Difference between revisions of "A Learning-Based Framework to Utilize E-Hownet Ontology and Wikipedia Sources to Generate Multiple-Choice Factual Questions"
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| − | '''A Learning-Based Framework to Utilize E-Hownet Ontology and Wikipedia Sources to Generate Multiple-Choice Factual Questions''' - scientific work related to Wikipedia quality published in 2012, written by Min-Huang Chu, Wen-Yu Chen and Shou-De Lin. | + | '''A Learning-Based Framework to Utilize E-Hownet Ontology and Wikipedia Sources to Generate Multiple-Choice Factual Questions''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Min-Huang Chu]], [[Wen-Yu Chen]] and [[Shou-De Lin]]. |
== Overview == | == Overview == | ||
| − | This 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. Authors 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. Authors then propose a way to generate distractors by using E-How Net 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%. | + | This 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. Authors 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. Authors then propose a way to generate distractors by using E-How Net [[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%. |
Revision as of 10:54, 26 October 2019
A Learning-Based Framework to Utilize E-Hownet Ontology and Wikipedia Sources to Generate Multiple-Choice Factual Questions - scientific work related to Wikipedia quality published in 2012, written by Min-Huang Chu, Wen-Yu Chen and Shou-De Lin.
Overview
This 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. Authors 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. Authors then propose a way to generate distractors by using E-How Net 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%.
