Ilaria Lombardi

Personalized and Adaptive Services on Board a Car: An Application for Tourist Information

Personalization and adaptation techniques are an interesting opportunity to design new services on-board vehicles. In this context, in fact, the need of an individual user to receive the “right” service at the “right” time and in the “right” way is more critical than in other cases, where personalization and adaptation already showed interesting advantages. At the same time, this context of application can provide new interesting insights for user modeling and adaptation. In the paper we present an architecture for providing personalized services on-board vehicles and we discuss an application to the case of tourist information. We focus on the choices we made to design an on-board system which was as less intrusive and distracting as possible and that could adapt its recommendations, the way it presents them and its own behavior to the users preferences/interests and to the context of interaction (especially the driving conditions).

Adaptation and Personalization on Board Cars: A Framework and Its Application to Tourist Services

In this paper we analyse the goals and problems that should be taken into account when designing adaptive/personalized services that must run on-board vehicles. This is, in fact, a very interesting and promising area of application where adaptation and personalization can provide unique advantages. We then introduce a framework and a multi-agent architecture for on-board services supporting different forms of user and context modelling and different forms of adaptation and personalization. Finally, to support our claims and framework, we discuss a specific prototype system for on-board tourist services.

Interacting with social networks of intelligent things and people in the world of gastronomy

This article introduces a framework for creating rich augmented environments based on a social web of intelligent things and people. We target outdoor environments, aiming to transform a region into a smart environment that can share its cultural heritage with people, promoting itself and its special qualities. Using the applications developed in the framework, people can interact with things, listen to the stories that these things tell them, and make their own contributions. The things are intelligent in the sense that they aggregate information provided by users and behave in a socially active way. They can autonomously establish social relationships on the basis of their properties and their interaction with users. Hence when a user gets in touch with a thing, she is also introduced to its social network consisting of other things and of users; she can navigate this network to discover and explore the world around the thing itself. Thus the system supports serendipitous navigation in a network of things and people that evolves according to the behavior of users. An innovative interaction model was defined that allows users to interact with objects in a natural, playful way using smartphones without the need for a specially created infrastructure. The framework was instantiated into a suite of applications called WantEat, in which objects from the domain of tourism and gastronomy (such as cheese wheels or bottles of wine) are taken as testimonials of the cultural roots of a region. WantEat includes an application that allows the definition and registration of things, a mobile application that allows users to interact with things, and an application that supports stakeholders in getting feedback about the things that they have registered in the system. WantEat was developed and tested in a real-world context which involved a region and gastronomy-related items from it (such as products, shops, restaurants, and recipes), through an early evaluation with stakeholders and a final evaluation with hundreds of users.

Semantic similarity in heterogeneous ontologies

Recent extensive usage of ontologies as knowledge bases that enable rigorous representation and reasoning over heterogenous data poses certain challenges in their construction and maintenance. Many of these ontologies are incomplete, containing many dense sub-ontologies. A need arises for a measure that would help calculate the similarity between the concepts in these kinds of ontologies. In this work, we introduce a new similarity measure for ontological concepts that takes these issues into account. It is based on conceptual specificity, which measures how much a certain concept is relevant in a given context, and on conceptual distance, which introduces different edge lengths in the ontology graph. We also address the problem of computing similarity between concepts in the presence of implicit classes in ontologies. The evaluation of our approach shows an improvement over Leacock and Chodorows distance based measure. Finally, we provide two application domains which can benefit when this similarity measure is used.

Toward a social web of intelligent things

In this paper we introduce the notion of “Social Web of Intelligent Things” (SWIT hereafter) as a an evolution of both the “Web of Things” and “Smart Objects” paradigms. In a SWIT, things become entities capable of an intelligent and social behavior. On the one hand, things maintain and socialize knowledge and can interact and communicate with people; on the other, “social” networks of people and things arise as a result of this interaction. SWIT is an evolution of social media that goes beyond the desktop paradigm and is a way of bridging the gap between real-life and virtual experiences. Interactions between people and things happen naturally in real life, augmenting and enhancing peoples experiences. We claim that SWITs are a challenging area of research and application for Artificial Intelligence in the context of the Future Internet. The paper provides a characterization of SWITs, discussing the ingredients that are needed to create a SWIT; it introduces a framework for building SWITs and briefly presents an instance we developed and tested with users. In the paper we claim that many areas of Artificial Intelligence can contribute to the is framework, which in turn can stimulate research in these areas and on their integration.

