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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1075/nlp.2....
Part of book or chapter of book . 2001 . Peer-reviewed
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Automatic term detection

A review of current systems
descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book 15 Jun 2001 English Publisher:John Benjamins Publishing Company
Authors: M. Teresa Cabré Castellví; Rosa Estopà Bagot; Jordi Vivaldi Palatresi;

doi: 10.1075/nlp.2.04cab

Automatic term detection

Abstract

In this paper we account for the main characteristics and performance of a number of recently developed term extraction systems. The analysed tools represent the main strategies followed by researchers in this area. All systems are analysed and compared against a set of technically relevant characteristics.

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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!
97
Top 1%
Top 10%
Average
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