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Educational Question Answering based on Social Media Content

Gurevych, Iryna ; Bernhard, Delphine ; Ignatova, Kateryna ; Toprak, Cigdem
eds.: Dimitrova, Vania ; Mizoguchi, Riichiro ; du Boulay, Benedict ; Graesser, Art (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)
Book Section, Bibliographie

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 ; Mizoguchi, Riichiro ; du Boulay, Benedict ; Graesser, Art
Creators: Gurevych, Iryna ; Bernhard, Delphine ; Ignatova, Kateryna ; Toprak, Cigdem
Type of entry: Bibliographie
Title: Educational Question Answering based on Social Media Content
Language: English
Date: July 2009
Publisher: IOS Press
Book Title: Proceedings of the 14th International Conference on Artificial Intelligence in Education. Building learning systems that care: From knowledge representation to affective modelling (AIED2009)
Series: Frontiers in Artificial Intelligence and Applications
Series Volume: 200
URL / URN: http://ebooks.iospress.nl/volumearticle/5146
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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.

Uncontrolled Keywords: Educational Natural Language Processing;UKP_a_ENLP;UKP_p_QAEL
Identification Number: TUD-CS-2009-0015
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
Date Deposited: 31 Dec 2016 14:29
Last Modified: 24 Jan 2020 12:03
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