Abstractive text summarization done with the help of LSTMs using encoder-decoder model which was able to achieve accuracy of 77.27% on training set and cumulative BLEU-4 score of 0.8800 on test set.

In this paper, we propose a novel neural network model called RNN Encoder-Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a fixed-length vector ...

Text Auto-complete feature suggests a stream of words which complete a user's text as the user types each character. Such a feature is used in search engines, email programs, source code editors, ...

In the above section, we have discussed how the encoder-decoder model works well with the sequential information and how the time series is sequential data. This section of the article will be a ...

RNN Encoder-Decoder in PyTorch. pytorch attention sequence-to-sequence rnn-encoder-decoder. Updated Aug 7, 2024; Python; venkat-a / Text_Processing_RNN_LSTM. Star 0 ... Automatically describing the ...

Text Auto-complete feature suggests a stream of words which complete a user's text as the user types each character. Such a feature is used in search engines, email programs, source code editors, ...