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
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;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.488