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Research on Data Mining Technology Based on Weka Platform

Received: 6 June 2017     Published: 8 June 2017
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Abstract

Research uses Weka big data mining technology platform to analyze the data.The association rules miningmethods of discrete sample data by Weka technology,using SimpleKMeans clustering algorithm for clustering analysisof thesimulated sample data mining, common features of each type of data and the difference data between differentclusters from where, for a variety of data region division, analysis of different regions of the data distribution. For example, mining research project, a school in the college entrance examination scores data for the simulation sample, in Chinese, math and English college entrance examination scores as the object of analysis of large data mining, thepaper in science classes, the language, the total scores were compared with the distribution.The integrated use of statistical analysis and data mining technology, mining analysis on college entrance examination data deeply, get useful informationwith performance clustering, has strong theoreticalvalue, can help to the college entrance examination reform, give some guidance to high school education.

Published in Science Discovery (Volume 5, Issue 4)
DOI 10.11648/j.sd.20170504.18
Page(s) 287-292
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

Data Mining, Cluster Analysis, Weka Platform, College Entrance Examination

References
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    Wang Pan Zao. (2017). Research on Data Mining Technology Based on Weka Platform. Science Discovery, 5(4), 287-292. https://doi.org/10.11648/j.sd.20170504.18

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    Wang Pan Zao. Research on Data Mining Technology Based on Weka Platform. Sci. Discov. 2017, 5(4), 287-292. doi: 10.11648/j.sd.20170504.18

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    Wang Pan Zao. Research on Data Mining Technology Based on Weka Platform. Sci Discov. 2017;5(4):287-292. doi: 10.11648/j.sd.20170504.18

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  • @article{10.11648/j.sd.20170504.18,
      author = {Wang Pan Zao},
      title = {Research on Data Mining Technology Based on Weka Platform},
      journal = {Science Discovery},
      volume = {5},
      number = {4},
      pages = {287-292},
      doi = {10.11648/j.sd.20170504.18},
      url = {https://doi.org/10.11648/j.sd.20170504.18},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20170504.18},
      abstract = {Research uses Weka big data mining technology platform to analyze the data.The association rules miningmethods of discrete sample data by Weka technology,using SimpleKMeans clustering algorithm for clustering analysisof thesimulated sample data mining, common features of each type of data and the difference data between differentclusters from where, for a variety of data region division, analysis of different regions of the data distribution. For example, mining research project, a school in the college entrance examination scores data for the simulation sample, in Chinese, math and English college entrance examination scores as the object of analysis of large data mining, thepaper in science classes, the language, the total scores were compared with the distribution.The integrated use of statistical analysis and data mining technology, mining analysis on college entrance examination data deeply, get useful informationwith performance clustering, has strong theoreticalvalue, can help to the college entrance examination reform, give some guidance to high school education.},
     year = {2017}
    }
    

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    T1  - Research on Data Mining Technology Based on Weka Platform
    AU  - Wang Pan Zao
    Y1  - 2017/06/08
    PY  - 2017
    N1  - https://doi.org/10.11648/j.sd.20170504.18
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    JO  - Science Discovery
    SP  - 287
    EP  - 292
    PB  - Science Publishing Group
    SN  - 2331-0650
    UR  - https://doi.org/10.11648/j.sd.20170504.18
    AB  - Research uses Weka big data mining technology platform to analyze the data.The association rules miningmethods of discrete sample data by Weka technology,using SimpleKMeans clustering algorithm for clustering analysisof thesimulated sample data mining, common features of each type of data and the difference data between differentclusters from where, for a variety of data region division, analysis of different regions of the data distribution. For example, mining research project, a school in the college entrance examination scores data for the simulation sample, in Chinese, math and English college entrance examination scores as the object of analysis of large data mining, thepaper in science classes, the language, the total scores were compared with the distribution.The integrated use of statistical analysis and data mining technology, mining analysis on college entrance examination data deeply, get useful informationwith performance clustering, has strong theoreticalvalue, can help to the college entrance examination reform, give some guidance to high school education.
    VL  - 5
    IS  - 4
    ER  - 

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Author Information
  • Department of Information and Engineering, Sichuan Tourism University, Chengdu, China

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