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Incremental learning is an efficient technique for knowledge discovery in a dynamic database, which enables acquiring additional knowledge from new data without forgetting prior knowledge. Rough set theory has been successfully used in information systems for classification analysis. Set-valued information systems are generalized models of single-valued information systems, which can be classified...
The description of an information system will be more accurate when objects and attributes are added to it. The approximations of a concept may change when an information system varies. No research work has been done yet on incremental updating for approximations when objects and attributes change simultaneously. In traditional rough set theory, granules are induced by equivalence classes. The granularity...
In real applications, information systems may vary with time due to different reasons. Approximations of a concept under variable precision rough sets (VPRS) will change when an information system changes. Usually, incremental updating methods are an effective way to maintenance knowledge in a dynamic environment. Algorithms for incremental updating approximations are proposed in this paper when objects...
Set-valued information systems are a general model of single-valued information systems. Set-valued ordered information systems can be defined based on the inclusion relation between attribute values of objects. Firstly, a variable precision set-valued ordered rough set model is proposed in this paper by introducing the variable precision rough set method into set-valued ordered information systems...
Incrementally updating approximations in rough set theory may contribute to enhancement of the efficiency of knowledge discovery. This paper firstly introduces the definitions of attribute values' coarsening and refining in set-valued information systems. Then the approach for incrementally updating approximations of a concept is presented while attribute values coarsening and refining. Finally, an...
In rough set theory (RST), upper and lower approximations of a concept will change dynamically while the information system varies over time. How to update approximations based on the original approximations' information is an important problem since it may improve the efficiency of knowledge discovery. This paper focuses on the approach for dynamically updating approximations when attribute values...
Approximations of a concept in the variable precision rough set model will change when an information system varies with time. Usually, it is an effective method to carry out incremental updating approximations by using existing information in the dynamic environment. This paper focuses on the incremental updating principle of computing approximations while objects in information systems dynamically...
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