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Using natural language patterns for the development of ontologies

Authors: Montiel Ponsoda, Elena; Aguado de Cea, Guadalupe;

Using natural language patterns for the development of ontologies

Abstract

The combination of certain linguistic units that recurrently appear in text genres has attracted the attention of many researchers in several domains, as they can provide valuable information about different types of relations. In this paper, the focus is on some of these combinatory units, referred to as Lexico-Syntactic Patterns (LSPs) that provide information about conceptual structures present in ontologies, also called Ontology Design Patterns (ODPs). The final end is to create a repository of LSPs associated to the ontological structures they convey to help novice users in the development of ontologies. In this paper we present the different strategies we have followed to identify LSPs, as well as an excerpt of the repository of LSPs-ODPs that is currently being built.

Country
Spain
Related Organizations
Keywords

Informática, NeOn, oeg

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    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).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
3
Average
Average
Average
Green