Automatic Text Summarization Using Fuzzy Inference

被引:0
作者
Jafari, Mehdi [1 ]
Shahabi, Amir Shahab [2 ]
Wang, Jing [3 ]
Qin, Yongrui [3 ]
Tao, Xiaohui [4 ]
Gheisari, Mehdi [5 ]
机构
[1] Eyvanakey Higher Inst Educ, Semnan, Iran
[2] Islamic Azad Univ, Sci & Res Branch, Dept Comp Engn, Tehran, Iran
[3] Univ Huddersfield, Sch Comp & Engn, Huddersfield HD1 3DH, W Yorkshire, England
[4] Univ Southern Queensland, Fac Hlth Engn & Sci, Toowoomba, Qld, Australia
[5] Islamic Azad Univ, Parand Branch, Young Researchers & Elite Club, Parand, Iran
来源
2016 22ND INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC) | 2016年
关键词
text summarization; fuzzy logic; sense relation;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:256 / 260
页数:5
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