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Personality Diagnosis for Personalized eHealth Services

  • Fabio Cortellese
  • Marco Nalin
  • Angelica Morandi
  • Alberto Sanna
  • Floriana Grasso
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 27)

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 static clustering of the population, with a specific motivation strategy designed for each cluster. The second approach relies on a dynamic population 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.

Keywords

Personalization Personality Diagnosis Motivation Strategy Collaborative Filtering Natural Language Processing Contextualization Dynamic Clustering 

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Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2010

Authors and Affiliations

  • Fabio Cortellese
    • 1
  • Marco Nalin
    • 2
  • Angelica Morandi
    • 2
  • Alberto Sanna
    • 2
  • Floriana Grasso
    • 1
  1. 1.Department of Computer ScienceUniversity of LiverpoolLiverpoolUK
  2. 2.Fondazione Centro San Raffaele del Monte Tabor, eServices for Life and HealthMilanoItaly

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