Title :
Discover relaxed periodicity in temporal databases
Author :
Changjie, Tang ; Zhonghua, Yu ; Tianqing, Zhang
Author_Institution :
Dept. of Comput., Sichuan Univ., Chengdu, China
Abstract :
The relaxed-periodicity pattern describes loose-cyclic behavior of objects while allowing uneven stretch or shrink on the time axis, limited noise, and inflation/deflation of attribute values. To discover relaxed-periodicity from temporal databases, we propose the concepts of attribute trend, trend inertia, peak-valley pattern, inertia algorithm with anti-noise ability as well as the peak-valley algorithm and show that the implementation prototype is efficient
Keywords :
database theory; temporal databases; anti-noise ability; attribute trend; attribute value deflation; attribute value inflation; inertia algorithm; limited noise; loose-cyclic object behavior; peak-valley pattern; relaxed periodicity discovery; relaxed-periodicity pattern; temporal databases; time axis; trend inertia; uneven shrink; uneven stretch; Association rules; Cities and towns; Data mining; Data models; Databases; Electrical capacitance tomography; Postal services; Prototypes; Read only memory; Search methods;
Conference_Titel :
Database Systems for Advanced Applications, 1999. Proceedings., 6th International Conference on
Conference_Location :
Hsinchu
Print_ISBN :
0-7695-0084-6
DOI :
10.1109/DASFAA.1999.765753
