Personality diagnosis for personalized eHealth services

Fabio Cortellese, Marco Nalin, Angelica Morandi, Alberto Sanna, Floriana Grasso

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Pages157-164
Number of pages8
Volume27 LNICST
DOIs
Publication statusPublished - 2010
Event2nd International ICST Conference on Electronic Healthcare, eHealth 2009 - Istanbul, Turkey
Duration: Sep 23 2009Sep 25 2009

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Volume27 LNICST
ISSN (Print)18678211

Other

Other2nd International ICST Conference on Electronic Healthcare, eHealth 2009
CountryTurkey
CityIstanbul
Period9/23/099/25/09

Keywords

  • Collaborative filtering
  • Contextualization
  • Dynamic clustering
  • Motivation strategy
  • Natural language processing
  • Personality diagnosis
  • Personalization

ASJC Scopus subject areas

  • Computer Networks and Communications

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