@inproceedings{pho-etal-2014-multiple,
title = "Multiple Choice Question Corpus Analysis for Distractor Characterization",
author = "Pho, Van-Minh and
Andr{\'e}, Thibault and
Ligozat, Anne-Laure and
Grau, Brigitte and
Illouz, Gabriel and
Fran{\c{c}}ois, Thomas",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/692_Paper.pdf",
pages = "4284--4291",
abstract = "In this paper, we present a study of MCQ aiming to define criteria in order to automatically select distractors. We are aiming to show that distractor editing follows rules like syntactic and semantic homogeneity according to associated answer, and the possibility to automatically identify this homogeneity. Manual analysis shows that homogeneity rule is respected to edit distractors and automatic analysis shows the possibility to reproduce these criteria. These ones can be used in future works to automatically select distractors, with the combination of other criteria.",
}
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<abstract>In this paper, we present a study of MCQ aiming to define criteria in order to automatically select distractors. We are aiming to show that distractor editing follows rules like syntactic and semantic homogeneity according to associated answer, and the possibility to automatically identify this homogeneity. Manual analysis shows that homogeneity rule is respected to edit distractors and automatic analysis shows the possibility to reproduce these criteria. These ones can be used in future works to automatically select distractors, with the combination of other criteria.</abstract>
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%0 Conference Proceedings
%T Multiple Choice Question Corpus Analysis for Distractor Characterization
%A Pho, Van-Minh
%A André, Thibault
%A Ligozat, Anne-Laure
%A Grau, Brigitte
%A Illouz, Gabriel
%A François, Thomas
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F pho-etal-2014-multiple
%X In this paper, we present a study of MCQ aiming to define criteria in order to automatically select distractors. We are aiming to show that distractor editing follows rules like syntactic and semantic homogeneity according to associated answer, and the possibility to automatically identify this homogeneity. Manual analysis shows that homogeneity rule is respected to edit distractors and automatic analysis shows the possibility to reproduce these criteria. These ones can be used in future works to automatically select distractors, with the combination of other criteria.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/692_Paper.pdf
%P 4284-4291
Markdown (Informal)
[Multiple Choice Question Corpus Analysis for Distractor Characterization](http://www.lrec-conf.org/proceedings/lrec2014/pdf/692_Paper.pdf) (Pho et al., LREC 2014)
ACL
- Van-Minh Pho, Thibault André, Anne-Laure Ligozat, Brigitte Grau, Gabriel Illouz, and Thomas François. 2014. Multiple Choice Question Corpus Analysis for Distractor Characterization. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 4284–4291, Reykjavik, Iceland. European Language Resources Association (ELRA).