Attribution: Please use this identifier to share, cite, or link to this item: http://hdl.handle.net/10625/49050
Title: Function-based question classification for general QA
Authors: Bu, Fan
Zhu, Xingwei
Hao, Yu
Zhu, Xiaoyan
Keywords: DATA
QUESTION ANSWER SYSTEMS
MACHINE LEARNING
KNOWLEDGE REPRESENTATION
NATURAL LANGUAGE PROCESSING
Date: Oct-2010
Publisher: Association for Computational Linguistics, Stroudsburg, PA
Citation: Bu, F., Zhu, X., & Hao, Y., Zhu, X. (2010). Function-based question classification for general QA. Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, MIT, Massachusetts, USA. (p. 1119–1128). Association for Computational Linguistics.
Abstract: In contrast with the booming increase of internet data, state-of-art QA (question answering) systems, otherwise, concerned data from specific domains or resources such as search engine snippets, online forums and Wikipedia in a somewhat isolated way. Users may welcome a more general QA system for its capability to answer questions of various sources, integrated from existed specialized sub-QA engines. In this framework, question classification is the primary task. However, the current paradigms of question classification were focused on some specified type of questions, i.e. factoid questions, which are inappropriate for the general QA. In this paper, we propose a new question classification paradigm, which includes a question taxonomy suitable to the general QA and a question classifier based on MLN (Markov logic network), where rule-based methods and statistical methods are unified into a single framework in a fuzzy discriminative learning approach. Experiments show that our method outperforms traditional
Description: Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
URI: http://hdl.handle.net/10625/49050
Project Number: 104519
Project Title: International Research Chairs Initiative (IRCI)
Access: IDRC Only
Copyright: Association for Computational Linguistics
Access Restriction: Due to copyright restrictions the full text of this research output is not available in the IDRC Digital Library or by request from the IDRC Library. / Compte tenu des restrictions relatives au droit d`auteur, le texte intégral de cet extrant de recherche n`est pas accessible dans la Bibliothèque numérique du CRDI, et il n`est pas possible d`en faire la demande à la Bibliothèque du CRDI.
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