Web feeds recommending system based on social data
Diego Oliveira Rodrigues, Sagar Gurung, Mihaela Cocea · 2015
Staying up to date with an individual's interests is a daunting task. An unstoppable number of growing online resources such as websites, blogs and news portals are providing information on various subjects and topics and it is provoking certain difficulties on individuals to identify the best resources or providers in order to trust and follow them continuously. Even though, some trustworthy useful sources have been identified, individuals are still losing them due to lack of management, not bookmarking the sites, carelessness, and so on. The proposed system in this paper will help internet users to figure out an approach to identify and recommend web feeders based on the social data collected from social channels like Facebook. It aims to provide a common place for internet users to read updates of their interest without having to perform search queries. It will also explain about the techniques used to filter data to generate recommended web feeds for users.