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Educational Question Answering based on Social Media Content

Gurevych, Iryna and Bernhard, Delphine and Ignatova, Kateryna and Toprak, Cigdem
Dimitrova, Vania and Mizoguchi, Riichiro and du Boulay, Benedict and Graesser, Art (eds.) (2009):
Educational Question Answering based on Social Media Content.
In: Proceedings of the 14th International Conference on Artificial Intelligence in Education. Building learning systems that care: From knowledge representation to affective modelling (AIED2009), IOS Press, pp. 133-140, [Online-Edition: http://ebooks.iospress.nl/volumearticle/5146],
[Book Section]

Abstract

We analyze the requirements for an educational Question Answering (QA) system operating on social media content. As a result, we identify a set of advanced natural language processing (NLP) technologies to address the challenges in educational QA. We conducted an inter-annotator agreement study on subjective question classification in the Yahoo!Answers social Q&A site and propose a simple, but effective approach to automatically identify subjective questions. We also developed a two-stage QA architecture for answering learners’ questions. In the first step, we aim at re-using human answers to already answered questions by employing question paraphrase identification [1]. In the second step, we apply information retrieval techniques to perform answer retrieval from social media content. We show that elaborate techniques for question preprocessing are crucial.

Item Type: Book Section
Erschienen: 2009
Editors: Dimitrova, Vania and Mizoguchi, Riichiro and du Boulay, Benedict and Graesser, Art
Creators: Gurevych, Iryna and Bernhard, Delphine and Ignatova, Kateryna and Toprak, Cigdem
Title: Educational Question Answering based on Social Media Content
Language: English
Abstract:

We analyze the requirements for an educational Question Answering (QA) system operating on social media content. As a result, we identify a set of advanced natural language processing (NLP) technologies to address the challenges in educational QA. We conducted an inter-annotator agreement study on subjective question classification in the Yahoo!Answers social Q&A site and propose a simple, but effective approach to automatically identify subjective questions. We also developed a two-stage QA architecture for answering learners’ questions. In the first step, we aim at re-using human answers to already answered questions by employing question paraphrase identification [1]. In the second step, we apply information retrieval techniques to perform answer retrieval from social media content. We show that elaborate techniques for question preprocessing are crucial.

Title of Book: Proceedings of the 14th International Conference on Artificial Intelligence in Education. Building learning systems that care: From knowledge representation to affective modelling (AIED2009)
Series Name: Frontiers in Artificial Intelligence and Applications
Volume: 200
Publisher: IOS Press
Uncontrolled Keywords: Educational Natural Language Processing;UKP_a_ENLP;UKP_p_QAEL
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
Date Deposited: 31 Dec 2016 14:29
Official URL: http://ebooks.iospress.nl/volumearticle/5146
Identification Number: TUD-CS-2009-0015
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