DocumentCode
2864217
Title
An Evolutionary Mining Model in Incremental Data Mining
Author
Jiancong, Fan ; Yongquan, Liang ; Jiuhong, Ruan
Author_Institution
Dept. of Comput. Sci. & Technol., Shandong Univ. of Sci. & Technol., Qingdao, China
Volume
3
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
114
Lastpage
118
Abstract
Incremental data mining is very important to solve the temporal dynamic property of knowledge, improve the performance of mining processes and efficiency of mining results. Incremental data occurs with the passage of time. Evolutionary methods can be adopted to solve such increment. A multiply evolutionary model is built to describe incremental data evolutionary mining processes. Copy operator, cross operator and mutation operator are designed. A general algorithm for dynamic evolutionary mining is also presented. The experiments showed that the evolutionary incremental data mining method could solve the scalable problem of data mining better, and have high accuracy and good time performance.
Keywords
data mining; evolutionary computation; cross operator; dynamic evolutionary mining; incremental data mining; multiply evolutionary model; mutation operator; Association rules; Computer science; Data engineering; Data mining; Educational institutions; Evolution (biology); Information science; Iterative algorithms; Knowledge engineering; Space technology; data mining; evolutionary model; evolutionary strategy;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.488
Filename
5366247
Link To Document