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https://doi.org/10.3115/992133...
Article . 1992 . Peer-reviewed
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A feature-based model for lexical databases

Authors: Jean Véronis; Nancy Ide;

A feature-based model for lexical databases

Abstract

To date, no fully suitable data model for lexical databases has been proposed. As lexical databases have proliferated in multiple formats, there has been growing concern over the reusability of lexical resources. In this paper, we propose a model based on feature structures which overcomes most of the problems inherent in classical database models, and in particular enables accessing, manipulating or merging information structured in multiple ways. Because of their widespread use in the representation of linguistic information, the applicability of feature structures to lexical databases seems natural, although to our knowledge this has not yet been implemented. The use of feature structures in lexical databases also opens up the possibility of compatibility with computational lexicons.

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    citations
    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).
    3
    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.
    Average
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citations
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
Top 10%
Average
bronze