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Automatic Text Summarization Using Fuzzy Inference

Jafari, Mehdi, Shahabi, Amir, Wang, Jing, Qin, Yongrui, Tao, Xiaohui and Gheisari, Mehdi (2016) Automatic Text Summarization Using Fuzzy Inference. In: Proceedings 22nd International Conference on Automation and Computing. IEEE. ISBN 9781862181328

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Due to the high volume of information and electronic documents on the Web, it is almost impossible for a human to study, research and analyze this volume of text. Summarizing the main idea and the major concept of the context enables the humans to read the summary of a large volume of text quickly and decide whether to further dig into details. Most of the existing summarization approaches have applied probability and statistics based techniques. But these approaches cannot achieve high accuracy. We observe that attention to the concept and the meaning of the context could greatly improve summarization accuracy, and due to the uncertainty that exists in the summarization methods, we simulate human like methods by integrating fuzzy logic with traditional statistical approaches in this study. The results of this study indicate that our approach can deal with uncertainty and achieve better results when compared with existing methods.

Item Type: Book Chapter
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools: School of Computing and Engineering
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Depositing User: Xiaowei Wang
Date Deposited: 28 Jul 2016 13:19
Last Modified: 28 Aug 2021 16:53


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