Using mobile phone cameras to interact with ontological data

In addition to being used to access data and services on the Internet, mobile phones can also be used to retrieve information about physical objects. In this paper we present a framework and a prototype implementation of a reality browsing system that exploits mobile camera phones as access points to ontological knowledge with the corresponding physical counterparts. The use of ontologies to represent the information about the objects of the domain permits for application of reasoning and querying techniques on domain elements. Users can identify a desired product by framing its logo, obtaining further information about the object in a direct, natural and intuitive way. In addition, users can perform Web 2.0 actions on objects, contributing to the creation and development of the network of objects and users. We also provide a brief description of the implemented interface and a real world user evaluation.

Dynamic interface reconfiguration based on different ontological relations

This paper presents a framework and a prototype implementation of a system that integrates ontological knowledge base with the services for the users in mobility. Our system tries to help users navigate the domain of gastronomy, offering a possibility to explore the ontological base consisting of many concepts and relations. We present the logic and technical realization of the modules responsible for knowledge base interrogation and for presenting the obtained information to a user. We also provide a brief description of the implemented interface and user evaluation.

Engaging Users in Self-Reporting Their Data: A Tangible Interface for Quantified Self

Personal Informatics systems allow users to self-track a variety of states and behaviors. However, not all these data are suitable to be automatically collected. This is especially true for emotions and mood. These data require to be self-reported by the users and this activity can be very cumbersome, requiring an high compliance to be effective: instead users often fail in reporting their data due to forgetfulness, lack of time and motivation. To overcome these problems, we propose to exploit Tangible User Interface for relieving the task of self-reporting. In particular, we present a Personal Informatics Tangible Interface able to support users in self-reporting their mood. This solution allows the collection of emotional states in an amusing, simple and appealing way by means of a physical object.

Flexible rule-based inference exploiting taxonomies

Rule-based systems are widely used to implement knowledge-based systems. They are usually intuitive to use, have good performance and can be easily integrated with other software components. However, a critical problem is that the behavior of a rule-based system tends to degrade abruptly whenever the knowledge base is incomplete or not detailed enough or when operating at the borders of its expertise. Various forms of approximate reasoning have been introduced but they solve the problem only in a partial way. In the paper we propose new forms of rule inference that tackle this problem, introducing a form of flexible or common sense reasoning that can support a softer degradation of problem solving ability when knowledge is partial or incomplete. The solution we propose relies on the exploitation of semantic information associated with the concepts involved in the rules. In particular, we show how taxonomical information can be exploited to define flexible forms of match between rule antecedents and the working memory, and flexible forms of conflict resolution. In this way, even when no rule perfectly matches the working memory, the inference engine can select rules that apply to more general or to similar cases and provide some approximate solution. The approach has been motivated by work on context aware (recommender) systems where the problem of incomplete descriptions and brittle degradation of problem solving ability are particularly relevant.

SEeS@W: Internet of Persons meets Internet of Things for Safety at Work

SEeS@w faces the problem of safety in working environments in an innovative way, putting together objects and people, and the virtual and real word. We aimed at designing and developing a demonstrative prototype of an innovative ICT solution to monitor, evaluate and manage risks in a complex cooperative working environment. Data about risks are provided by workers themselves using interactive maps, according to the Internet of Persons paradigm. Maps are also fed by other data collected by networks of ambient and wearable sensors connected to the Internet, according to the Internet of Things paradigm. Maps display and bring all these data together, and can be therefore used by workers as a powerful instrument to coordinate people, manage risk issues, and improve safety at work. Thanks to the Living Lab methodology, we brought together the technical and human aspects of the project, testing the solution in terms of effectiveness, acceptability, usability and ergonomics.