[dbjapan] CFP: iCAST Special Session on "Awareness Technology for Economic and Social Data Analysis" （〆切：July 26）

[Takako Hashimoto <takako [at] cuc.ac.jp>]

日本データベース学会のみなさま

（重複して受け取られた場合はご容赦ください）

千葉商科大学の橋本と申します。

本年10月23日〜25日まで、盛岡で開催される iCAST 2019 の Special Session 

"Awareness Technology for Economic and Social Data Analysis"  CFPを送付させていただきます。

本セッションの目的は，機械学習の手法で経済データ及び社会科学などのデータを分析する研究者の

ディスカッションの場を作りたい，ということです。機械学習による経済・社会データの分析手法に

ついてもっと議論したい，と感じていらっしゃる研究者に是非とも参集頂きたいと思っております。

ご投稿を検討いただければと思います。

宜しくお願いいたします。

橋本

−−−

Session Title:  Awareness Technology for Economic and Social Data Analysis

at The 10th IEEE International Conference on Awareness Science and Technology iCAST 2019

October 23 - 25, 2019,

Morioka, Japan Webpage: http://www.chishiki.soft.iwate-pu.ac.jp/icast2019/

Organizers:

• Prof. Yukari Shirota (Gakushuin University) yukari.shirota [at] gakushuin.ac.jp
• Prof. Takako Hashimoto (Chiba University of Commerce) takako [at] cuc.ac.jp
• Prof. Basabi Chakraborty (Iwate Prefectural University) basabi [at] iwate-pu.ac.jp

Abstract:

In the field of economic, social and environmental data analysis, machine learning technologies have been more and more used. The analysis target include stock process, GDP, exchange rate, Gini index, TFR (total fertility rate), working population, and profit of company. However, in some conferences concerning economics, there is not enough discussions on the data analysis technologies. Especially concerning the latest machine learning analysis methods, there is quite few comments because the audience have not enough knowledge on the machine learning technologies. The organizer will propose the special session so that we can discuss the data analysis method and the used data. We will exchange advices and comments using concrete library names such as sklearn and the source data such as World Bank. The special session will contribute a lot to economic data analysts, because they will be able to know other researcher methodologies. Therefore, the papers are limited to be ones that use machine learning methods including PCA(Principal Component Analysis) and SVD(Singular Value Decomposition) other than DNN and tree-based models and others. The target data must be no image data, because the image analysis is out of this theme. The main target is economics data analysis. However other non-image data analysis is welcome.

Topics of Interests include but are not limited to:

(1) Classification or regression of economics/social/environmental data

(2) Social media data analysis by machine learning methods

(3) Financial prediction/analysis by machine learning methods

(4) Sustainable Development Goals related data analysis by machine learning methods

(5) Visualization of those data analyses 

Venue:

AIINA 7th, & 8th. Fl., Morioka, Iwate, Japan. http://www.aiina.jp/en/ (4mins. Walk from Morioka station, 8mins drive from Tohoku Expressway)

Paper Submission Procedure:
Electronic version of full paper (IEEE format, A4 six-page standard including figures and tables) complete with authors' affiliations should be submitted through official site. All accepted papers will be sent to IEEE Xplore Digital Library. Selected papers will be recommended for post-conference publication in some Science Citation Index Expanded, EI, or Scopus journals.

 Important Dates:

• June 3, 2019: Deadline of Special Session (SS) proposal

• June 28, 2019: Notification of Acceptance of SS proposal

• July 26, 2019: Deadline of paper submission (both general session and SS)

• August 30, 2019: Notification of paper acceptance

• September 17, 2019: Submission of final camera-ready papers

• September 10, 2019: Deadline for registration

-- 
Takako Hashimoto, Ph. D.
Vice President, Chiba University of Commerce  (Professor)

Director, International Center, Chiba University of Commerce

IEEE R10 Secretary (2019)
Past Chair, IEEE MGA Membership Recruitment and Recovery (2017-2018)
1-3-1, Konodai Ichikawa City, Chiba,
272-8512 Japan,　tel:+81-47-373-4222
takako [at] cuc.ac.jp