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Multimedia Tools and Applications

, Volume 77, Issue 4, pp 4339–4353 | Cite as

A news-topic recommender system based on keywords extraction

  • Zihuan Wang
  • Kyusup Hahn
  • Youngsam Kim
  • Sanghyup Song
  • Jong-Mo Seo
Article

Abstract

In recent years, internet news has become one of the most important channels for information acquisition, as more and more people read news through internet connected computers, tablets, and smart phones, etc. Owing to the constantly reproduced news, the number of online media increases dramatically and the volume of news also expands rapidly. Consequently, obtaining primary information from the internet is of great interest. This paper presents a news-topic recommender system based on keywords extraction. It is shown that the proposed system is very effective in acquiring specific topics within any specific period of time.

Keywords

Internet news Recommender system Keywords extraction Topic extraction 

Notes

Acknowledgements

This work was supported by Seoul National University Big Data Institute through the Data Science Research Project 2015.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  • Zihuan Wang
    • 1
  • Kyusup Hahn
    • 2
  • Youngsam Kim
    • 3
  • Sanghyup Song
    • 4
  • Jong-Mo Seo
    • 1
  1. 1.Department of Electrical and Computer EngineeringSeoul National UniversityGwanak-guSouth Korea
  2. 2.Department of CommunicationSeoul National UniversityGwanak-guSouth Korea
  3. 3.Department of LinguisticsSeoul National UniversityGwanak-guSouth Korea
  4. 4.Big Data InstituteSeoul National UniversityGwanak-guSouth Korea

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