Artificial Intelligence and Communication Technologies
A News Recommender System: Implementation and Analysis
Authors: Shweta Rani, Ankit Rathore, Apoorv Nandan and Arjun Bhatt
Publishing Date: 09-09-2022
ISBN: 978-81-955020-5-9
Abstract
In the past few years, the need of prediction has increased rapidly. Predicting the purchase, reading of news, buying food items are a few popular interests of researchers and marketing people as well. Newspapers are quite essential to urge information concerning recent activity and general awareness for all age groups. Varied solutions are being developed to convert paper News systems to digital news and it has become a standard for all news companies. A recommendation system has been proposed and developed for suggestions to the user. Researchers have developed many algorithms for developing the recommendation system. Each approach has its pros and cons. In this paper, we have studied different approaches for news recommendation systems and developed a content-based filtering model for recommending news articles to the user. The articles with more euclidean similarity have higher chances of suggesting to the user.
Keywords
Recommender system, Content based Filtering, Collaborative Filtering, News Recommendation.
Cite as
Shweta Rani, Ankit Rathore, Apoorv Nandan and Arjun Bhatt, "A News Recommender System: Implementation and Analysis", In: Saroj Hiranwal and Garima Mathur (eds), Artificial Intelligence and Communication Technologies, SCRS, India, 2022, pp. 245-261. https://doi.org/10.52458/978-81-955020-5-9-26