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https://doi.org/10.1007/115800...
Part of book or chapter of book . 2005 . Peer-reviewed
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Active Rules in the Semantic Web: Dealing with Language Heterogeneity

Authors: Wolfgang May; José Júlio Alferes; Ricardo Amador;

Active Rules in the Semantic Web: Dealing with Language Heterogeneity

Abstract

In the same way as the “static” Semantic Web deals with data model and language heterogeneity and semantics that lead to RDF and OWL, there is language heterogeneity and the need for a semantical account concerning Web dynamics. Thus, generic rule markup has to bridge these discrepancies, i.e., allow for composition of component languages, retaining their distinguished semantics and making them accessible e.g. for reasoning about rules. In this paper we analyze the basic concepts for a general language for evolution and reactivity in the Semantic Web. We propose an ontology based on the paradigm of Event-Condition-Action (ECA) rules including an XML markup. In this framework, different languages for events (including languages for composite events), conditions (queries and tests) and actions (including complex actions) can be composed to define high-level rules for describing behavior in the Semantic Web.

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Germany
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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).
    19
    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.
    Average
    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!
19
Average
Top 10%
Top 10%
Green
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