@inproceedings{tayyar-madabushi-lee-2016-high,
title = "High Accuracy Rule-based Question Classification using Question Syntax and Semantics",
author = "Tayyar Madabushi, Harish and
Lee, Mark",
editor = "Matsumoto, Yuji and
Prasad, Rashmi",
booktitle = "Proceedings of {COLING} 2016, the 26th International Conference on Computational Linguistics: Technical Papers",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/C16-1116",
pages = "1220--1230",
abstract = "We present in this paper a purely rule-based system for Question Classification which we divide into two parts: The first is the extraction of relevant words from a question by use of its structure, and the second is the classification of questions based on rules that associate these words to Concepts. We achieve an accuracy of 97.2{\%}, close to a 6 point improvement over the previous State of the Art of 91.6{\%}. Additionally, we believe that machine learning algorithms can be applied on top of this method to further improve accuracy.",
}
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%0 Conference Proceedings
%T High Accuracy Rule-based Question Classification using Question Syntax and Semantics
%A Tayyar Madabushi, Harish
%A Lee, Mark
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F tayyar-madabushi-lee-2016-high
%X We present in this paper a purely rule-based system for Question Classification which we divide into two parts: The first is the extraction of relevant words from a question by use of its structure, and the second is the classification of questions based on rules that associate these words to Concepts. We achieve an accuracy of 97.2%, close to a 6 point improvement over the previous State of the Art of 91.6%. Additionally, we believe that machine learning algorithms can be applied on top of this method to further improve accuracy.
%U https://aclanthology.org/C16-1116
%P 1220-1230
Markdown (Informal)
[High Accuracy Rule-based Question Classification using Question Syntax and Semantics](https://aclanthology.org/C16-1116) (Tayyar Madabushi & Lee, COLING 2016)
ACL