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Question Answering System Using LSTM and Keyword Generation

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Advances in Information Communication Technology and Computing

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 135))

Abstract

Question answering system is an area under natural language processing and information retrieval which automatically answers the questions generated by humans. This work represents an approach for building a system that generates answers for the question based on deep learning neural network which has the competence of processing the information present inside the dataset and enables the user to obtain an insight from the SQuAD dataset by inviting questions in natural language form. Key stages of this approach cover corpus pre-processing, question pre-processing, answer generation, deep neural network for answer extraction and keyword generation. The concept of keyword generation is a novel idea implemented to enable naïve user of the system to apprehend the passage. The system is competent in interpreting the question, responding to the user’s query in natural language form along with generating the keywords. The performance was measured on SQuAD dataset using EM and F1 score.

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Author information

Authors and Affiliations

  1. University School of Information Communication and Technology, GGSIPU, Delhi, India

    Minakshi Tomer

  2. Maharaja Surajmal Institute of Technology, Delhi, India

    Minakshi Tomer

  3. Ambedkar Institute of Advanced Communication Technologies and Research, Delhi, India

    Manoj Kumar

Authors
  1. Minakshi Tomer
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  2. Manoj Kumar
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Corresponding author

Correspondence to Minakshi Tomer .

Editor information

Editors and Affiliations

  1. Department of Computer Application, Government Engineering College, Bikaner, Rajasthan, India

    Vishal Goar

  2. Department of Electronics and Communication, Government Engineering College, Bikaner, Rajasthan, India

    Manoj Kuri

  3. Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Rajesh Kumar

  4. Department of Electrical and Electronics Engineering, University of the Ryukyus, Nishihara, Japan

    Tomonobu Senjyu

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Tomer, M., Kumar, M. (2021). Question Answering System Using LSTM and Keyword Generation. In: Goar, V., Kuri, M., Kumar, R., Senjyu, T. (eds) Advances in Information Communication Technology and Computing. Lecture Notes in Networks and Systems, vol 135. Springer, Singapore. https://doi.org/10.1007/978-981-15-5421-6_28

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  • DOI: https://doi.org/10.1007/978-981-15-5421-6_28

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5420-9

  • Online ISBN: 978-981-15-5421-6

  • eBook Packages: EngineeringEngineering (R0)

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