Use of fuzzy logic and wordnet for improving performance of extractive automatic text summarization
Automatic Text Summarization is a process of generating Summary/Head note for the text document. Text Summarization is carried out by two main methods, namely, Extraction and Abstraction. This paper utilizes the extraction process for sentence selection. Here some Feature based sentence scoring techniques also used, which played an important role in text summarization. Finally an analysis is done by comparing the Fuzzy Logic and Neural Networks techniques based upon the Precision, Recall & F-Measure. Fuzzy Logic rules were used to balance the weights between important and unimportant features based on the feature Extraction. The Experimental result shows that fuzzy Logics give an improving result than the Neural Networks. Keywords— Fuzzy Logic, Neural Network, Sentence Scoring, Feature Extraction, Text Summarization.