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Abstract. We present a study on a rough set based approach for feature selection. Instead of using significance or support, Parameterized Average Support Heuristic (PASH) consider...
Abstract. We introduce a hybrid approach to magnetic resonance image segmentation using unsupervised clustering and the rules derived from approximate decision reducts. We utilize ...
The paper concerns failing queries in incomplete Distributed Autonomous Information Systems (DAIS) based on attributes which are hierarchical and which semantics at different site...
Zbigniew W. Ras, Agnieszka Dardzinska, Osman G&uum...
We discuss an ontological framework for approximation, i.e., to approximation of concepts and vague dependencies specified in a given ontology. The presented approach is based on ...
We discuss the problems of spatio-temporal reasoning in the context of hierarchical information maps and approximate reasoning networks (AR networks). Hierarchical information maps...
Abstract. We present a rough set approach to vague concept approximation within the adaptive learning framework. In particular, the role of extensions of approximation spaces in se...
Abstract. In this paper, we propose a logical framework for reasoning about uncertain belief fusion. The framework is a combination of multi-agent epistemic logic and possibilistic...
In this paper, the concept of a granulation order is proposed in an information system. The positive approximation of a set under a granulation order is defined. Some properties o...