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Introducing Word's Importance Level-Based Text Summarization Using Tree Structure
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Author(s): Nitesh Kumar Jha (Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India)and Arnab Mitra (Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India)
Copyright: 2020
Volume: 10
Issue: 1
Pages: 21
Source title:
International Journal of Information Retrieval Research (IJIRR)
Editor(s)-in-Chief: Zhongyu Lu (University of Huddersfield, UK)
DOI: 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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