Multilingual automatic text summarizer using statistical approach and extraction

Text Summarization Overview and Background

Automatic Text Summarization using a Graph Theoretic Approach

This repository contains the MSc thesis project titled "A Generic Multitask Summarizer for Amharic Text Documents". The project addresses the challenges of information overload and automatic text analysis by providing a versatile and parameterizable framework for extractive text summarization.

This repository contains scripts for a weak learning summarization pipeline in Arabic and English.

Reproduction package for A comprehensive review of automatic text summarization techniques: method, data, evaluation and coding

A simple text summarizer

Typical automatic text summarisation makes use of either an extraction or an abstraction based model. This project specifically is an implementation of a feature-based extraction summariser. Primarily engineered using Python 2.7

Automatic Text Summarization is implemented using Python NLTK library by tokenizing the sentences, finding weighted frequency of occurrence and calculating sentence scores. The process of web scraping articles is done using BeautifulSoup library.

Automatic Text Summarization Tool.

An extractive text summarizer