Title
A novel approach for efficient updating approximations in dynamic ordered information systems.
Abstract
Dynamic data in real-time application are typically updating in a multi-dimensional manner. In this paper, we introduce a novel approach based on Dominance-based Rough Set Approach (DRSA) to efficiently deal with the multi-dimensional variations of attribute set and attribute values in dynamic Ordered Information Systems (OIS). We improve the original notion of the P-generalized decision domains to make the feature value matrix be dominance symmetrical, and propose an efficient strategy based on the improved notion to obtain the dominance feature matrix. Then, we employ the dominance-feature-matrix-based incremental strategy to avoid repeated comparisons between original attributes, so that to efficiently update rough approximations of DRSA with the simultaneously increased attribute set and varied attribute values. In our approach, the steps based on these two combined strategies can work altogether or separately, not only efficiently dealing with the simultaneously increased attribute set and varied attribute values, but also efficiently dealing with the individually increased attribute set or varied attribute values in dynamic OIS. Efficient algorithm based on the updating strategies is designed and multiple groups of experiments are conducted. Experimental results on different real-world data sets show that the proposed algorithm is much faster than other algorithms for dealing with the multi-dimensional or the single-dimensional variations of attribute set and attribute values.
Year
DOI
Venue
2020
10.1016/j.ins.2019.08.046
Information Sciences
Keywords
Field
DocType
Rough sets,Ordered information system,Dominance-based rough sets,Knowledge discovery
Information system,Incremental strategy,Data set,Matrix (mathematics),Algorithm,Approximations of π,Rough set,Dynamic data,Feature matrix,Artificial intelligence,Machine learning,Mathematics
Journal
Volume
ISSN
Citations 
507
0020-0255
4
PageRank 
References 
Authors
0.36
0
6
Name
Order
Citations
PageRank
Shu Wang140.36
Tianrui Li23176191.76
Chuan Luo3694.74
Jie Hu493.89
Hamido Fujita52644185.03
Tian-qiang Huang6335.74