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IMTAR: Incremental Mining of General Temporal Association Rules
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  • IMTAR: Incremental Mining of General Temporal Association Rules
  • IMTAR: Incremental Mining of General Temporal Association Rules
저자명
Dafa-Alla. Anour F.A.,Shon. Ho-Sun,Saeed. Khalid E.K.,Piao. Minghao,Yun. Un-Il,Cheoi. Kyung-Joo,Ryu. Keun-Ho
간행물명
Journal of information processing systems
권/호정보
2010년|6권 2호|pp.163-176 (14 pages)
발행정보
한국정보처리학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Nowadays due to the rapid advances in the field of information systems, transactional databases are being updated regularly and/or periodically. The knowledge discovered from these databases has to be maintained, and an incremental updating technique needs to be developed for maintaining the discovered association rules from these databases. The concept of Temporal Association Rules has been introduced to solve the problem of handling time series by including time expressions into association rules. In this paper we introduce a novel algorithm for Incremental Mining of General Temporal Association Rules (IMTAR) using an extended TFP-tree. The main benefits introduced by our algorithm are that it offers significant advantages in terms of storage and running time and it can handle the problem of mining general temporal association rules in incremental databases by building TFP-trees incrementally. It can be utilized and applied to real life application domains. We demonstrate our algorithm and its advantages in this paper.