@article {236,
	title = {Extraction of children{\textquoteright}s friend relations from activity level},
	journal = {Journal of Digital Information Management},
	volume = {8},
	year = {2010},
	note = {Export Date: 10 July 2014},
	month = {2010},
	pages = {270 - 275},
	abstract = {This paper proposes the method to extract the friendship relations of children by using motion sensors. Children learn to fit into society through living in a group, and it{\textquoteright}s greatly influenced by their friend relations. Although preschool teachers need to observe them to assist in the growth of children{\textquoteright}s social progress and support the development each child{\textquoteright}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 tree diagram called dendrogram based on hierarchical clustering with recorded activity level. Also, the authors calculate children{\textquoteright}s "breadth" and "depth" of friend relations by using more than one dendrogram. When the authors record children{\textquoteright}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.},
	keywords = {Acceleration sensor, Clustering, Friendship relation, Pedometer},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79960659287\&partnerID=40\&md5=0f94aed0a83203638341b37b6cb7cc8b},
	author = {Haga, H. and Kaneda, S. and Kono, A. and Shintani, K.}
}
