Salvatore Rinzivillo

Salvatore Rinzivillo
Italian National Research Council | CNR · Institute of Information Science and Technology "Alessandro Faedo" ISTI

About

92
Publications
26,493
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2,803
Citations

Publications

Publications (92)
Chapter
Full-text available
Explainable AI consists in developing models allowing interaction between decision systems and humans by making the decisions understandable. We propose a case study for skin lesion diagnosis showing how it is possible to provide explanations of the decisions of deep neural network trained to label skin lesions.
Preprint
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The burgeoning of AI has prompted recommendations that AI techniques should be "human-centered". However, there is no clear definition of what is meant by Human Centered Artificial Intelligence, or for short, HCAI. This paper aims to improve this situation by addressing some foundational aspects of HCAI. To do so, we introduce the term HCAI agent t...
Preprint
Full-text available
A key issue in critical contexts such as medical diagnosis is the interpretability of the deep learning models adopted in decision-making systems. Research in eXplainable Artificial Intelligence (XAI) is trying to solve this issue. However, often XAI approaches are only tested on generalist classifier and do not represent realistic problems such as...
Article
Full-text available
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are bei...
Article
Full-text available
Increased availability of epidemiological data, novel digital data streams, and the rise of powerful machine learning approaches have generated a surge of research activity on real-time epidemic forecast systems. In this paper, we propose the use of a novel data source, namely retail market data to improve seasonal influenza forecasting. Specifical...
Preprint
The widespread adoption of black-box models in Artificial Intelligence has enhanced the need for explanation methods to reveal how these obscure models reach specific decisions. Retrieving explanations is fundamental to unveil possible biases and to resolve practical or ethical issues. Nowadays, the literature is full of methods with different expl...
Preprint
Full-text available
Increased availability of epidemiological data, novel digital data streams, and the rise of powerful machine learning approaches have generated a surge of research activity on real-time epidemic forecast systems. In this paper, we propose the use of a novel data source, namely retail market data to improve seasonal influenza forecasting. Specifical...
Chapter
This paper presents an analytical platform for evaluation of the performance and anomaly detection of tests for admission to public universities in Italy. Each test is personalized for each student and is composed of a series of questions, classified on different domains (e.g. maths, science, logic, etc.). Since each test is unique for composition,...
Preprint
Full-text available
Understanding collective mobility patterns is crucial to plan the restart of production and economic activities, which are currently put in stand-by to fight the diffusion of the epidemics. In this report, we use mobile phone data to infer the movements of people between Italian provinces and municipalities, and we analyze the incoming, outcoming a...
Preprint
Full-text available
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being...
Article
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are bei...
Article
Full-text available
The new data sources give the possibility to answer analytically the questions that arise from mobility manager. The process of transforming raw data into knowledge is very complex, and it is necessary to provide metaphors of visualizations that are understandable to decision makers. Here, we propose an analytical platform that extracts information...
Article
People living in highly populated cities increasingly experience decreased quality of life due to pollution and traffic congestion. With the objective of reducing the number of circulating vehicles, we investigate a novel approach to boost ride-sharing opportunities based on the knowledge of the human activities behind individual mobility demands....
Conference Paper
Nowadays the analysis of dynamics of and on networks represents a hot topic in the Social Network Analysis playground. To support students, teachers, developers and researchers we introduced a novel framework, named NDlib, an environment designed to describe diffusion simulations. NDlib is designed to be a multi-level ecosystem that can be fruitful...
Article
Full-text available
Nowadays the analysis of dynamics of and on networks represents a hot topic in the social network analysis playground. To support students, teachers, developers and researchers, in this work we introduce a novel framework, namely NDlib, an environment designed to describe diffusion simulations. NDlib is designed to be a multi-level ecosystem that c...
Chapter
During the last 35 years, data management principles such as physical and logical independence, declarative querying and cost-based optimization have led to profound pervasiveness of relational databases in any kind of organization. More importantly, these technical advances have enabled the first round of business intelligence applications and...
