Summarization
With nltk - words assigned weighted frequency, summed up in sentences and then selected based on the top K scored sentences.
NAMAS - Neural attention model for abstractive summarization, -Neural Attention Model for Abstractive Sentence Summarization - summarizes single sentences quite well, github
Unsupervised methods using sentence emebeddings (long and good) - using sent2vec, clustering, picking by rank
Abstractive
Facebooks neural attention network NAMAS on git
Keywords extraction
Extractive summarization
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
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