• DocumentCode
    1848362
  • Title

    Content-based School Assignment Cluster Algorithm

  • Author

    Feng, Juan ; Zhao, Jie ; Zhan, Guohua

  • Author_Institution
    Hangzhou Normal Univ., Hangzhou
  • fYear
    2008
  • fDate
    18-21 Nov. 2008
  • Firstpage
    2614
  • Lastpage
    2618
  • Abstract
    Based on the clustering technology in data mining, we aimed to establish a new schoolwork identifying mechanism. In order to let the normal answer can adapt to actual situations better, we first generalized the normal answer, and then calculated the similarity between every sample and normal answer, as well as similar degree between school works. Based on the similarity, we clustered all school work texts, and gave the one most similar to the standard answer the highest grade. Certainly, the number of clusters is appointed by teacher. Finally, we calculated the similarity between each cluster group and the standard answer, and in accordance with these calculation results, determined the final grade of the cluster groups.
  • Keywords
    computer aided instruction; data mining; pattern clustering; teaching; text analysis; content-based school assignment cluster algorithm; data mining; normal answer; school work text; schoolwork identifying mechanism; teaching; text clustering; text similarity; Clustering algorithms; Data mining; Education; Educational institutions; Frequency; Humans; Internet; Plagiarism; Statistics; Text categorization; Data mining; Generalization; Text clustering; Text similarity; Vector;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3398-8
  • Electronic_ISBN
    978-0-7695-3398-8
  • Type

    conf

  • DOI
    10.1109/ICYCS.2008.234
  • Filename
    4709390