Paper Title
Shortpress - News recommender summarizer translator with GPT3
Article Identifiers
Authors
Prasenjeet Shirsat , Sahil Golatkar , Pavan Gupta
Keywords
Abstract
In today's digital age, the consumption of news has been transformed by the availability of countless articles online. This abundance of information can make it difficult for readers to keep up with the latest events happening worldwide. Furthermore, language barriers can limit access to news articles written in unfamiliar languages. To address these challenges, news recommendation, summarizer, and translator apps have been developed using algorithms and machine learning techniques to recommend personalized news articles, summarize lengthy articles into shorter versions, and translate articles from one language to another. This paper aims to investigate the effectiveness of these apps in facilitating news consumption in the digital age. Through our evaluation of user experiences with these apps, we have identified their strengths and limitations. Our findings indicate that these apps are effective in improving news consumption, particularly for users who prefer personalized content and access news in their native language. However, we have also identified areas for improvement, such as enhancing the accuracy of machine translations and improving the summarization algorithms. Overall, our study provides valuable insights into the role of news recommendation, summarizer, and translator apps in facilitating news consumption in the digital age.
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How To Cite (APA)
Prasenjeet Shirsat , Sahil Golatkar , & Pavan Gupta (April-2023). Shortpress - News recommender summarizer translator with GPT3 . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), f601-f607. https://ijnrd.org/papers/IJNRD2304571.pdf
Issue
Volume 8 Issue 4, April-2023
Pages : f601-f607
Other Publication Details
Paper Reg. ID: IJNRD_192685
Published Paper Id: IJNRD2304571
Downloads: 000121977
Research Area: Information TechnologyÂ
Country: Mumbai, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2304571.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304571
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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