Research Article
Cloud-based platform for personalization in a wellness management ecosystem: Why, what, and how
@INPROCEEDINGS{10.4108/icst.collaboratecom.2010.44, author={Pei-Yun S. Hsueh and Raymund J.R. Lin and Mark J.H. Hsiao and Liangzhao Zeng and Sreeram Ramakrishnan and Henry Chang}, title={Cloud-based platform for personalization in a wellness management ecosystem: Why, what, and how}, proceedings={6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing}, publisher={IEEE}, proceedings_a={COLLABORATECOM}, year={2011}, month={5}, keywords={computer-tailored lifestyle intervention cloud computing personalization dynamic pricing active learning feature selection sample selection}, doi={10.4108/icst.collaboratecom.2010.44} }- Pei-Yun S. Hsueh
Raymund J.R. Lin
Mark J.H. Hsiao
Liangzhao Zeng
Sreeram Ramakrishnan
Henry Chang
Year: 2011
Cloud-based platform for personalization in a wellness management ecosystem: Why, what, and how
COLLABORATECOM
ICST
DOI: 10.4108/icst.collaboratecom.2010.44
Abstract
Offering personalized services through dynamically formed ecosystems is essential to personal wellness management. In this paper, we present the design of a cloud-enabled platform to facilitate the collection and delivery of evidence for personalization in a multi-provider ecosystem environment. In addition, the platform also provides essential building blocks of personalization services: smarter analytics for active personalization and dynamic provisioning. While the former common service takes charge of inferring user wellness risks from multiple data sources on the fly and making risk-driven recommendations, the latter common service determines optimal platform pricing and resource allocation given the constraint of acceptable quality of service.
