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TORA: Text Summarization Using Optical Character Recognition and Attention Neural Networks
(Springer Science and Business Media Deutschland GmbH, 2022) Sneha, H.R.; Annappa, B.
Text Summarization is the process of creating a short and coherent version of a longer document that holds the same meaning as that of the original data. This article illustrates the technique to read the text in a printed document (such as newspaper, brochure, web document, etc.) and generate a summary of text. The method proposed is named Text Summarization using Optical Character Recognition and Attention Neural Networks (TORA). TORA can perform extractive summarization of a news article with the aid of Recurrent Neural Networks, Bidirectional Long Short-Term Memory, and Bahadanu Attention Network. The experimental results of the proposed method are promising. The experimental results have shown 80% accuracy in producing the summary from the large text document. Â© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.