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2020 | OriginalPaper | Chapter

Question–Answer System on Episodic Data Using Recurrent Neural Networks (RNN)

Authors : Vineet Yadav, Vishnu Bharadwaj, Alok Bhatt, Ayush Rawal

Published in: Data Management, Analytics and Innovation

Publisher: Springer Singapore

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Abstract

Data comprehension is one of the key applications of question-answer systems. This involves a closed-domain answering system where a system can answer questions based on the given data. Previously people have used methods such as part of speech tagging and named entity recognition for such problems but those methods have struggled to produce accurate results since they have no information retention mechanisms. Deep learning and specifically recurrent neural networks based methods such as long short-term memory have been shown to be successful in creating accurate answering systems. This paper focuses on episodic memory where certain facts are aggregated in the form of a story and a question is asked related to a certain object in the story and a single fact present is given as answer. The paper compares the performance of these algorithms on benchmark dataset and provides guidelines on parameter tuning to obtain maximum accuracy. High accuracy (80% and above) was achieved on three tasks out of four.

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Literature
1.
go back to reference Wang, Z., Yan, S., Wang, H., Huang, X.: An overview of Microsoft deep QA system on Stanford WebQuestions benchmark. Technical report, Microsoft Research (2014) Wang, Z., Yan, S., Wang, H., Huang, X.: An overview of Microsoft deep QA system on Stanford WebQuestions benchmark. Technical report, Microsoft Research (2014)
8.
go back to reference Kumar, A., Ondruska, P., Iyyer, M., Bradbury, J., Gulrajani, I., Zhong, V., Paulus, R., Socher, R.: Ask Me Anything: Dynamic Memory Networks for Natural Language Processing (2015). arXiv preprint arXiv:1506.07285 Kumar, A., Ondruska, P., Iyyer, M., Bradbury, J., Gulrajani, I., Zhong, V., Paulus, R., Socher, R.: Ask Me Anything: Dynamic Memory Networks for Natural Language Processing (2015). arXiv preprint arXiv:​1506.​07285
Metadata
Title
Question–Answer System on Episodic Data Using Recurrent Neural Networks (RNN)
Authors
Vineet Yadav
Vishnu Bharadwaj
Alok Bhatt
Ayush Rawal
Copyright Year
2020
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-32-9949-8_39