Special Session - 01


Prof. Yukari Shirota Gakushuin University yukari.shirota@gakushuin.ac.jp
Prof. Basabi Chakraborty Iwate Prefectural University basabi@iwate-pu.ac.jp
Prof. Takako Hashimoto Chiba University of Commerce takako@cuc.ac.jp


In the field of economic, social and environmental data analysis, machine learning technologies have been more and more used. The analysis target includes stock price, GDP, exchange rate, Gini index, TFR (total fertility rate), working population, and profit of company. However, in the conferences concerning economics, there is not enough discussions on the data analysis technologies. Especially, concerning the latest machine learning analysis methods, there are quite few comments as the audience do not possess sufficient knowledge regarding machine learning technologies. In iCAST 2019, the organizers held the special session with the same title and there were active discussions from both the viewpoints of application fields and machine learning technologies. So, in iCAST 2020, we would like to have critical discussion on improvement of interpretation ability of machine learning technique in analysis of Economic and Social data. The remarkable progress for interpretation of machine learning techniques has great effect in the data engineering field. The main target of this special session is economics, financial and social data analysis. However other non-image data analysis is also welcome.


Topics of Interests include but are not limited to:


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