SemKnowNews: A Semantically Inclined Knowledge Driven Approach for Multi-source Aggregation and Recommendation of News with a Focus on Personalization

The availability of digital devices has increased throughout the world exponentially owing to which the average reader has shifted from offline media to online sources. There are a lot of online sources which aggregate and provide news from various outlets but due to the abundance of content there is an overload to the user. Personalization is therefore necessary to deliver interesting content to the user and alleviate excessive information. In this paper, we propose a novel semantically inclined knowledge driven approach for multi-source aggregation and recommendation of news with a focus on personalization to address the aforementioned issues. The proposed approach surpasses the existing work and yields an accuracy of 96.62%