Top 10 algorithms in data mining

Article Properties
  • Language
    English
  • DOI (url)
    10.1007/s10115-007-0114-2
  • Publication Date
    2007/12/04
  • Journal
    Knowledge and Information Systems
  • Indian UGC (Journal)
  • Refrences
    92
  • Citations
    2,329
  • Xindong Wu
  • Vipin Kumar
  • J. Ross Quinlan
  • Joydeep Ghosh
  • Qiang Yang
  • Hiroshi Motoda
  • Geoffrey J. McLachlan
  • Angus Ng
  • Bing Liu
  • Philip S. Yu
  • Zhi-Hua Zhou
  • Michael Steinbach
  • David J. Hand
  • Dan Steinberg
Cite
Wu, Xindong, et al. “Top 10 Algorithms in Data Mining”. Knowledge and Information Systems, vol. 14, no. 1, 2007, pp. 1-37, https://doi.org/10.1007/s10115-007-0114-2.
Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G. J., Ng, A., Liu, B., Yu, P. S., Zhou, Z.-H., Steinbach, M., Hand, D. J., & Steinberg, D. (2007). Top 10 algorithms in data mining. Knowledge and Information Systems, 14(1), 1-37. https://doi.org/10.1007/s10115-007-0114-2
Wu X, Kumar V, Ross Quinlan J, Ghosh J, Yang Q, Motoda H, et al. Top 10 algorithms in data mining. Knowledge and Information Systems. 2007;14(1):1-37.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Science (General)
Cybernetics
Information theory
Technology
Electrical engineering
Electronics
Nuclear engineering
Telecommunication
Technology
Technology (General)
Industrial engineering
Management engineering
Information technology
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Citations Analysis
Category Category Repetition
Science: Mathematics: Instruments and machines: Electronic computers. Computer science841
Technology: Engineering (General). Civil engineering (General)505
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics484
Technology: Mechanical engineering and machinery383
Science: Science (General): Cybernetics: Information theory357
The first research to cite this article was titled Learning decision tree for ranking and was published in 2008. The most recent citation comes from a 2024 study titled Learning decision tree for ranking . This article reached its peak citation in 2022 , with 284 citations.It has been cited in 1,001 different journals, 17% of which are open access. Among related journals, the IEEE Access cited this research the most, with 83 citations. The chart below illustrates the annual citation trends for this article.
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