Host: NPO: Transdisciplinary Federation of Science and Technology
A machine learning approach can be applied to consumer modeling. This modeling framework consists of statistical learning, probabilistic reasoning, graphical modeling, and large-scale data collecting technologies. Bayesian networks can represent causality relationships and latent structures as graphical structures. Such models can hold situations and contexts of daily life behavior through real services. In order to collect large-scale data connected with them, we have to provide real services supported by many users. This concept, "research as a service" is discussed with real applications.
