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Mining Historical Social Issues

  • Yasunobu Sumikawa
  • Ryohei Ikejiri
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 39)

Abstract

This paper presents a framework for identifying human histories that are similar to a modern social issue specified by a learner. From the historical data, the learner can study how people in history tried to resolve social issues and what results they achieved. This can help the learner consider how to resolve the modern social issue. To identify issues in history similar to a given modern issue, our framework uses the characteristics and explanation of the specified modern issue in two techniques: clustering and classification. These techniques identify the similarity between historical and the modern issues by using matrix operation and text classification. We implemented our proposed framework and evaluated it in terms of analysis time. Experimental results proved that our framework has practical usage with an analysis time of only about 0.7 s.

Keywords

History education Transfer of learning Authentic learning Clustering Text classification Semi-supervised learning 

Notes

Acknowledgments

This work was supported by JSPS KAKENHI Grant Number 26750076.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Tokyo University of ScienceTokyoJapan
  2. 2.The University of TokyoTokyoJapan

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