This paper presents a novel ontology mapping approach based on rough set theory and instance selection.In this appoach the construction approach of a rough set-based inference instance base in which the instance selec...This paper presents a novel ontology mapping approach based on rough set theory and instance selection.In this appoach the construction approach of a rough set-based inference instance base in which the instance selection(involving similarity distance,clustering set and redundancy degree)and discernibility matrix-based feature reduction are introduced respectively;and an ontology mapping approach based on multi-dimensional attribute value joint distribution is proposed.The core of this mapping aI overlapping of the inference instance space.Only valuable instances and important attributes can be selected into the ontology mapping based on the multi-dimensional attribute value joint distribution,so the sequently mapping efficiency is improved.The time complexity of the discernibility matrix-based method and the accuracy of the mapping approach are evaluated by an application example and a series of analyses and comparisons.展开更多
This paper proposes a constructive approach to solving geometric constraint systems.The approach incorporates graph-based and rule-based approaches, and achieves interactive speed.The paper presents a graph representa...This paper proposes a constructive approach to solving geometric constraint systems.The approach incorporates graph-based and rule-based approaches, and achieves interactive speed.The paper presents a graph representation of geometric conStraint syStems, and discusses in detailthe algorithm of geometric reasoning based on poinl-cluster reduction. An example is made forillustration.展开更多
基金the National High Technology Research and Development Program of China(No.2002AA411420)the National Key Basic Research and Development Program of China(No.2003CB316905)the National Natural Science Foundation of China(No.60374071)
文摘This paper presents a novel ontology mapping approach based on rough set theory and instance selection.In this appoach the construction approach of a rough set-based inference instance base in which the instance selection(involving similarity distance,clustering set and redundancy degree)and discernibility matrix-based feature reduction are introduced respectively;and an ontology mapping approach based on multi-dimensional attribute value joint distribution is proposed.The core of this mapping aI overlapping of the inference instance space.Only valuable instances and important attributes can be selected into the ontology mapping based on the multi-dimensional attribute value joint distribution,so the sequently mapping efficiency is improved.The time complexity of the discernibility matrix-based method and the accuracy of the mapping approach are evaluated by an application example and a series of analyses and comparisons.
文摘This paper proposes a constructive approach to solving geometric constraint systems.The approach incorporates graph-based and rule-based approaches, and achieves interactive speed.The paper presents a graph representation of geometric conStraint syStems, and discusses in detailthe algorithm of geometric reasoning based on poinl-cluster reduction. An example is made forillustration.
