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Interactive personalized recommendation systems for human health - 2021

Interactive Personalized Recommendation Systems For Human Health

Research Area:  Machine Learning


Recent research in Artificial Intelligence (AI) and recommendation systems have focused on developing highly intelligent and interactive algorithms, utilizing informations acquired from healthcare sensor networks. Regardless of its requirement for higher computational power and the huge volume of healthcare data, a large number of researchers are proactively involved in finding appropriate solutions against this background. This is the editorial of Interactive Personalized Recommendation Systems for Human Health special issue of the Journal of Ambient Intelligence and Humanized Computing Springer Journal. The response of the research community has been significant, and many original contributions have been submitted for consideration. Among that totally 29 papers were accepted after going through a rigorous review process. All of the accepted research papers have significant elements of novelty, and it adds reasonable contributions to the existing research works in this domain. They not only provide novel ideas and state-of-the-art techniques in the field, but also stimulate future research in the sustainable environment.


Author(s) Name:  Ching-Hsien Hsu, Amir H. Alavi & Mianxiong Dong

Journal name:  Journal of Ambient Intelligence and Humanized Computing

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/s12652-021-02950-2

Volume Information:  volume 12, pages 3209–3212 (2021)