Title :
A mining algorithm based on time series association rules
Author :
Liping Liu ; Ninghai Cui
Author_Institution :
Coll. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China
Abstract :
Based on the concept lattice theory, this paper studies the cycle of association rule mining about the periodic fluctuations of time-series. First of all, do anti-season pretreatment to time-series, then give the algorithm of the generation of the cycle of association rules, and the pruning to the generated concept within algorithm improve the efficiency of the mining speed. And then we can use the given higher precision model to do anti-season changes calculation to those time series which dissatisfy anti-season pretreatment using the moving average method.
Keywords :
data mining; time series; antiseason changes calculation; antiseason pretreatment; association rule mining cycle generation; concept lattice theory; mining algorithm; moving average method; periodic fluctuation time series; precision model; time series association rules; Association rules; Data models; Fluctuations; Lattices; Predictive models; Time series analysis; association rules; data mining; formal concept analysis; time-series;
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4577-1414-6
DOI :
10.1109/CECNet.2012.6201827
