@inproceedings{fiser-etal-2010-learning,
title = "Learning to Mine Definitions from {S}lovene Structured and Unstructured Knowledge-Rich Resources",
author = "Fi{\v{s}}er, Darja and
Pollak, Senja and
Vintar, {\v{S}}pela",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/141_Paper.pdf",
abstract = "The paper presents an innovative approach to extract Slovene definition candidates from domain-specific corpora using morphosyntactic patterns, automatic terminology recognition and semantic tagging with wordnet senses. First, a classification model was trained on examples from Slovene Wikipedia which was then used to find well-formed definitions among the extracted candidates. The results of the experiment are encouraging, with accuracy ranging from 67{\%} to 71{\%}. The paper also addresses some drawbacks of the approach and suggests ways to overcome them in future work.",
}
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<abstract>The paper presents an innovative approach to extract Slovene definition candidates from domain-specific corpora using morphosyntactic patterns, automatic terminology recognition and semantic tagging with wordnet senses. First, a classification model was trained on examples from Slovene Wikipedia which was then used to find well-formed definitions among the extracted candidates. The results of the experiment are encouraging, with accuracy ranging from 67% to 71%. The paper also addresses some drawbacks of the approach and suggests ways to overcome them in future work.</abstract>
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%0 Conference Proceedings
%T Learning to Mine Definitions from Slovene Structured and Unstructured Knowledge-Rich Resources
%A Fišer, Darja
%A Pollak, Senja
%A Vintar, Špela
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F fiser-etal-2010-learning
%X The paper presents an innovative approach to extract Slovene definition candidates from domain-specific corpora using morphosyntactic patterns, automatic terminology recognition and semantic tagging with wordnet senses. First, a classification model was trained on examples from Slovene Wikipedia which was then used to find well-formed definitions among the extracted candidates. The results of the experiment are encouraging, with accuracy ranging from 67% to 71%. The paper also addresses some drawbacks of the approach and suggests ways to overcome them in future work.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/141_Paper.pdf
Markdown (Informal)
[Learning to Mine Definitions from Slovene Structured and Unstructured Knowledge-Rich Resources](http://www.lrec-conf.org/proceedings/lrec2010/pdf/141_Paper.pdf) (Fišer et al., LREC 2010)
ACL