Poster
Full-text available
Big Data offer nowadays the capability of creating a digital nervous system of our society, enabling the measurement, monitoring and prediction of various phenomena in quasi real time. But with that, comes the need of more timely forecast, in other words nowcast of changes and events in nearly real-time as well. The goal of nowcasting is to estimat...
Article
Full-text available
The availability of massive digital traces of individuals is offering a series of novel insights on the understanding of patterns characterizing human mobility. Many studies try to semantically enrich mobility data with annotations about human activities. However, these approaches either focus on places with high frequencies (e.g., home and work),...
Conference Paper
ComeWithMe is an activity oriented carpooling service that enlarges the candidate destinations of a ride request by considering alternative places where the desired activity can be performed. It is based on the observation that individuals often move towards a place to perform an activity while the activity is often not strictly associated with a s...
Chapter
The paper illustrates basic methods of mobility data mining, designed to extract from the big mobility data the patterns of collective movement behavior, i.e., discover the subgroups of travelers characterized by a common purpose, profiles of individual movement activity, i.e., characterize the routine mobility of each traveler. We illustrate a num...
Article
Full-text available
The timely, accurate monitoring of social indicators, such as poverty or inequality, on a finegrained spatial and temporal scale is a crucial tool for understanding social phenomena and policymaking, but poses a great challenge to official statistics. This article argues that an interdisciplinary approach, combining the body of statistical research...
Conference Paper
Full-text available
Modeling the properties of individual human mobility is a challenging task that has received increasing attention in the last decade. Since mobility is a complex system, when modeling individual human mobility one should take into account that human movements at a collective level influence, and are influenced by, human movement at an individual le...
Conference Paper
Full-text available
Evaluating a community detection algorithm is a complex task due to the lack of a shared and universally accepted definition of community. In literature, one of the most common way to assess the performances of a community detection algorithm is to compare its output with given ground truth communities by using computationally expensive metrics (i....
Chapter
Evaluating a community detection algorithm is a complex task due to the lack of a shared and universally accepted definition of community. In literature, one of the most common way to assess the performances of a community detection algorithm is to compare its output with given ground truth communities by using computationally expensive metrics (i....
Article
Carpooling, i.e., the act where two or more travelers share the same car for a common trip, is one of the possibilities brought forward to reduce traffic and its externalities, but experience shows that it is difficult to boost the adoption of carpooling to significant levels. In our study, we analyze the potential impact of carpooling as a collect...
Conference Paper
The interest in carpooling is increasing due to the need to reduce traffic and noise pollution. Most of the available approaches and systems are route oriented, where driver and passengers are matched when the destination location is the same. ComeWithMe offers a new perspective: the destination is the intended activity instead of a location. This...
Conference Paper
Full-text available
The striking proliferation of sensing technologies that provide high-fidelity data streams extracted from every game induced an amazing evolution of football statistics. Nowadays professional statistical analysis firms like ProZone and Opta provide data to football clubs, coaches and leagues, who are starting to analyze these data to monitor their...
Article
Full-text available
The availability of massive digital traces of human whereabouts has offered a series of novel insights on the quantitative patterns characterizing human mobility. In particular, numerous recent studies have lead to an unexpected consensus: the considerable variability in the characteristic travelled distance of individuals coexists with a high degr...
Conference Paper
We demonstrate a system of tools for real-time detection of significant clusters of spatial events and observing their evolution. The tools include an incremental stream clustering algorithm, interactive techniques for controlling its operation, a dynamic map display showing the current situation, and displays for investigating the cluster evolutio...
Article
A spatially abstracted transportation network is a graph where nodes are territory compartments (areas in geographic space) and edges, or links, are abstract constructs, each link representing all possible paths between two neighboring areas. By applying visual analytics techniques to vehicle traffic data from different territories, we discovered t...
