Article Abstractive text summarization using LSTM-CNN based deep learning

Article Effective Deep Learning Approaches for Summarization of Legal Texts

The techniques may include LSTM and GRU. Also, you can use some attention mechanism which performs best, especially in NLP problems. My fellow works on this project and it gives better results.

for your reading: https://blog.floydhub.com/attention-mechanism/

I have worked with Text Rank and BERT for summarization tasks and BERT seems to work better. Here's a link to its python package: https://pypi.org/project/bert-extractive-summarizer/

You will need to install it in your python environment version:3.6 along with all the packages given in its github repo here: https://github.com/dmmiller612/bert-extractive-summarizer/blob/master/requirements.txt

Thank you Cristian Ramos-Vera , Muhammad Mudasser Afzal and Akshara Goyal

You can used topic modeling algorithm ( LDA, LSI, NMF) and also lexical database

WordNet synset for text clustering from unsupervised text .besides ,you can use Tf-idf or word2vec but BERT better work than Word2vec .

Thank you Shadikur Rahman