Document Type : Research Paper


1 Islamic Azad University of Shahrekord branch, Shahrekord, Iran

2 Shahid Bahonar University of Kerman, International Center for Science and High Technology and Environmental Sciences, Kerman, Iran

3 Shahid Bahonar University of Kerman, The centre of Excellence for Fuzzy system and applications, Kerman, Iran

4 Department of Energy, Electrical Engineering division, Politecnico di Milano, Milan, Italy


Due to the explosive growth of the world-wide web, automatic
text summarization has become an essential tool for web users. In this paper
we present a novel approach for creating text summaries. Using fuzzy logic
and word-net, our model extracts the most relevant sentences from an original
document. The approach utilizes fuzzy measures and inference on the
extracted textual information from the document to find the most significant
sentences. Experimental results reveal that the proposed approach extracts
the most relevant sentences when compared to other commercially available
text summarizers. Text pre-processing based on word-net and fuzzy analysis
is the main part of our work.


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