EXTRACTION-BASED TEXT SUMMARIZATION USING FUZZY ANALYSIS

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.