
著者Chen, Yi-Cheng; Weng, Julia Tzu-Ya; Wang, Jun-Zhe; Chou, Chien-Li; Huang, Jiun-Long; Lee, Suh-Yin
作品所屬單位資訊工程學系暨研究所
出版者IEEE
會議名稱The 2014 International Conference on Data Science and Advanced Analytics (DSAA 2014)
會議地點Shanhai, China
摘要In several applications, sequence databases generally update incrementally with time. Obviously, it is impractical and inefficient to re-mine sequential patterns from scratch every time a number of new sequences are added into the database. Some recent studies have focused on mining sequential patterns in an incremental manner; however, most of them only considered patterns extracted from time point-based data. In this paper, we proposed an efficient algorithm, Inc_TPMiner, to incrementally mine sequential patterns from interval-based data. We also employ some optimization techniques to reduce the search space effectively. The experimental results indicate that Inc_TPMiner is efficient in execution time and possesses scalability. Finally, we show the practicability of incremental mining of interval-based sequential patterns on real datasets.
關鍵字dynamic representation; incremental mining; interval-based pattern; sequential pattern mining
語言英文(美國)
收錄於
會議性質國際
校內研討會地點
研討會時間20141030~20141101
通訊作者Chen, Yi-Cheng
國別中國
公開徵稿Y
出版型式電子版
出處The 2014 International Conference on Data Science and Advanced Analytics
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