Adaptive Merging of Prioritized Knowledge Bases

• Autorzy: Liu W. , Qi G. , Bell D.A.
• Języki publikacji: EN

Abstrakty

EN

In this paper, we propose an adaptive algorithm for merging n (n ł 2) prioritized knowledge bases which takes into account the degrees of conflict and agreement among these knowledge bases. The algorithm first selects largely partially maximal consistent subsets (LPMCS) of sources by assessing how (partially) consistent the information in the subset is. Then within each of these created subsets, a maximal consistent subset is further selected and knowledge bases in it are merged with a suitable conjunctive operator based on the degree of agreement among them. This result is then merged with the remaining knowledge bases in the corresponding LPMCS in the second step through the relaxation of the minimum operator. Finally, the knowledge bases obtained from the second step are merged by a maximum operator. In comparison with other merging methods, our approach is more context dependent and is especially useful when most sources of information are in conflict.

Słowa kluczowe

EN

possibilistic logic; prioritized knowledge bases; belief merging; context dependent merging

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2006
• Tom: Vol. 73, nr 3
• Strony: 389--407
• Opis fizyczny: bibliogr. 17 poz.

Twórcy

autor

Liu W.

autor

Qi G.

autor

Bell D.A.

• School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, BT7 1NN, UK,

Bibliografia

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