A curated list of resources dedicated to text summarization

Automagically generates summaries from html or text.

Source based extractive summarizer web-app and chatbot.

Scripts for an upcoming blog "Extractive vs. Abstractive Summarization" for RaRe Technologies.

A script to process the ArXiv-PubMed dataset.

Simple Extractive Text Summarization using SpaCy, using a frequency model

Extractive summarizationof medical transcriptions

A lightweight Extractive Summarization Formulation for the CNN Dataset

Extractive text summarization application

Extractive Summarization of text using TF-IDF

This repository contains the source code written in Python for generating short crisp summaries of given long text. I used Amazon review dataset from Kaggle for this project. The short summaries are generated using Recurrent Neural Networks.

The repository include the evaluation code for the SumTO summarization system proposed for the FNS 2020 Shared Task

LinTO's NLP service: Extractive Summarization

Extractive Text Summarizer, based on tf-idf text representation (an example)

Automatic summarization is the process of shortening a text document with software, in order to create a summary with the major points of the original document. Technologies that can make a coherent summary take into account variables such as length, writing style and syntax.

Código fonte da aplicação desenvolvida no meu PIBIC de 2019 a 2020, orientado pelo professor Dr. Hendrik Macedo. Este código executa a aplicação localmente.

Extractive Text Summarization using Integrated TextRank and BM25+ Algorithm

This repository presents and compares HeterSUMGraph and variants using GATConv, GATv2Conv and a combination of HeterSUMGraph and SummaRuNNer (using HeterSUMGraph as a sentence encoder).