Abstractive Text Summarization
Keywords:Text summarization, Natural Language Processing, Abstractive
The objective of this project is to imitate the fundamental concepts of this research of state-of-the-art abstract text repeated models to examine various processes until the work had a reasonable functional basis. This work was motivated by various research papers with several novel features that have achieved remarkable achievement. In multiple iterations, this study will enhance the adoption of words, complexity of decoders, and attentiveness. In addition, a bilinear care mechanism adds the last model, increasing the rate of loss of training. Text Summarization is one of the most experimental subjects in natural language processing that reduces the size of a document while keeping its meaning. Summary techniques are classed as extractive or abstractive based on whether the precise phrases in the original text are produced or whether new phrases are constructed using natural language methods. Extractive summaries have been carefully examined and a developed state has been obtained. Abstractive summary is the focus of the research. Due to the ins and outs of the text, abstractive summarization is challenging.
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