Article
Full-text available
By applying visual analytics techniques to vehicle traffic data, we found a way to visualize and study the relationships between the traffic intensity and movement speed on links of a spatially abstracted transportation network. We observed that the traffic intensities and speeds in an abstracted network are interrelated in the same way as they are...
Conference Paper
Big Data originating from the digital breadcrumbs of human activities, sensed as by-product of the technologies that we use for our daily activities, allows us to observe the individual and collective behavior of people at an unprecedented detail. Many dimensions of our social life have big data “proxies”, such as the mobile calls data for mobility...
Article
Full-text available
Aim of this paper is to introduce the complex system perspective into retail market analysis. Currently, to understand the retail market means to search for local patterns at the micro level, involving the segmentation, separation and profiling of diverse groups of consumers. In other contexts, however, markets are modelled as complex systems. Such...
Article
Full-text available
Privacy is ever-growing concern in our society and is becoming a fundamental aspect to take into account when one wants to use, publish and analyze data involving human personal sensitive information. Unfortunately, it is increasingly hard to transform the data in a way that it protects sensitive information: we live in the era of big data characte...
Conference Paper
Full-text available
The large availability of mobility data allows us to investigate complex phenomena about human movement. However this adundance of data comes with few information about the purpose of movement. In this work we address the issue of activity recognition by introducing Activity-Based Cascading (ABC) classification. Such approach departs completely fro...
Conference Paper
Full-text available
Human mobility analysis is emerging as a more and more fundamental task to deeply understand human behavior. In the last decade these kind of studies have become feasible thanks to the massive increase in availability of mobility data. A crucial point, for many mobility applications and analysis, is to extract interesting locations for people. In t...
Conference Paper
In recent years, the exponential growth of positioning-enabled devices have allowed us to study the mobility behavior of individuals analyzing their collected tracks. In this context, a small, but steadily increasing part of the literature is looking at the semantic aspects of mobility. This paper presents a contribution to this trend, and is conce...
Conference Paper
Mobility crowdsourced data, like check-ins of the social networks and GPS tracks, are the digital footprints of our lifestyles. This mobility produces an impact on the places that we are visiting, characterizing them by our behavior. In this paper we concentrate on the loyalty of places, indicating the regularity of people in visiting a given place...
Chapter
The availability of massive network and mobility data from diverse domains has fostered the analysis of human behavior and interactions. This data availability leads to challenges in the knowledge discovery community. Several different analyses have been performed on the traces of human trajectories, such as understanding the real borders of human...
Chapter
Full-text available
The increasing expressiveness of spatio-temporal microsimulation systems makes them attractive for a wide range of real world applications. However, the broad field of applications puts new challenges to the quality of microsimulation systems. They are no longer expected to reflect a few selected mobility characteristics but to be a realistic repre...
Article
This paper proposes and experiments new techniques to de- Tect urban mobility patterns and anomalies by analyzing trajectories mined from publicly available geo-positioned social media traces left by the citizens (namely Twitter). By collecting a large set of geo-located tweets characterizing a specific urban area over time, we semantically enrich...
Article
Mobility crowdsourced data, like check-ins of the social networks and GPS tracks, are the digital footprints of our lifestyles. This mobility produces an impact on the places that we are visiting, characterizing them by our behavior. In this paper we concentrate on the loyalty of places, indicating the regularity of people in visiting a given place...
Conference Paper
This information about our GSM calls is stored by the TelCo operator in large volumes and with strict privacy constraints making it challenging the analysis of these fingerprints for inferring mobility behavior. This paper proposes a strategy for mobility behavior identification based on aggregated calling profiles of mobile phone users. This compa...
Conference Paper
In our market society, buyers are considered rational entities, driven by two utility functions: i) the amount of money spent, a universal quantity to be minimized; and ii) the individual needs to satisfy, a personal quantity, varying from person to person, to be maximized. In this paper, we propose an analytic framework based on big data to measur...
