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Bibliometric Research on Recommender System Research Based on Web of Science

Received: 19 July 2017    Accepted:     Published: 19 July 2017
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Abstract

Since recommender systems are widely used in many fields, it is important to analyze the present situation of recommender system and its development trends. This paper measured and visualized the related papers between 1996 and 2015 based on Web of Science™ Core Collection. Based on annual publications and times cited, journal distribution and research fields, high-frequency authors and cited references, countries or regions and institutions, high-frequency keywords and bursts keywords, this paper summarized the current situation of recommender system and forecasted the development trends of recommender system. This paper determined that the research hotspot of recommender systems was method for recommender system and the application in the field of electronic commerce, science basic research, electronic learning and knowledge management. The future research hotspot will still be the application of the recommender system.

Published in Science Innovation (Volume 5, Issue 5)
DOI 10.11648/j.si.20170505.11
Page(s) 250-255
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Web of Science, Recommender System, Bibliometrics, CiteSpace

References
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    Yafei Di. (2017). Bibliometric Research on Recommender System Research Based on Web of Science. Science Innovation, 5(5), 250-255. https://doi.org/10.11648/j.si.20170505.11

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    Yafei Di. Bibliometric Research on Recommender System Research Based on Web of Science. Sci. Innov. 2017, 5(5), 250-255. doi: 10.11648/j.si.20170505.11

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    AMA Style

    Yafei Di. Bibliometric Research on Recommender System Research Based on Web of Science. Sci Innov. 2017;5(5):250-255. doi: 10.11648/j.si.20170505.11

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  • @article{10.11648/j.si.20170505.11,
      author = {Yafei Di},
      title = {Bibliometric Research on Recommender System Research Based on Web of Science},
      journal = {Science Innovation},
      volume = {5},
      number = {5},
      pages = {250-255},
      doi = {10.11648/j.si.20170505.11},
      url = {https://doi.org/10.11648/j.si.20170505.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20170505.11},
      abstract = {Since recommender systems are widely used in many fields, it is important to analyze the present situation of recommender system and its development trends. This paper measured and visualized the related papers between 1996 and 2015 based on Web of Science™ Core Collection. Based on annual publications and times cited, journal distribution and research fields, high-frequency authors and cited references, countries or regions and institutions, high-frequency keywords and bursts keywords, this paper summarized the current situation of recommender system and forecasted the development trends of recommender system. This paper determined that the research hotspot of recommender systems was method for recommender system and the application in the field of electronic commerce, science basic research, electronic learning and knowledge management. The future research hotspot will still be the application of the recommender system.},
     year = {2017}
    }
    

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    T1  - Bibliometric Research on Recommender System Research Based on Web of Science
    AU  - Yafei Di
    Y1  - 2017/07/19
    PY  - 2017
    N1  - https://doi.org/10.11648/j.si.20170505.11
    DO  - 10.11648/j.si.20170505.11
    T2  - Science Innovation
    JF  - Science Innovation
    JO  - Science Innovation
    SP  - 250
    EP  - 255
    PB  - Science Publishing Group
    SN  - 2328-787X
    UR  - https://doi.org/10.11648/j.si.20170505.11
    AB  - Since recommender systems are widely used in many fields, it is important to analyze the present situation of recommender system and its development trends. This paper measured and visualized the related papers between 1996 and 2015 based on Web of Science™ Core Collection. Based on annual publications and times cited, journal distribution and research fields, high-frequency authors and cited references, countries or regions and institutions, high-frequency keywords and bursts keywords, this paper summarized the current situation of recommender system and forecasted the development trends of recommender system. This paper determined that the research hotspot of recommender systems was method for recommender system and the application in the field of electronic commerce, science basic research, electronic learning and knowledge management. The future research hotspot will still be the application of the recommender system.
    VL  - 5
    IS  - 5
    ER  - 

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  • Literature Information Center, Fudan University, Shanghai, China

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