Bibliometric Research on Recommender System Research Based on Web of Science

Yafei Di

doi:doi:10.11648/j.si.20170505.11

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Bibliometric Research on Recommender System Research Based on Web of Science

Yafei Di

Published in Science Innovation (Volume 5, Issue 5)

Received: 19 July 2017 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), 2017. 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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ACS 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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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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TY  - JOUR
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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Author Information

Yafei Di

Literature Information Center, Fudan University, Shanghai, China

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APA Style

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

Copy | Download

ACS 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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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

Copy | Download

@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}
}

Copy | Download

TY  - JOUR
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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