Chapter
Full-text available
This paper proposes and experiments new techniques to detect urban mobility patterns and anomalies by analyzing trajectories mined from publicly available geo-positioned social media traces left by the citizens (namely Twitter). By collecting a large set of geo-located tweets characterizing a specific urban area over time, we semantically enrich th...
Conference Paper
Full-text available
In the last years, the emergence of big data led scientists from diverse disciplines toward the study of the laws underlying human mobility. Although these recent discoveries have shed light on very interesting and fascinating aspects about people movements, they are generally focused on global and general mobility patterns. For this reason, they d...
Poster
Full-text available
Why do we move so differently? What are the factors that shape our mobility? What are the movements that mainly determine the mobility of an individual?
Conference Paper
Traditionally, the information about human mobility behavior, called diary, is acquired from volunteers by means of paper-and-pencil surveys. These diaries, representing the mobile activities of individuals, are semantically rich, but lack in spatial and temporal precision. An alternative way is collecting diaries by annotating with activities the...
Article
Full-text available
Place-oriented analysis of movement data, i.e., recorded tracks of moving objects, includes finding places of interest in which certain types of movement events occur repeatedly and investigating the temporal distribution of event occurrences in these places and, possibly, other characteristics of the places and links between them. For this class o...
Conference Paper
Full-text available
Are the patterns of car travel different from those of general human mobility? Based on a unique dataset consisting of the GPS trajectories of 10 million travels accomplished by 150,000 cars in Italy, we investigate how known mobility models apply to car travels, and illustrate novel analytical findings. We also assess to what extent the sample in...
Article
Full-text available
Are the patterns of car travel different from those of general human mobility? Based on a unique dataset consisting of the GPS trajectories of 10 million travels accomplished by 150,000 cars in Italy, we investigate how known mobility models apply to car travels, and illustrate novel analytical findings. We also assess to what extent the sample in...
Conference Paper
We propose a novel approach to privacy-preserving analytical processing within a distributed setting, and tackle the problem of obtaining aggregated information about vehicle traffic in a city from movement data collected by individual vehicles and shipped to a central server. Movement data are sensitive because people’s whereabouts have the potent...
Article
We propose an approach to preserve privacy in an analytical processing within a distributed setting, and tackle the problem of obtaining aggregated information about vehicle traffic in a city from movement data collected by individual vehicles and shipped to a central server. Movement data are sensitive because they may describe typical movement be...
Chapter
The ability to understand the dynamics of human mobility is crucial for tasks like urban planning and transportation management. The recent rapidly growing availability of large spatio-temporal datasets gives us the possibility to develop sophisticated and accurate analysis methods and algorithms that can enable us to explore several relevant mobil...
Technical Report
Full-text available
This document is the DATA SIM deliverable of WP1 for the first review period of the project (01.09.2011-31.08.2012). The document is mainly a descriptive report of the consortium’s availability of the different datasets that will be used in the project. The document also contains a selection of the main study area and a section about privacy issues...
Article
Full-text available
The huge quantity of positioning data registered by our mobile phones stimulates several research questions, mainly originating from the combination of this huge quantity of data with the extreme heterogeneity of the tracked user and the low granularity of the data. We propose a methodology to partition the users tracked by GSM phone calls into pro...
Article
The availability of massive network and mobility data from diverse domains has fostered the analysis of human behavior and interactions. Broad, extensive, and multidisciplinary research has been devoted to the extraction of non-trivial knowledge from this novel form of data. We propose a general method to determine the influence of social and mobil...
Article
Full-text available
The vision and scientific challenges presented in this paper are the objectives of the FET-FP7 project DATASIM. The project aims at providing an entirely new and highly detailed spatio-temporal microsimulation methodology for human mobility, grounded on massive amounts of big data of various types and from various sources, with the goal to forecast...