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A learning-based framework to utilize E-HowNet ontology and Wikipedia sources to generate multiple-choice factual questions
Abstract This paper proposes a framework that automThis paper proposes a framework that automatically generates multiple-choice questions. Unlike most other similar works that focus on generating questions for English proficiency tests, this paper provides a framework to generate factual questions in Chinese. We have decomposed this problem into several sub-tasks: a) the identification of sentences that contain factual knowledge, b) the identification of the query term from each factual sentence, and c) the generation of distractors. Learning-based approaches are applied to address the first two problems. We then propose a way to generate distractors by using E-HowNet ontology database and Wikipedia sources. The system was evaluated through user study and test theory, and achieved a satisfaction rate of up to 70.6%.hieved a satisfaction rate of up to 70.6%.
Abstractsub This paper proposes a framework that automThis paper proposes a framework that automatically generates multiple-choice questions. Unlike most other similar works that focus on generating questions for English proficiency tests, this paper provides a framework to generate factual questions in Chinese. We have decomposed this problem into several sub-tasks: a) the identification of sentences that contain factual knowledge, b) the identification of the query term from each factual sentence, and c) the generation of distractors. Learning-based approaches are applied to address the first two problems. We then propose a way to generate distractors by using E-HowNet ontology database and Wikipedia sources. The system was evaluated through user study and test theory, and achieved a satisfaction rate of up to 70.6%.hieved a satisfaction rate of up to 70.6%.
Bibtextype inproceedings  +
Doi 10.1109/TAAI.2012.38  +
Has author Chu M.-H. + , Chen W.-Y. + , Lin S.-D. +
Has extra keyword Distractor + , E-HowNet + , Factual knowledge + , Learning-based approach + , Multiple-choice questions + , Proficiency tests + , Query terms + , Subtasks + , User study + , Wikipedia + , Artificial intelligence + , Ontology + , Query processing + , Websites +
Has keyword Distractor + , E-HowNet + , Multiple-choice questions + , Ontology + , Wikipedia +
Isbn 9780769549194  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 125–130  +
Published in Proceedings - 2012 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2012 +
Title A learning-based framework to utilize E-HowNet ontology and Wikipedia sources to generate multiple-choice factual questions +
Type conference paper  +
Year 2012 +
Creation dateThis property is a special property in this wiki. 7 November 2014 01:24:44  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 01:24:44  +
DateThis property is a special property in this wiki. 2012  +
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A learning-based framework to utilize E-HowNet ontology and Wikipedia sources to generate multiple-choice factual questions + Title
 

 

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