Feature-Based Sentence Extraction Using Fuzzy Inference Rules

摘要: Automatic text summarization is a wide research area. to compress the original into shorter version and help user quickly understand large volumes of information. There are several ways in which one can characterize different approaches summarization: extractive abstractive from single document or multi document. This paper focuses on automatic by sentence extraction. The first step extraction identification important features. Our approach used features based fuzzy logic extract sentences. In our experiment, we 30 test documents DUC2002 data set. Each prepared preprocessing process: segmentation, tokenization, removing stop word, word stemming. Then, use 8 calculate their score for each sentence. We propose method using compare results with baseline summarizer Microsoft Word 2007 summarizers. show that highest average precision, recall, F-measure summaries conducted method.