Paper Info
Title
Attribute Core Computation Based on Divide and Conquer Method
Abstract
The idea of divide and conquer method is used in developing algorithms of rough set theory. In this paper, according to the partitions of equivalence relations on attributes of decision tables, two novel algorithms for computing attribute core based on divide and conquer method are proposed. Firstly, a new algorithm for computing the positive region of a decision table is proposed, and its time complexity is O(|U|×|C|), where, |U| is the size of the set of objects and Cis the size of the set of attributes. Secondly, a new algorithm for computing the attribute core of a decision table is developed, and its time complexity is O(|U|×|C|2). Both these two algorithms are linear with |U|. Simulation experiment results show that the algorithm of computing attribute core is not only efficient, but also adapt to huge data sets.
Year
DOI
Venue
2007
10.1007/978-3-540-73451-2_33
RSEISP
Keywords
Field
DocType
decision table,attribute core,conquer method,rough set theory,attribute core computation,positive region,equivalence relation,simulation experiment result,new algorithm,novel algorithm,huge data set,time complexity,simulation experiment,rough set,divide and conquer
Equivalence relation,Data set,Decision table,Algorithm,Rough set,Theoretical computer science,Divide and conquer algorithms,Akra–Bazzi method,Time complexity,Mathematics,Attribute domain
Conference
Volume
ISSN
Citations 
4585
0302-9743
6
PageRank 
References 
Authors
0.75
7
3
Name
Order
Citations
PageRank
Feng Hu1485.33
Guoyin Wang22144202.16
Ying Xia3125.28