28th Annual International Computer Software and Applications Conference (COMPSAC'04)
Efficient Partial Multiple Periodic Patterns Mining without Redundant Rules
Hong Kong
September 28-September 30
ISBN: 0-7695-2209-2
Partial periodic patterns mining is a very interesting domain in data mining problem. In the previous studies, full and partial multiple periodic patterns mining problems are considered. The proposed methods, however, may produce redundant information and are inefficient. In this paper, a novel concept and new parameters are proposed to improve the performance of partial multiple periodic patterns mining. Instead of considering the whole database, the information needed for mining partial periodic patterns is transformed into a bit vector which can be stored in a main memory. A set of simulations is also performed to show the benefit of our approach.
Index Terms:
Data Mining, Partial periodicity, Cyclic patterns, Time series analysis
Citation:
Wenpo Yang, Guanling Lee, "Efficient Partial Multiple Periodic Patterns Mining without Redundant Rules," compsac, vol. 1, pp.430-435, 28th Annual International Computer Software and Applications Conference (COMPSAC'04), 2004