A Framework for Extractive Text Summarization of Single Text Document in Tamil Language Using Frequency Based Feature Extraction Technique

Text summarization, a technique in Natural Language Processing, helps in summarizing documents like news articles, legal documents, essays and more. The content may be comprehensive and redundant. A summary gives an insight of the document. Text summarization is broadly classified into two categories—extractive and abstractive summarization. Abstractive summarization uses deep learning techniques to generate summary, just as humans generate summary using their own words and sentences. Extractive summarization highlights information based on some features or technique used to identify the importance of the sentence from the source document. Methods used for extractive summarization include ranking algorithms, sentence scoring, sentence similarity and so on. In this paper, a framework for extractive text summarization using features extracted from a Tamil document has been proposed. The summarizer is based on Fuzzy logic inference engine. The framework describes the modules involved in the generation of Extractive Text Summary for a single document.