No. 1373
Application of Machine Learning to Service-Oriented Systems
Investigating R&D Committee on Machine Learning Techniques for Efficiency and Optimization of Service-oriented systems
Keyword : machine learning, service-oriented systems
Service industries have recently increased in importance owing to their economic status. Increasing the productivity of such industries is therefore a critical issue. One of the important research projects for increasing their productivity is how to optimize and streamline services when viewed as complex systems, including the presence of several types of uncertainties (e.g., people). Machine learning techniques regarding optimization and big data processing, among other areas, are extremely useful tools to overcome existing research problems.
Our committee has conducted research and surveys regarding machine learning techniques based on the findings obtained by the previous committee (Investigation R&D Committee on Realistic Application-oriented Machine Learning Techniques) to optimize and improve the efficiency of service-oriented systems, along with a broad range of relevant industrial systems. The purpose of our committee is to provide such machine learning techniques to industries and contribute to the economic development of our country.
This technical report outlines the activities of the committee (from Apr. 2012 to Mar. 2014), thereby offering a variety of applications of machine learning techniques to service-oriented and other relevant industrial systems.

©2007. The Institute of Electrical Engineers of Japan