@inproceedings{sadamitsu-etal-2014-extraction,
title = "Extraction of Daily Changing Words for Question Answering",
author = "Sadamitsu, Kugatsu and
Higashinaka, Ryuichiro and
Matsuo, Yoshihiro",
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/271_Paper.pdf",
pages = "2608--2612",
abstract = "This paper proposes a method for extracting Daily Changing Words (DCWs), words that indicate which questions are real-time dependent. Our approach is based on two types of template matching using time and named entity slots from large size corpora and adding simple filtering methods from news corpora. Extracted DCWs are utilized for detecting and sorting real-time dependent questions. Experiments confirm that our DCW method achieves higher accuracy in detecting real-time dependent questions than existing word classes and a simple supervised machine learning approach.",
}
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%0 Conference Proceedings
%T Extraction of Daily Changing Words for Question Answering
%A Sadamitsu, Kugatsu
%A Higashinaka, Ryuichiro
%A Matsuo, Yoshihiro
%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 sadamitsu-etal-2014-extraction
%X This paper proposes a method for extracting Daily Changing Words (DCWs), words that indicate which questions are real-time dependent. Our approach is based on two types of template matching using time and named entity slots from large size corpora and adding simple filtering methods from news corpora. Extracted DCWs are utilized for detecting and sorting real-time dependent questions. Experiments confirm that our DCW method achieves higher accuracy in detecting real-time dependent questions than existing word classes and a simple supervised machine learning approach.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/271_Paper.pdf
%P 2608-2612
Markdown (Informal)
[Extraction of Daily Changing Words for Question Answering](http://www.lrec-conf.org/proceedings/lrec2014/pdf/271_Paper.pdf) (Sadamitsu et al., LREC 2014)
ACL
- Kugatsu Sadamitsu, Ryuichiro Higashinaka, and Yoshihiro Matsuo. 2014. Extraction of Daily Changing Words for Question Answering. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 2608–2612, Reykjavik, Iceland. European Language Resources Association (ELRA).