Title :
A frequent itemsets mining algorithm based on spatial partition
Author :
Liu, Tieying ; Chen, Lirong ; Wang, Guoguang
Author_Institution :
Coll. of Comput. Sci., Inner Mongolia Univ., Hohhot, China
Abstract :
Established a complete lattices description for the problem of mining association rules, gave the lower limit of the problem scale, and put forward a spatial partition search based itemsets frequency calculation model. Based on the improved FP-tree, gave a frequent itemset mining algorithm UPM (upward partition mine) and proved that its complexity has achieved the minimum size of the problem. Performance experiments show that, compared with FP-Growth algorithm, UPM has an excellent performance in space and time.
Keywords :
data mining; search problems; association rule mining; frequent itemsets mining algorithm; spatial partition search calculation model; upward partition mine; Association rules; Computer science; Data mining; Educational institutions; Frequency; Itemsets; Lattices; Partitioning algorithms; Software algorithms; Transaction databases; association rules mining; complete lattices; frequent itemsets;
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
DOI :
10.1109/ICCSIT.2009.5234411
