Takafumi Nakanishi | Experts | The Tokyo Foundation for Policy Research

Experts

Takafumi Nakanishi

SENIOR DATA SCIENTIST

Associate Professor, Faculty of Data Science, Musashino University

Senior Researcher, Center for Global Communications, International University of Japan

Visiting Professor, Digital Hollywood University

Areas of Expertise

Data mining
data analysis system
integrated database
sensitivity information processing
media content analysis

Research Unit

Politics & Economy

Projects

Political Risk Analysis (2016–)

Bio

Received his PhD from the Graduate School of Systems and Information Engineering, University of Tsukuba. Was engaged as a researcher in R&D at the Knowledge Cluster system of the National Institute of Information and Communications Technology (2006–14). Was an associate professor and senior researcher at the Center for Global Communications, International University of Japan (2014–18). Concurrently serves as a member of the AI Network Society Promotion Conference of Japan’s Ministry of Internal Affairs and Communications (2016–). Was a member of the Study Group on the Utilization and Application of Information in the Distribution and Logistics Field, Japan’s Ministry of Economy, Trade and Industry (2015–16).

Publications and Conferece Papers

S. Kato, T. Nakanishi, H. Shimauchi, B. Ahsan, Topic Variation Detection Method for Detecting Political Business Cycles, In Proceedings of the 6th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT '19). ACM, New York, NY, USA, 85-93 (2019).
B. Ahsan, S. Kato, T. Nakanishi, H. Shimauchi, Augmenting Political Data through Generative Adversarial Networks (GANs), Paper presented at the 115th American Political Science Association's Annual Meeting (2019).
S. Kato, H. Shimauchi, T. Nakanishi and B. Ahsan, Detecting Political Business Cycles through the Prime Minister’s Daily Schedule, Paper presented at the 77th Annual Meeting of the Midwest Political Science Association (2019).
Okada, T. Nakanishi, Y. Tanaka, Y. Ogasawara, and K. Ohashi, “A Visualization Method of Relationships among Topics in a Series of Meetings,” Information Engineering Express Journal, vol.3, no.4 (2017), p.115–24.
Okada, T. Nakanishi, Y. Tanaka, Y. Ogasawara, K. Ohashi, “A Topic Structuration Method on Time Series for a Meeting from Text Data,” In R. Lee (ed), Studies in Computational Intelligence, Springer, Cham, vol. 721 (2017), pp. 45-59.

“A Feature Selection for Comparison among Each Concept and its Visualization,” ACIS International Journal of Computer & Information Science, vol.17, no.1 (2016).

“A Discovery Method of Anteroposterior Correlation for Big Data Era, Software Engineering,” In R. Lee (ed), Studies in Computational Intelligence, Springer, Cham, vol. 569, pp. 161–77.

“A Data-Driven Axes Creation Model for Correlation Measurement on Big Data Analytics,” Information Modelling and Knowledge Bases XXVI, IOS Press, pp. 308–23 (2014).

By This Author

Publications

Time-Series Topic Analysis Using Singular Spectrum Transformation for Detecting Political Business Cycles

By Sota Kato

By Takafumi Nakanishi

By Hirokazu Shimauchi

By Budrul Ahsan

Tokyo Foundation for Policy Research

December, 2020