Title :
Adaptive AFOPT algorithm
Author :
Györödi, Cornelia ; Györödi, Robert ; Pater, Mirela ; Boc, Ovidiu ; David, Zoltan
Author_Institution :
Dept. of Comput. Sci., Oradea Univ., Romania
Abstract :
Mining frequent patterns is a fundamental part of data mining. Most of the previous studies adopt an a priori-like candidate set generation-and-test approach. The a priori is the first algorithm which uses the a priori property to prune the search space. In this paper the AFOPT algorithm is adapted for mining at different levels by using different support. Furthermore, the efficiency of this algorithm is being shown by comparing it to similar algorithms.
Keywords :
data mining; pattern classification; tree searching; a priori property; adaptive AFOPT algorithm; data mining; search space; Computer science; Costs; Data mining; Databases; Frequency; Informatics; Itemsets; Iterative algorithms; Test pattern generators; Testing;
Conference_Titel :
Symbolic and Numeric Algorithms for Scientific Computing, 2005. SYNASC 2005. Seventh International Symposium on
Print_ISBN :
0-7695-2453-2
DOI :
10.1109/SYNASC.2005.17
