Title :
A new method for mining maximal frequent itemsets
Author :
Nadimi-Shahraki, Mohammad ; Mustapha, Norwati ; Sulaiman, Md Nasir B. ; Mamat, Ali B.
Author_Institution :
Faculty of Computer Science and Information Technology, University of Putra Malaysia, 43400, Selangor, Malaysia
Abstract :
In this paper, we propose a new method for mining maximal frequent itemsets. Our method introduces an efficient database encoding technique, a novel tree structure called PC_Tree and also PC_Miner algorithm. The database encoding technique utilizes Prime number characteristics and transforms each transaction into a positive integer that has all properties of its items. The PC_Tree is a simple tree structure but yet powerful to capture whole of transactions by one database scan. The PC_Miner algorithm traverses the PC_Tree and builds the gcd (greatest common divisor) set of its nodes to mine maximal frequent itemsets. Experiments verify the efficiency and advantages of the proposed method.
Keywords :
Computer science; Data mining; Encoding; Information technology; Itemsets; Search methods; Transaction databases; Tree data structures;
Conference_Titel :
Information Technology, 2008. ITSim 2008. International Symposium on
Conference_Location :
Kuala Lumpur, Malaysia
Print_ISBN :
978-1-4244-2327-9
Electronic_ISBN :
978-1-4244-2328-6
DOI :
10.1109/ITSIM.2008.4631691