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Question Answering System (QAS) is one of the information extraction techniques that is used to retrieve the answer from the given text paragraph for the given question. In the proposed QAS system for agricultural domain (AQAPS) involves both Question Generation and Answer Extraction from the domain based input document. First, a Knowledge Graph (KG) is generated from the given input text document using relationship extractor. From the generated KG, questions are generated using encoder-decoder neural network and answers are extracted using Recurrent Neural Network (RNN). Appropriate question-answer pairs are generated using answer selection methodology. The proposed AQAPS shows accuracy of 87.3% and while comparing with existing systems, the AQAPS performs better.

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An Agricultural Domain Based Question Answering System Using Natural Language Processing and Deep Learning Methodologies

  • 会议论文

  • 发表日期：

    2025年

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  • Krithikha Sanju Saravanan,
  • B. L. Velammal

摘要

Question Answering System (QAS) is one of the information extraction techniques that is used to retrieve the answer from the given text paragraph for the given question. In the proposed QAS system for agricultural domain (AQAPS) involves both Question Generation and Answer Extraction from the domain based input document. First, a Knowledge Graph (KG) is generated from the given input text document using relationship extractor. From the generated KG, questions are generated using encoder-decoder neural network and answers are extracted using Recurrent Neural Network (RNN). Appropriate question-answer pairs are generated using answer selection methodology. The proposed AQAPS shows accuracy of 87.3% and while comparing with existing systems, the AQAPS performs better.