一、自动文本摘要

   （1）Sequence-to-Sequence with Attention Model for Text Summarization:

       https://github.com/tensorflow/models/tree/master/research/textsum

       论文：Rush et al. A Neural Attention Modelfor Sentence Summarization.

   （2）Preparing a dataset for TensorFlow text summarization (TextSum) model：（数据处理的参考）

       https://github.com/surmenok/TextSum

   （3）传统文本摘要，抽取式的

       https://github.com/zkwi/textSummary

         （4）Uses Recurrent Neural Network (LSTM and GRU units) for developing Seq2Seq Encoder Decoded model with and without attention mechanism for summarization of amazon food reviews into abstractive tips：

       https://github.com/harpribot/deep-summarization

• Encoder Decoder Model

• DataSet

• Installation Requirements

• Run Instructions

• Documentation

• References

   （5）fasttext和sentence_extractor代码参考：

       https://github.com/yangze01/NeuralSummarization/tree/master/model

    （6）tl-dr (abstractive text summarization)：GRU encoder-decoder model and a QRNNenc + RNNdec model.

       https://github.com/padelson/tl-dr2

   （7）Abstractive-Summarization-using-Query-based-Deep-Neural-Attention-Models

        https://github.com/genzen2103/Abstractive-Summarization-using-Query-based-Deep-Neural-Attention-Models

       （8）A neural news summarization tool. Collect google news topics, crawl related news articles, generate summaries.Including the following units:    

1. BasicSum: traditional freq-based news-summary generator.

2. LSTM-Attetion: Neural network model that summarizes news.

3. WikiNews Dataset: A list of news articles crawled from WikiNews, every element(event) of the list contains at least three articles from mainstream website talking about the event.

      https://github.com/qinenergy/NewsSum

   （9） Sequence to sequence model for abstractive text summarization

       https://github.com/weichengzhang/Summarization

   （10）

二、seq2seq学习

   （1）Sequence to sequence (seq2seq) learning Using TensorFlow.

       https://github.com/JayParks/tf-seq2seq

   （2）Neural Sequence Learning Using TensorFlow

       https://github.com/ufal/neuralmonkey

   （3）生成古诗

       https://github.com/Disiok/poetry-seq2seq

   （4）

三、机器阅读理解

   （1）Bi-directional Attention Flow for Machine Comprehension

       https://github.com/allenai/bi-att-flow

四、数据可视化

   （1）A tool for finding distinguishing terms in small-to-medium sizedcorpora, and presenting them in a sexy, interactive scatter plot withnon-overlapping term labels.  Exploratory data analysis just got more fun.

       https://github.com/JasonKessler/scattertext