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Introducing Word's Importance Level-Based Text Summarization Using Tree Structure

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  • Nitesh Kumar Jha

    (Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India)

  • Arnab Mitra

    (Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India)

Abstract

Text-summarization plays a significant role towards quick knowledge acquisition from any text-based knowledge resource. To enhance the text-summarization process, a new approach towards automatic text-summarization is presented in this article that facilitates level (word importance factor)-based automated text-summarization. An equivalent tree is produced from the directed-graph during the input text processing with WordNet. Detailed investigations further ensure that the execution time for proposed automatic text-summarization, is strictly following a linear relationship with reference to the varying volume of inputs. Further investigation towards the performance of proposed automatic text-summarization approach ensures its superiority over several other existing text-summarization approaches.

Suggested Citation

  • Nitesh Kumar Jha & Arnab Mitra, 2020. "Introducing Word's Importance Level-Based Text Summarization Using Tree Structure," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 10(1), pages 13-33, January.
    • Handle: RePEc:igg:jirr00:v:10:y:2020:i:1:p:13-33
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