This paper proposes a method to extract the friendship relations of children by using motion sensors. Children learn to fit into society through living in a group, and this is greatly influenced by their friendship relations. Although preschool teachers need to observe them to assist in the growth of children's social progress and support the development of 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 the authors make a tree diagram called a dendrogram based on hierarchical clustering with recorded activity level. Also, the authors calculate children's "breadth" and "depth" of friend relations by using more than one dendrogram. When the authors recorded children's activity level in a certain kindergarten for two months and evaluated the proposed method, the results usually coincided with the remarks of teachers about the children. © 2011 Springer-Verlag.
CITATION STYLE
Haga, H., & Kaneda, S. (2011). Mining the friendship relation of children from the activity data. In Communications in Computer and Information Science (Vol. 252 CCIS, pp. 706–716). https://doi.org/10.1007/978-3-642-25453-6_59
Mendeley helps you to discover research relevant for your work.