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Pagerank-Like Algorithm for Ranking News Stories and News Portals

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ICT Innovations 2013 (ICT Innovations 2013)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 231))

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Abstract

News websites are one of the most visited destinations on the web. As there are many news portals created on a daily basis, each having its own preference for which news are important, detecting unbiased important news might be useful for users to keep up to date with what is happening in the world. In this work we present a method for identifying top news in the web environment that consists of diversified news portals. It is commonly know that important news generally occupies visually significant place on a home page of a news site and that many news portals will cover important news events. We used these two properties to model the relationship between homepages, news articles and events in the world, and present an algorithm to identify important events and automatically calculate the significance, or authority, of the news portals.

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References

  1. Newspaper Association of America (2009), http://www.naa.org/News-and-Media/Press-Center/Archives/2009/Newspaper-websites-attract-more-than-70-million-visitors.aspx

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Correspondence to Igor Trajkovski .

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© 2014 Springer International Publishing Switzerland

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Trajkovski, I. (2014). Pagerank-Like Algorithm for Ranking News Stories and News Portals. In: Trajkovik, V., Anastas, M. (eds) ICT Innovations 2013. ICT Innovations 2013. Advances in Intelligent Systems and Computing, vol 231. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01466-1_8

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  • DOI: https://doi.org/10.1007/978-3-319-01466-1_8

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-01465-4

  • Online ISBN: 978-3-319-01466-1

  • eBook Packages: EngineeringEngineering (R0)

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