In past years ,people were hardly aware of Mapping Knowledge between Environments when dealing with problems,did not consider the ability of their constraint and introduction to handle cognition problem under incomple...In past years ,people were hardly aware of Mapping Knowledge between Environments when dealing with problems,did not consider the ability of their constraint and introduction to handle cognition problem under incomplete information environment. This paper firstly points out the importance of explicit representation on background knowledge,then gives a method that deals with imprecise infor mation aggregation using generalized rough set theory. This process involves representation and acquiring about background knowledge.展开更多
In order to reduce knowledge reasoning space and improve knowledge processing efficiency, a framework of distributed attribute reduction in concept lattices is presented. By employing the idea similar to that of the r...In order to reduce knowledge reasoning space and improve knowledge processing efficiency, a framework of distributed attribute reduction in concept lattices is presented. By employing the idea similar to that of the rough set, the characterization of core attributes, dispensable attributes and unnecessary attributes are described from the point of view of local formal contexts and virtual global contexts. A determinant theorem of attribute reduction is derived. Based on these results, an approach for distributed attribute reduction is presented. It first performs reduction independently on each local context using the existing approaches, and then local reducts are merged to compute reducts of global contexts. An algorithm implementation is provided and its effectiveness is validated. The distributed reduction algorithm facilitates not only improving computation efficiency but also avoiding the problems caused by the existing approaches, such as data privacy and communication overhead.展开更多
文摘In past years ,people were hardly aware of Mapping Knowledge between Environments when dealing with problems,did not consider the ability of their constraint and introduction to handle cognition problem under incomplete information environment. This paper firstly points out the importance of explicit representation on background knowledge,then gives a method that deals with imprecise infor mation aggregation using generalized rough set theory. This process involves representation and acquiring about background knowledge.
基金The National Outstanding Young Scientist Foundationby NSFC(No.60425206)the National Natural Science Foundation of Chi-na(No.60503020)the Natural Science Foundation of Jiangsu Province(No.BK2006094).
文摘In order to reduce knowledge reasoning space and improve knowledge processing efficiency, a framework of distributed attribute reduction in concept lattices is presented. By employing the idea similar to that of the rough set, the characterization of core attributes, dispensable attributes and unnecessary attributes are described from the point of view of local formal contexts and virtual global contexts. A determinant theorem of attribute reduction is derived. Based on these results, an approach for distributed attribute reduction is presented. It first performs reduction independently on each local context using the existing approaches, and then local reducts are merged to compute reducts of global contexts. An algorithm implementation is provided and its effectiveness is validated. The distributed reduction algorithm facilitates not only improving computation efficiency but also avoiding the problems caused by the existing approaches, such as data privacy and communication overhead.
