Title :
Discovering frequent itemsets an improved algorithm of directed graph and array
Author :
Naili Liu ; Lei Ma
Author_Institution :
Dept. of Inf., Linyi Univ., Linyi, China
Abstract :
Mining association rules is an essential task for knowledge discovery. But discovering association rules based on graph need many times to traverse graph in generating candidate itemset. This paper proposes the improved algorithm, which constructs the directed graph and generate candidate item sets by using the directed neighbor nodes set, the algorithm need traverse the directed graph only once. The algorithm verifies whether a candidate itemset is a frequent itemset by logic AND operation. Experimental result shows that the improved algorithm has better efficiency than other algorithms based on graph.
Keywords :
data mining; directed graphs; array; association rule mining; candidate item sets; directed graph; directed neighbor nodes set; frequent itemset discovery; graph traversal; knowledge discovery; logic AND operation; Arrays; Computers; Itemsets; data mining; directed graph; directed neighbor node; frequent item sets; logic operation;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-4997-0
DOI :
10.1109/ICSESS.2013.6615479