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

  1. S. Kato, T. Nakanishi, H. Shimauchi, B. Ahsan, Topic Variation Detection Method for Detecting Political Business Cycles, Accepted at the 6th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, (2019).
  2. 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.
  3. 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).