EXTRACTION-BASED TEXT SUMMARIZATION USING FUZZY ANALYSIS

Abstract

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