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International Joint Conference on Knowledge Discovery, Knowledge Engineering, and Knowledge Management

IC3K 2014: Knowledge Discovery, Knowledge Engineering and Knowledge Management pp 84–98Cite as

Content-Based News Recommendation: Comparison of Time-Based System and Keyphrase-Based System

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 553))

Abstract

As internet resources are increasing at an unprecedented speed, users are tired of searching important ones among them. So, what users need and where they can find them are getting more important. Users require a personalized support in sifting through large amounts of available information according to their interests and recommendation systems try to answer this need. In this context, it is crucial to offer user friendly tools that facilitate faster and more accurate access to articles in digital newspapers. In this paper, a content-based news recommendation system for news domain is presented and contents of news articles are represented by words appearing in news articles or their keyphrases. News articles are recommended according to user dynamic and static profiles. User dynamic profiles reflect user past interests and recent interests play much bigger roles in the selection of recommendations. Our recommendation system is a complete content-based recommendation system together with categorization, summarization and news collection modules.

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Acknowledgements

This paper is a revised and extended version of our KDIR-2014 paper whose title is “A Media Tracking and News Recommendation System”.

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Authors and Affiliations

  1. Department of Computer Engineering, Hacettepe University, Ankara, Turkey

    Servet Tasci & Ilyas Cicekli

Authors
  1. Servet Tasci
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  2. Ilyas Cicekli
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Corresponding author

Correspondence to Ilyas Cicekli .

Editor information

Editors and Affiliations

  1. Instituto de Telecomunicações, Lisboa, Portugal

    Ana Fred

  2. Delft University of Technology, Delft, Zuid-Holland, The Netherlands

    Jan L. G. Dietz

  3. University of Madeira, Funchal, Portugal

    David Aveiro

  4. Henley Business School, University of Reading, Reading, United Kingdom

    Kecheng Liu

  5. INSTICC, Setubal, Portugal

    Joaquim Filipe

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Tasci, S., Cicekli, I. (2015). Content-Based News Recommendation: Comparison of Time-Based System and Keyphrase-Based System. In: Fred, A., Dietz, J., Aveiro, D., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2014. Communications in Computer and Information Science, vol 553. Springer, Cham. https://doi.org/10.1007/978-3-319-25840-9_6

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  • DOI: https://doi.org/10.1007/978-3-319-25840-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25839-3

  • Online ISBN: 978-3-319-25840-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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