A study of social graph analysis for preschool education using face authentication: Pruning for centrality optimization in graph analysis

Tsuyoshi Tomioka, M. Hasegawa, Shojiro Shiraishi
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Abstract

Social graph analysis for preschool education is discussed in this paper. Our social graph describes relations between preschool children and preschool teachers. The preschool teachers wear eyeglasses equipped with a video camera, and they take a video in their childcare. The social graph is created by a face recognition and authentication systems that perform identification for children and preschool teachers from the video. Some centralities of our graph are computed, and analyze the preschool education. When we take a long video, our social graph may become a complete graph, so that values of the centralities for all children are equal; it is our technical issues. In this paper, we discuss graph pruning and optimize our centralities for the graph analysis. Our performances of graph pruning are shown in our experiments.
基于人脸认证的学前教育社交图分析研究:图分析中中心性优化的剪枝
本文对社会图谱分析在学前教育中的应用进行了探讨。我们的社交图描述了学龄前儿童和幼儿教师之间的关系。幼儿园的老师们戴着装有摄像机的眼镜,在照顾孩子的过程中拍摄视频。社交图谱是由面部识别和认证系统创建的,该系统对视频中的儿童和幼儿园教师进行身份识别。计算了图的一些中心性,并对幼儿教育进行了分析。当我们拍摄一个很长的视频时,我们的社交图可能会变成一个完整的图,所有孩子的中心性值都是相等的;这是我们的技术问题。在本文中,我们讨论了图修剪和优化我们的中心性图分析。我们的图修剪性能在实验中得到了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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