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

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

Nitesh Kumar Jha, Arnab Mitra
Copyright: © 2020 |Volume: 10 |Issue: 1 |Pages: 21
ISSN: 2155-6377|EISSN: 2155-6385|EISBN13: 9781799807315|DOI: 10.4018/IJIRR.2020010102
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MLA

Jha, Nitesh Kumar, and Arnab Mitra. "Introducing Word's Importance Level-Based Text Summarization Using Tree Structure." IJIRR vol.10, no.1 2020: pp.13-33. http://doi.org/10.4018/IJIRR.2020010102

APA

Jha, N. K. & Mitra, A. (2020). Introducing Word's Importance Level-Based Text Summarization Using Tree Structure. International Journal of Information Retrieval Research (IJIRR), 10(1), 13-33. http://doi.org/10.4018/IJIRR.2020010102

Chicago

Jha, Nitesh Kumar, and Arnab Mitra. "Introducing Word's Importance Level-Based Text Summarization Using Tree Structure," International Journal of Information Retrieval Research (IJIRR) 10, no.1: 13-33. http://doi.org/10.4018/IJIRR.2020010102

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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.

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