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  • 标题:Extraction of Children's Friendship Relation from Activity Level
  • 本地全文:下载
  • 作者:Aki Kono ; Kimio Shintani ; Takuya Katsuki
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2008
  • 卷号:23
  • 期号:6
  • 页码:402-411
  • DOI:10.1527/tjsai.23.402
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:Children learn to fit into society through living in a group, and it's greatly influenced by their friend relations. Although preschool teachers need to observe them to assist in the growth of children's social progress and support the development each child's personality, only experienced teachers can watch over children while providing high-quality guidance. To resolve the problem, this paper proposes a mathematical and objective method that assists teachers with observation. It uses numerical data of activity level recorded by pedometers, and we make tree diagram called dendrogram based on hierarchical clustering with recorded activity level. Also, we calculate children's ``breadth'' and ``depth'' of friend relations by using more than one dendrogram. When we record children's activity level in a certain kindergarten for two months and evaluated the proposed method, the results usually coincide with remarks of teachers about the children.
  • 关键词:activity level ; association ; clustering ; data minig ; lifelog
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