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Mining Correlated Policy Rules with Concept Lattice

Authors: Suyun Jiao; Yanheng Liu 0001; Xuejie Liu; Da Wei; Hai-yan Hu;

Mining Correlated Policy Rules with Concept Lattice

Abstract

Concept lattice was creatively used in mining correlated policy rules in this study. It takes much time for a conflict detection routine to search every policy in policy repository with conventional policy storage models to see if conflict occurs before a new dynamic policy is added to the policy repository. A novel storage model for dynamic policies was proposed to address this problem. Dynamic policies were organized into a concept lattice to be grouped effectively and stably. Then a correlated policy rules algorithm based on the concept lattice was proposed after the concept of correlated policy rules was defined. The algorithm greatly reduces the number of policies necessary for conflict detection, and increases efficiency of conflict detection. Performance analysis and simulation show that the proposed algorithm is effective.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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