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International Journal of Approximate Reasoning
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International Journal of Approximate Reasoning
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Hybrid possibilistic networks

Authors: Benferhat, Salem; Smaoui, Salma;

Hybrid possibilistic networks

Abstract

zbMATH Open Web Interface contents unavailable due to conflicting licenses.

Country
France
Keywords

Possibility theory, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Possibilistic logic, possibilistic networks, Applied Mathematics, Possibilistic networks, possibility theory, Reasoning under uncertainty in the context of artificial intelligence, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Theoretical Computer Science, Knowledge representation, Artificial Intelligence, possibilistic logic, Software

  • BIP!
    Impact byBIP!
    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).
    26
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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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!
26
Top 10%
Top 10%
Top 10%
hybrid