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generating and summarizing worldwide covid-19 reports using abstractive and extractive nlp
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نویسنده
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feili arman ,feili amin ,badrooh iman
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منبع
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اولين كنفرانس بين المللي و ششمين كنفرانس ملي كامپيوتر، فناوري اطلاعات و كاربردهاي هوش مصنوعي - 1401 - دوره : 1 - اولین کنفرانس بین المللی و ششمین کنفرانس ملی کامپیوتر، فناوری اطلاعات و کاربردهای هوش مصنوعی - کد همایش: 01220-12911 - صفحه:0 -0
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چکیده
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Since the beginning of the covid-19 outbreak, each country has experienced substantial changes regarding the burden of the disease. accordingly, the volume of covid-19 data has expanded in size and variety.[1] authorities, news services, and the public find it too challenging to stay aware of new happenings about the disease. it is, therefore, vital to help the public and policymakers catch up with the latest news about the pandemic using an easy-to-understand report. this project aims to produce an accessible application in python that can retrieve covid-19 data, generate a well-structured text report, and create two reviews based on the extractive and abstractive nlp (natural language processing) summarization approaches without any grammatical errors
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کلیدواژه
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covid-19 ,nlp ,data2text ,abstractive text summarization ,extractive text summarization ,grammar-check
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آدرس
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, iran, , iran, , iran
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Authors
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