Research Article
Personality Diagnosis for Personalized eHealth Services
516 downloads
@INPROCEEDINGS{10.1007/978-3-642-11745-9_25, author={Fabio Cortellese and Marco Nalin and Angelica Morandi and Alberto Sanna and Floriana Grasso}, title={Personality Diagnosis for Personalized eHealth Services}, proceedings={Electronic Healthcare. Second International ICST Conference, eHealth 2009, Istanbul, Turkey, September 23-15, 2009, Revised Selected Papers}, proceedings_a={E-HEALTH}, year={2012}, month={5}, keywords={Personalization Personality Diagnosis Motivation Strategy Collaborative Filtering Natural Language Processing Contextualization Dynamic Clustering}, doi={10.1007/978-3-642-11745-9_25} }- Fabio Cortellese
Marco Nalin
Angelica Morandi
Alberto Sanna
Floriana Grasso
Year: 2012
Personality Diagnosis for Personalized eHealth Services
E-HEALTH
Springer
DOI: 10.1007/978-3-642-11745-9_25
Abstract
In this paper we present two different approaches to personality diagnosis, for the provision of innovative personalized services, as used in a case study where diabetic patients were supported in the improvement of physical activity in their daily life. The first approach presented relies on a of the population, with a specific motivation strategy designed for each cluster. The second approach relies on a clustering, making use of recommendation systems and algorithms, like Collaborative Filtering. We discuss pro and cons of each approach and a possible combination of the two, as the most promising solution for this and other personalization services in eHealth.
Copyright © 2009–2025 ICST
