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  • 标题:Improvement of Curriculum Analyzing System utilizing Syllabus-Term Co-clustering
  • 本地全文:下载
  • 作者:Takayuki NOZAWA ; Masaaki IDA ; Fuyuki YOSHIKANE
  • 期刊名称:知能と情報
  • 印刷版ISSN:1347-7986
  • 电子版ISSN:1881-7203
  • 出版年度:2005
  • 卷号:17
  • 期号:5
  • 页码:569-586
  • DOI:10.3156/jsoft.17.569
  • 出版社:Japan Society for Fuzzy Theory and Intelligent Informatics
  • 摘要:Comprehending the features of curricula provided by various higher education institutions is significant in designing and evaluating a curriculum. To facilitate comprehension of the curricula's features, Curriculum Analyzing System has been developed by Nozawa et al. utilizing document-clustering of syllabus data. However, speeding up and improvement of interactivity in the clustering procedure remained to be accomplished. In this article, a co-clustering method based on graph partitioning is introduced in order to improve the curriculum analyzing system. We show that recursive application of co-clustering to syllabus-term data makes the system more efficient and enables the users to understand the curricula's features more interactively.
  • 关键词:co-clustering ; document clustering ; curriculum ; syllabus ; interactive system
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