2015 ApplyingDeepLearningtoAnswerSel

• (Feng et al., 2015) ⇒ Minwei Feng, Bing Xiang, Michael R. Glass, Lidan Wang, and Bowen Zhou. (2015). “Applying Deep Learning to Answer Selection: A Study and An Open Task.” In: Proceedings of 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU 2015). ISBN:978-1-4799-7291-3 doi:10.1109/ASRU.2015.7404872

Subject Headings: Question Answering (QA) System; Deep QA System.

Cited By

• http://scholar.google.com/scholar?q=%222015%22+Applying+Deep+Learning+to+Answer+Selection%3A+A+Study+and+An+Open+Task

Quotes

Author Keywords

• Answer Selection; Question Answering; Convolutional Neural Network (CNN); Deep Learning; Spoken Question Answering System

Abstract

We apply a general deep learning framework to address the non-factoid question answering task. Our approach does not rely on any linguistic tools and can be applied to different languages or domains. Various architectures are presented and compared. We create and release a QA corpus and setup a new QA task in the insurance domain. Experimental results demonstrate superior performance compared to the baseline methods and various technologies give further improvements. For this highly challenging task, the top-1 accuracy can reach up to 65.3% on a test set, which indicates a great potential for practical use.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2015 ApplyingDeepLearningtoAnswerSel	Lidan Wang Minwei Feng Bing Xiang Bowen Zhou Michael R. Glass			Applying Deep Learning to Answer Selection: A Study and An Open Task				10.1109/ASRU.2015.7404872		2015