A rough set approach to attribute generalization in data mining
Information Sciences: an International Journal
Dominance-based rough set approach and knowledge reductions in incomplete ordered information system
Information Sciences: an International Journal
Stochastic dominance-based rough set model for ordinal classification
Information Sciences: an International Journal
Credible rules in incomplete decision system based on descriptors
Knowledge-Based Systems
An Incremental Approach for Inducing Knowledge from Dynamic Information Systems
Fundamenta Informaticae - Fundamentals of Knowledge Technology
Dominance-based rough set approach to incomplete interval-valued information system
Data & Knowledge Engineering
Variable-precision dominance-based rough set approach and attribute reduction
International Journal of Approximate Reasoning
A study of using RST to create the supplier selection model and decision-making rules
Expert Systems with Applications: An International Journal
International Journal of Intelligent Systems
A labeled-tree approach to semantic and structural data interoperability applied in hydrology domain
Information Sciences: an International Journal
The incremental method for fast computing the rough fuzzy approximations
Data & Knowledge Engineering
Experiments with rough set approach to face recognition
International Journal of Intelligent Systems
Incremental learning optimization on knowledge discovery in dynamic business intelligent systems
Journal of Global Optimization
Inductive discovery of laws using monotonic rules
Engineering Applications of Artificial Intelligence
Incremental attribute reduction based on elementary sets
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Incremental versus non-incremental rule induction for multicriteria classification
Transactions on Rough Sets II
International Journal of Approximate Reasoning
Neighborhood rough sets for dynamic data mining
International Journal of Intelligent Systems
Multisensor data fusion: A review of the state-of-the-art
Information Fusion
Composite rough sets for dynamic data mining
Information Sciences: an International Journal
Information Sciences: an International Journal
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Dominance-based Rough Sets Approach (DRSA) is a generalized model of the classical Rough Sets Theory (RST) which may handle information with preference-ordered attribute domain. The attribute set in the information system may evolve over time. Approximations of DRSA used to induce decision rules need updating for knowledge discovery and other related tasks. We firstly introduce a kind of dominance matrix to calculate P-dominating sets and P-dominated sets in DRSA. Then we discuss the principles of updating P-dominating sets and P-dominated sets when some attributes are added into or deleted from the attribute set P. Furthermore, we propose incremental approaches and algorithms for updating approximations in DRSA. The proposed incremental approaches effectively reduce the computational time in comparison with the non-incremental approach are validated by experimental evaluations on different data sets from UCI.