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Machine & Deep Learning Compendium
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Summarization

Jatana
  1. 1.
    ​Email summarization but with a great intro (see image above)​
  2. 2.
    ​With nltk - words assigned weighted frequency, summed up in sentences and then selected based on the top K scored sentences.
  3. 3.
    ​Awesome-text-summarization on github​
  4. 4.
    ​Methodical review of abstractive summarization​
  5. 5.
    ​Medium on extractive and abstractive - overview with the abstractive code ​
  6. 6.
    ​NAMAS - Neural attention model for abstractive summarization, -Neural Attention Model for Abstractive Sentence Summarization - summarizes single sentences quite well, github​
  7. 7.
    ​Abstractive vs extractive, blue intro​
  8. 8.
    ​Intro to text summarization​
  9. 9.
    ​Paper: survey on text summ, arxiv​
  10. 10.
    ​Very short intro​
  11. 11.
    ​Intro on encoder decoder​
  12. 12.
    ​Unsupervised methods using sentence emebeddings (long and good) - using sent2vec, clustering, picking by rank
  13. 13.
    ​Abstractive summarization using bert for sota​
  14. 14.
    Abstractive
    1. 1.
      ​Git1: uses pytorch 0.7, fails to work no matter what i did​
    2. 2.
      ​Git2, keras code for headlines, missing dataset​
    3. 3.
      ​Encoder decoder in keras using rnn, claims cherry picked results, the majority is prob not as good​
    4. 4.
      ​A lot of Text summarization algos on git, using seq2seq, using many methods, glove, etc - ​
    5. 5.
      ​Summarization with point generator networks on git
    6. 6.
      ​Summarization based on gigaword claims SOTA​
    7. 7.
      ​Facebooks neural attention network NAMAS on git
    8. 8.
      ​Medium on summarization with tensor flow on news articles from cnn​
  15. 15.
    Keywords extraction
    1. 1.
      ​The best text rank presentation​
    2. 2.
      ​Text rank by gensim on medium​
    3. 3.
      ​Text rank 2​
    4. 4.
      ​Text rank - custom code, extractive vs abstractive, how to use, some more theoretical info and page rank intuition.​
    5. 5.
      ​Text rank paper​
    6. 6.
      ​Improving textrank using adjectival and noun compound modifiers​
    7. 7.
      Unread - New similarity function paper for textrank​
  16. 16.
    Extractive summarization
    1. 1.
      ​Text rank with glove vectors instead of tf-idf as in the paper (sam)
    2. 2.
      ​Medium with code on extractive using word occurrence similarity + cosine, pick top based on rank​
    3. 3.
      ​Medium on methods, freq, LSA, linking words, sentences,bayesian, graph ranking, hmm, crf, ​
    4. 4.
      ​Wiki on automatic summarization, abstractive vs extractive, ​
    5. 5.
      ​Pyteaser, textteaset, lexrank, pytextrank summarization models & rouge-1/n and blue metrics to determine quality of summarization models Bottom line is that textrank is competitive to sumy_lex
    6. 6.
      ​Sumy​
    7. 7.
      ​Pyteaser​
    8. 8.
      ​Pytextrank​
    9. 9.
      ​Lexrank​
    10. 10.
      ​Gensim tutorial on textrank​
    11. 11.
      ​Email summarization​
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