News are newly received notable information concerning place or group or things. Everyone is concerned with the news on their own way. But it is hard to categorize the interest of news readers with one another. A recommendation system would be great idea to make a news reader familiar with only those contents he/she want to know about. So, we are developing a real news recommendation system where we recommend the only news readers the true news of their interests. Plus there is a separate section for the Fake News Detection where when are news are given input, they can be validated as true or false. We are doing this because in the real-life scenario people face problem reading the news article of their choice and we aim to solve this problem. The output of this work can be implemented in various online news portals.
This project is the combined work of following members:
Special thanks to:
Abstract
In the digital world of enormous flow of data, we could find ourselves at various crossroads that lead to different platforms containing the needed data. Between the options of saving time or checking all platforms, our project merges the crossroads to become one. The project “Real News Recommendation System” utilizes the click behaviour of users and recommends them the best news articles by analysing if the news is fake or not. We felt that a project like “Real News Recommendation System” was needed for the technological aspects relating closely to our nation and the emergence of its numerous news portals. We have created the project as a web application using Python and Django along with the concepts of NLP (Natural Language Processing). The project utilizes the concept of recommendation of online news understanding the importance of relevant news recommendation for the users who read news every day. We hope that our project can impact all Nepali news readers and give them an essence of multi- dimensionality in a concise and time saving manner.