Mobile Computing and Artificial Intelligence for Diet Management

Mazzei, Alessandro; Anselma, Luca; Michieli, Franco De; Bolioli, Andrea; Casu, Matteo; Gerbrandy, Jelle; Lunardi, Ivan

doi:10.1007/978-3-319-23222-5_42

Cited by 7 publications

(3 citation statements)

References 12 publications

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“…The MADiMan system is a virtual dietitian designed to fulfil three basic tasks: (1) retrieve the nutritional information of a dish directly from its recipe, (2) exploiting such nutrition information and data regarding diets by allowing some forms of diet disobedience while pursuing the goals of the diets and (3) encourage the user to reduce these disobedience acts. MADiMan offers facilities for verifying the compatibility and predicting the effect of disobedience acts on a specific diet [10,11]. Figure 1 shows the architecture of the MADiMan system.…”

Section: The Madiman Architecturementioning

confidence: 99%

“…In previous work, we discussed the general architecture of the MADiMan system [10,11] and the capacity of the reasoning module with a number of simulation experiments with virtual agents based on hospital menus [12] and on Mediterranean menus [13,14]. The research questions that we explore in this paper concern the NLG module of MADiMan, which has been partially previously described in some preliminary work [15,16].…”

Section: Introductionmentioning

confidence: 99%

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Building a Persuasive Virtual Dietitian

Anselma

Mazzei

2020

Informatics

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This paper describes the Multimedia Application for Diet Management (MADiMan), a system that supports users in managing their diets while admitting diet transgressions. MADiMan consists of a numerical reasoner that takes into account users’ dietary constraints and automatically adapts the users’ diet, and of a natural language generation (NLG) system that automatically creates textual messages for explaining the results provided by the reasoner with the aim of persuading users to stick to a healthy diet. In the first part of the paper, we introduce the MADiMan system and, in particular, the basic mechanisms related to reasoning, data interpretation and content selection for a numeric data-to-text NLG system. We also discuss a number of factors influencing the design of the textual messages produced. In particular, we describe in detail the design of the sentence-aggregation procedure, which determines the compactness of the final message by applying two aggregation strategies. In the second part of the paper, we present the app that we developed, CheckYourMeal!, and the results of two human-based quantitative evaluations of the NLG module conducted using CheckYourMeal! in a simulation. The first evaluation, conducted with twenty users, ascertained both the perceived usefulness of graphics/text and the appeal, easiness and persuasiveness of the textual messages. The second evaluation, conducted with thirty-nine users, ascertained their persuasive power. The evaluations were based on the analysis of questionnaires and of logged data of users’ behaviour. Both evaluations showed significant results.

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Section: The Madiman Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Building a Persuasive Virtual Dietitian

Anselma

Mazzei

2020

Informatics

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“…In this paper we describe the first steps towards the integration of Mediterranean diet into an exiting framework for the management of the diet called MADiMan (Multimedia Architecture for Diet Management) . In previous work, some questions concerning the general architecture of the MADiMan system (Mazzei et al, 2015;Anselma and Mazzei, 2015), concerning the capacities of the reasoning module with a number of computer simulations with virtual agents based on hospital menus and on Mediterranean menus and concerning the Natural Language Generation module have been addressed.…”

Section: Introductionmentioning

confidence: 99%