Automated Extraction Of Multiple News

dc.contributor.authorAzmat Ullah , Anum Riaz , Sarah Akbar Khan
dc.contributor.authorFA17-BSE-022 , FA17-BSE-082 , FA17-BSE-100
dc.contributor.authorShahid Bhatti
dc.contributor.authorLHR TP 7031
dc.date.accessioned2026-02-19T04:22:48Z
dc.date.issued2021
dc.description.abstractNews provides valuable information about the current situation. In the era of information and technology, People use different websites to get different news. These requirements raised the need for the system, which is Automated Extraction of Multiple news (AEMN). It will collect information from multiple online platforms and publish them on a single end-point. It also shows relevant news to the user. Moreover, it classifies news based on a different category, and news will be added to the relevant category. The source of the news is also provided to avoid copyright issues. In the future, AEMN is emerging as everyone wants to see authentic and similar information without searching too much or consuming time. In order to make the system more interesting, a different section will be added, such as auto-classification, similar/relevant news, and most trending news from different platforms without any manual effort. The system will be using Machine Learning algorithms to resolve all manual settings and searching.
dc.identifier.urihttps://repository.cuilahore.edu.pk/handle/123456789/1902
dc.language.isoen
dc.publisherLibrary Information Services, COMSATS University Islamabad, Lahore Campus
dc.relation.ispartofseriesLHR TP 7031
dc.subjectTECHNOLOGY::Information technology::Computer science
dc.titleAutomated Extraction Of Multiple News
dc.typeThesis

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