Floriana Grasso

Recent advances in computational models of natural argument

This article reviews recent advances in the interdisciplinary area lying between artificial intelligence and the theory of argumentation. The article has two distinct foci: first, examining the ways in which argumentation has inspired new models of logical and computational intelligence, and second, exploring how AI techniques have been used and extended to model and handle real world argument in a wide variety of domains including law, education, medicine, and e‐commerce.

Adaptive information for consumers of healthcare

This chapter discusses the application of some of the technologies of the adaptive web to the problem of providing information for healthcare consumers. The particular issues relating to this application area are discussed, including the goals of the communication, typical content of a user model, and commonly used techniques. Two case studies are presented, and evaluation approaches considered.

Refining instructional text generation after evaluation

In this paper, we describe how user-adapted explanations about drug prescriptions can be generated from already existing data sources. We start by illustrating the two-step approach employed in the first version of the natural language generator and the limitations of generated texts, that we discovered through analytical and empirical evaluations. We claim that, although style refinement would be needed in these texts, particular care should be devoted to implementing some of the persuasion techniques that doctors employ in their explanations. This would require either thoroughly revising the text planning techniques employed or converting to a multistep generation architecture. We justify why we selected this second alternative and propose some heuristics to repair problems found in the first version of the generator. Some final considerations about the advantages of this approach and the possibility of generalizing it to other domains conclude the paper.

Generation of Personalised Advisory Messages: An Ontology Based Approach

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 users characteristics, and to the context in which the message needs to be generated.

Research opportunities for argumentation in social networks

Nowadays, many websites allow social networking between their users in an explicit or implicit way. In this work, we show how argumentation schemes theory can provide a valuable help to formalize and structure on-line discussions and user opinions in decision support and business oriented websites that held social networks between their users. Two real case studies are studied and analysed. Then, guidelines to enhance social decision support and recommendations with argumentation are provided.

A Conversational Model for Health Promotion on the World Wide Web

In this paper we describe a new approach to computer-based health promotion, based on a conversational model. We base our model on a collection of human-human email dialogues concerning healthy nutrition. Our system uses a database of tips and small pieces of advice, organised so that support for the advice, and arguments against the advice may be explored. The technical framework and initial evaluation results are described.

Preface to the special issue on personalization and behavior change

Digital behavior intervention is a growing area of research which investigates how interactive systems can encourage and support people to change their behavior. Personalization plays an important role in this, as the most effective persuasive and motivational strategies are likely to depend on user characteristics such as the user’s personality, affective state, existing attitudes, behaviors, knowledge, and goals. Example application areas include healthcare (e.g., encouraging people to eatmore healthily and exercise more), education (e.g., motivating learners to study more), environment (e.g., encouraging people to use less energy and more public transport), and collaborative content development (e.g., incentivizing people to annotate resources). The idea that a system may be used to motivate people on the basis of a user model is certainly not novel. As early as the 1980s, intelligent tutoring systems encouraged students to learn by means of tailored feedback and hints (Sleeman and Brown 1982), and in the 90s patient education systems attempted to address compliance to a medical regimen by means of information and personalized advice (De Carolis et al. 1996) or encouraged people to adopt healthier lifestyles (Reiter et al. 2003). However, it is only recently that a number of seemingly non correlated, extensive research efforts,

Rhetorical Coding of Health Promotion Dialogues

Health promotion is a complex activity that requires both explanation and persuasion skills. This paper proposes a three-layered model of dialogue coding, based on a rhetorical argumentation model, and a behavioural model of change. The model was applied to the analysis of a corpus of 40 e-mail dialogue exchanges on healthy nutrition advice. Examples of analysis are given.

Personality Diagnosis for Personalized eHealth Services

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.

Using Dialectical Argumentation for User Modelling in Decision Support Systems

Often the aim of a decision support system is to give advice rather than to inform users. This work shows how linguistic theories of dialectical argumentation can provide a user modelling framework able to take account of the user’s current perspectives and values, in addition to prior knowledge and goals.