JOURNAL ARTICLE

Automatic question-answer pairs generation and question similarity mechanism in question answering system

Shivani G AithalAbishek B RaoSanjay Singh

Year: 2021 Journal:   Applied Intelligence Vol: 51 (11)Pages: 8484-8497   Publisher: Springer Science+Business Media

Abstract

Abstract With the swift growth of the information over the past few years, taking full benefit is increasingly essential. Question Answering System is one of the promising methods to access this much information. The Question Answering System lacks humans’ common sense and reasoning power and cannot identify unanswerable questions and irrelevant questions. These questions are answered by making unreliable and incorrect guesses. In this paper, we address this limitation by proposing a Question Similarity mechanism. Before a question is posed to a Question-Answering system, it is compared with possible generated questions of the given paragraph, and then a Question Similarity Score is generated. The Question Similarity mechanism effectively identifies the unanswerable and irrelevant questions. The proposed Question Similarity mechanism incorporates a human way of reasoning to identify unanswerable and irrelevant questions. This mechanism can avoid the unanswerable and irrelevant questions altogether from being posed to the Question Answering system. It helps the Question Answering Systems to focus only on the answerable questions to improve their performance. Along with this, we introduce an application of the Question Answering System that generates the question-answer pairs given a passage and is useful in several fields.

Keywords:
Question answering Mechanism (biology) Computer science Similarity (geometry) Paragraph Information retrieval Artificial intelligence Epistemology World Wide Web Philosophy

Metrics

35
Cited By
4.23
FWCI (Field Weighted Citation Impact)
46
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Multimodal Machine Learning Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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