Web feeds recommending system based on social data

Diego Oliveira Rodrigues, Sagar Gurung, Mihaela Cocea

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

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.
Original languageEnglish
Title of host publicationENCOINFO — congresso de computação e sistemas de informação
Publication statusPublished - Oct 2015
Event2015 Congress of Computing and Information Systems - , United Kingdom
Duration: 19 Oct 201522 Oct 2015

Publication series

NameENCOINFO
ISSN (Print)2447-0767

Conference

Conference2015 Congress of Computing and Information Systems
Abbreviated titleENCOINFO
Country/TerritoryUnited Kingdom
Period19/10/1522/10/15

Keywords

  • Recommender Systems
  • Web feeds
  • collaborative filtering

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