Marathi text summarization using Neural Networks
Anishka Chaudhari, Akash Dole, D.B. Kadam · International Journal for Advance Research and Development · 2019
The internet is comprised of web pages, news articles, status updates, blogs and much more. It is difficult to navigate through this data as it is unstructured and usually discursive. Condensed versions of this data are generated so we can navigate it more effectively as well as check whether the larger documents contain the information that we are looking for. We propose a system for extractive text summarization method using neural networks for Marathi text. Extractive summaries or extracts are produced by identifying important sentences or words which are directly selected from the document. To perform extractive text summarization we propose to use a Recurrent Neural Network (RNN) – a type of neural network that can perform calculations on sequential data (e.g. sequences of words) – as it has become the standard approach for many Natural Language Processing tasks. The translation of the Marathi text to English will be done using the Google translate API for this proposed system.