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Unifying Rough Set Analysis and Formal Concept Analysis Based on a Logic Approach to Granular Computing

Unifying Rough Set Analysis and Formal Concept Analysis Based on a Logic Approach to Granular Computing

Bing Zhou, Yiyu Yao
Copyright: © 2010 |Pages: 25
ISBN13: 9781605669021|ISBN10: 1605669024|ISBN13 Softcover: 9781616924140|EISBN13: 9781605669038
DOI: 10.4018/978-1-60566-902-1.ch017
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MLA

Zhou, Bing, and Yiyu Yao. "Unifying Rough Set Analysis and Formal Concept Analysis Based on a Logic Approach to Granular Computing." Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence, edited by Yingxu Wang, IGI Global, 2010, pp. 325-349. https://doi.org/10.4018/978-1-60566-902-1.ch017

APA

Zhou, B. & Yao, Y. (2010). Unifying Rough Set Analysis and Formal Concept Analysis Based on a Logic Approach to Granular Computing. In Y. Wang (Ed.), Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence (pp. 325-349). IGI Global. https://doi.org/10.4018/978-1-60566-902-1.ch017

Chicago

Zhou, Bing, and Yiyu Yao. "Unifying Rough Set Analysis and Formal Concept Analysis Based on a Logic Approach to Granular Computing." In Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence, edited by Yingxu Wang, 325-349. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-902-1.ch017

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Abstract

Granular computing is an emerging field of research that attempts to formalize and explore methods and heuristics for human problem solving with multiple levels of granularity and abstraction. A fundamental issue of granular computing is the construction, representation and utilization of granules and granular structures. Basic granules represent the basic pieces of knowledge. A granular structure reflects the connections between different pieces of knowledge. The main objective of this book chapter is to examine a logic approach to granular computing for combining rough set analysis and formal concept analysis. Following the classical interpretation of concepts that a concept consists of a pair of an extension and an intension, the authors interpret a granule as a pair containing a set of objects and a logic formula describing the granule. The building blocks of granular structures are basic granules representing elementary concepts or pieces of knowledge. They are treated as atomic formulas of a logic language. Different types of granular structures can be constructed by using logic connectives. Within this logic framework, this chapter shows that rough set analysis and formal concept analysis can be interpreted uniformly by using the proposed logic language. The two theories share high-level similarities, but differ in their choices of definable granules and granular structures. Algorithms and evaluation measures can be designed uniformly for both theories.

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