Intelligent news aggregator and validator
| dc.contributor.author | Khan, Tabrez | |
| dc.date.accessioned | 2019-08-01T11:06:17Z | |
| dc.date.available | 2019-08-01T11:06:17Z | |
| dc.date.issued | 2019-05 | |
| dc.description.abstract | In recent years, the widespread of fake news is growing at an alarming rate. So much so that it has turned into a social issue. So recognizing and distinguishing fake news is an important task which must be accomplished with proper ideas and science behind it. In this project we have implemented an application, which will help users to discern fake news amongst all sort of news which is available on all over internet. The application will provide users with up to date news using simple news aggregation along with news validation, the news will be classified into three categories fake, genuine and neutral. The validation will be performed in two stages; first using machine learning and second based on news feedback provided by the users of our system. Using this two step method we can make a validation system that is dynamic and one that becomes more accurate with time. Keywords: Machine learning, Fake news | en_US |
| dc.identifier.uri | http://www.aiktcdspace.org:8080/jspui/handle/123456789/3204 | |
| dc.language.iso | en | en_US |
| dc.publisher | AIKTC | en_US |
| dc.relation.ispartofseries | PE0582; | |
| dc.subject | Project Report - CO | en_US |
| dc.title | Intelligent news aggregator and validator | en_US |
| dc.type | Project Report | en_US |