2008 21st IEEE International Symposium on Computer-Based Medical Systems 2008
DOI: 10.1109/cbms.2008.103
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Generation of Personalised Advisory Messages: An Ontology Based Approach

Abstract: This paper presents an ontology based approach to the production of personalised motivational messages to the user of a e-Health service. The service is aimed at encouraging diabetic patients to do physical activity. The textual messages have an overall predetermined structure, and need to be personalised to the user's characteristics, and to the context in which the message needs to be generated.

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Cited by 19 publications
(19 citation statements)
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“…Both were dynamically generated. The textual part of the feedback followed a macro-structure that guided the message composition (similar to Erriquez and Grasso 2008). For example, a message usually started with a statement about the individual/family performance; then, it reminded the family about the goal to be attained; finally, it finished with an encouragement.…”
Section: Tailored Feedbackmentioning
confidence: 99%
“…Both were dynamically generated. The textual part of the feedback followed a macro-structure that guided the message composition (similar to Erriquez and Grasso 2008). For example, a message usually started with a statement about the individual/family performance; then, it reminded the family about the goal to be attained; finally, it finished with an encouragement.…”
Section: Tailored Feedbackmentioning
confidence: 99%
“…In the example message, the content is the fact that the user has not been active enough, a factual statement about the advantages of physical activity, and the suggestion to walk or perform vigorous exercise. The content of messages is the primary topic in the related literature discussed in Section 2, and the framework as presented in [7] deals also exclusively with the content of messages.…”
Section: Messagementioning
confidence: 99%
“…Erriquez and Grasso [7] propose an ontology-based approach for generating personalized messages that are sent to the user's mobile phone throughout the day. The work is based on an earlier publication by Morandi and Serafin [30] in which a personalized Diffuse affective states not resulting from specific events but more likely associated with general views at a point in time [34] Context…”
Section: Real-time Message Generationmentioning
confidence: 99%
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