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Future Information Technology pp 177–183Cite as

A Collaborative Filtering Recommendation Algorithm Based on Tag Clustering

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 276))

Abstract

Social tagging system is applied widely in Web 2.0 nowadays, which is designed to express the user’s interest and willingness more accurately. And tag clustering is an important research topic in personalized recommendation of social tagging systems. This paper presents a personalized recommendation method based on tag clustering. In this method, tag clustering is realized by calculating the tag similarity, and recommendation is made based on tag clustering results. Experiments using CiteULike data sets show, proposed method can optimize ranking of objective resources, and help users to discover new resources easier.

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References

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Author information

Authors and Affiliations

  1. The School of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100081, China

    Rujuan Liu & Zhendong Niu

Authors
  1. Rujuan Liu
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  2. Zhendong Niu
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Corresponding author

Correspondence to Rujuan Liu .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. SEECS, University of Ottawa, Ottawa, Ontario, Canada

    Ivan Stojmenovic

  3. School of Information and Communication Engineering, Chungbuk National University, Chungbuk, Korea, Republic of (South Korea)

    Min Choi

  4. Department of Languages and Informatics Systems, Polytechnic University of Catalonia, Barcelona, Spain

    Fatos Xhafa

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© 2014 Springer-Verlag Berlin Heidelberg

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Cite this paper

Liu, R., Niu, Z. (2014). A Collaborative Filtering Recommendation Algorithm Based on Tag Clustering. In: Park, J., Stojmenovic, I., Choi, M., Xhafa, F. (eds) Future Information Technology. Lecture Notes in Electrical Engineering, vol 276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40861-8_27

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  • DOI: https://doi.org/10.1007/978-3-642-40861-8_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40860-1

  • Online ISBN: 978-3-642-40861-8

  • eBook Packages: EngineeringEngineering (R0)

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