Tolerance approximation spaces
Fundamenta Informaticae - Special issue: rough sets
Knowledge discovery by application of rough set models
Rough set methods and applications
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Relational Data Mining
Rough-Neuro-Computing: Techniques for Computing with Words
Rough-Neuro-Computing: Techniques for Computing with Words
Knowledge Discovery in Inductive Databases: 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers (Lecture Notes in Computer Science)
Calculi of Approximation Spaces
Fundamenta Informaticae - SPECIAL ISSUE ON CONCURRENCY SPECIFICATION AND PROGRAMMING (CS&P 2005) Ruciane-Nide, Poland, 28-30 September 2005
Learning First-Order Rules: A Rough Set Approach
Fundamenta Informaticae - International Conference on Soft Computing and Distributed Processing (SCDP'2002)
Minimal Description and Maximal Description in Covering-based Rough Sets
Fundamenta Informaticae
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In this paper, we show that approximation spaces are basic structures for knowledge discovery from multi-relational data. The utility of approximation spaces as fundamental objects constructed for concept approximation is emphasized. Examples of basic concepts are given throughout this paper to illustrate how approximation spaces can be beneficially used in many settings.