News Recommendation System Based on Multiple Classifiers

Abstract

In this project, we have designed, implemented and analyzed a news recommendation system. We used news articles dataset provided by BBC for the experiments. The system trains multiple classifiers on the training set, and use them to classify the news article chosen by the user. It then recommends m similar articles to the user. In this report, we discuss the methods we have implemented, results and their analysis. We have got best results with Naive Bayes algorithm, although we use combination of all the classifiers