Sequential pattern mining is one of the important techniques of data mining to discover some potential useful knowledge from large databases. However, existing approaches for mining sequential patterns are designed for point-based events. In many applications, the essence of events are interval-based, such as disease suffered, stock price increase or decrease, chatting etc. This paper presents a new algorithm to discover temporal pattern from temporal sequences database consisting of interval-based events.
|主出版物標題||Fuzzy Systems and Knowledge Discovery - Third International Conference, FSKD 2006, Proceedings|
|出版狀態||已出版 - 2006|
|事件||3rd International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2006 - Xi'an, China|
持續時間: 24 9月 2006 → 28 9月 2006
|名字||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|???event.eventtypes.event.conference???||3rd International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2006|
|期間||24/09/06 → 28/09/06|