233 Open source projects that are alternatives of or similar to Sumrized

AQMAR Arabic Tagger: Sequence tagger with cost-augmented structured perceptron training

An implementation of transformer-based language model for sentence rewriting tasks such as summarization, simplification, and grammatical error correction.

Tensorflow seq2seq Implementation of Text Summarization.

ROUGE automatic summarization evaluation toolkit. Support for ROUGE-[N, L, S, SU], stemming and stopwords in different languages, unicode text evaluation, CSV output.

A text document will be provided and it'll produce it's summary

💨Making communication📞easier and faster🚅for all 👦 + 👧 + 👴 + 👶 + 🐮 + 🐦 + 🐱

Implementation of a seq2seq model for summarization of textual data. Demonstrated on amazon reviews, github issues and news articles.

自然语言处理工具Macropodus，基于Albert+BiLSTM+CRF深度学习网络架构，中文分词，词性标注，命名实体识别，新词发现，关键词，文本摘要，文本相似度，科学计算器，中文数字阿拉伯数字(罗马数字)转换，中文繁简转换，拼音转换。tookit(tool) of NLP，CWS(chinese word segnment)，POS(Part-Of-Speech Tagging)，NER(name entity recognition)，Find(new words discovery)，Keyword(keyword extraction)，Summarize(text summarization)，Sim(text similarity)，Calculate(scientific calculator)，Chi2num(chinese number to arabic number)

25,100 queries from the Paralex corpus (Fader et al., 2013) annotated with human ratings of whether they are well-formed natural language questions.

In a nutshell, this is a Text Summarizer

Code for paper "Discourse-Aware Neural Extractive Text Summarization" (ACL20)

This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021.

On Generating Extended Summaries of Long Documents

Arabic Tokenization Library. It provides many tokenization algorithms.

The guide to tackle with the Text Summarization

📖 A curated list of resources dedicated to Natural Language Processing (NLP) in the Yoruba Language.

Well tested & Multi-language evaluation framework for text summarization.

비지도학습 방법으로 한국어 텍스트에서 단어/키워드를 자동으로 추출하는 라이브러리입니다

Text summarization starting from scratch.

A simple Flask website for all NLP tasks which includes Text Preprocessing, Keyword Extraction, Text Summarization etc. Created Date: 30 Jan 2019

A small NLP SAAS project that summarize a webpage

Preparing a dataset for TensorFlow text summarization (TextSum) model.

Library of state-of-the-art models (PyTorch) for NLP tasks

A marketing tool that helps you to market your products using organic marketing. This tool can potentially save you 1000s of dollars every year. The tool predicts the reach of your posts on social media and also suggests you hashtags for captions in such a way that it increases your reach.

텍스트 요약 분야의 주요 연구 주제, Must-read Papers, 이용 가능한 model 및 data 등을 추천 자료와 함께 정리한 저장소입니다.

Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.

A tool to automatically summarize documents abstractively using the BART or PreSumm Machine Learning Model.

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

Project 4 for Metis bootcamp. Objective was generation of character-level RNN trained on Donald Trump's statements using Keras. Also generated Markov chains, and quick pyTorch RNN as baseline. Attempted semi-supervised GAN, but was unable to test in time.

Dataset for CIKM 2018 paper "Multi-Source Pointer Network for Product Title Summarization"

A module for E-mail Summarization which uses clustering of skip-thought sentence embeddings.

TextRank implementation for Python 3.

paribhasha.herokuapp.com/

文本挖掘和预处理工具（文本清洗、新词发现、情感分析、实体识别链接、关键词抽取、知识抽取、句法分析等），无监督或弱监督方法

This is a further development of the kdnuggets article on fake news classification by George McIntyre

Paper reading list in natural language processing, including dialogue systems and text generation related topics.

Pytorch implementation of "A Deep Reinforced Model for Abstractive Summarization" paper and pointer generator network

Multiple implementations for abstractive text summurization , using google colab

A simple strategy for training and finetuning NLP models for Arabic. Specify the parameters and just wait for the results. A simple design that makes use of the different tools in our NLP pipeline.

Text summarization using seq2seq in Keras

中文文本生成（NLG）之文本摘要（text summarization）工具包, 语料数据(corpus data), 抽取式摘要 Extractive text summary of Lead3、keyword、textrank、text teaser、word significance、LDA、LSI、NMF。（graph，feature，topic model，summarize tool or tookit）

No description or website provided.

A simple python implementation of the Maximal Marginal Relevance (MMR) baseline system for text summarization.

Abstractive text summarization based on deep learning and semantic content generalization

Python wrapper for evaluating summarization quality by ROUGE package

TextRank implementation for C#

reimplementing Neural Summarization by Extracting Sentences and Words

Gazeta: Dataset for automatic summarization of Russian news / Газета: набор данных для автоматического реферирования на русском языке

搜索所有中文NLP数据集，附常用英文NLP数据集

[NAACL2018] Entity Commonsense Representation for Neural Abstractive Summarization

No description or website provided.

[AAAI2021] Unsupervised Opinion Summarization with Content Planning

Tensorflow re-implementation of GAN for text summarization

Document Search Engine Tool

The Entire Transcript from the Office in Tidy Format

Natural Language Processing notes and implementations.

Python Framework for Extractive Text Summarization

Userscript that changes Clickbait headlines by headlines more honest to the news it links to.

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

Keras implementation for CrossNet in paper "Cross-Target Stance Classification with Self-Attention Networks"