Gianni Fenu

Gianni Fenu
Università degli studi di Cagliari | UNICA · Department of Mathematics and Computer Science

Professor

About

228
Publications
47,539
Reads
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4,525
Citations
Introduction
Additional affiliations
March 1988 - March 2021
Università degli studi di Cagliari
Position
  • Professor (Full)

Publications

Publications (228)
Conference Paper
Existing explainable recommender systems have mainly modeled relationships between recommended and already experienced products, and shaped explanation types accordingly (e.g., movie "x'' starred by actress "y'' recommended to a user because that user watched other movies with "y'' as an actress). However, none of these systems has investigated th...
Preprint
In recent years, there has been a stimulating discussion on how artificial intelligence (AI) can support the science and engineering of intelligent educational applications. Many studies in the field are proposing actionable data mining pipelines and machine-learning models driven by learning-related data. The potential of these pipelines and model...
Conference Paper
Full-text available
The relatively recent introduction on the market of low-cost devices able to perform an Electroencephalography (EEG) has opened a stimulating research scenario that involves a large number of researchers previously excluded due to the high costs of such hardware. In this regard, one of the most stimulating research fields is focused on the use of s...
Conference Paper
Full-text available
The rating of users requesting financial services is a growing task, especially in this historical period of the COVID-19 pandemic characterized by a dramatic increase in online activities, mainly related to e-commerce. This kind of assessment is a task manually performed in the past that today needs to be carried out by automatic credit scoring sy...
Preprint
Full-text available
Engaging all content providers, including newcomers or minority demographic groups, is crucial for online platforms to keep growing and working. Hence, while building recommendation services, the interests of those providers should be valued. In this paper, we consider providers as grouped based on a common characteristic in settings in which certa...
Preprint
Existing explainable recommender systems have mainly modeled relationships between recommended and already experienced products, and shaped explanation types accordingly (e.g., movie "x" starred by actress "y" recommended to a user because that user watched other movies with "y" as an actress). However, none of these systems has investigated the ex...
Article
Full-text available
Genetic background and age at first exposure have been identified as critical variables that contribute to individual vulnerability to drug addiction. Evidence shows that genetic factors may account for 40–70% of the variance in liability to addiction. Alcohol consumption by young people, especially in the form of binge-drinking, is becoming an ala...
Preprint
Full-text available
Breast cancer is the most prevalent type of cancer among the female world population. Its early detection has a crucial role in enhancing the effectiveness of treatments, as well as reducing serious complications and deaths. Ultrasound imaging represents a standard diagnostic technique for this purpose, due to its low invasiveness and cost. However...
Preprint
Enabling non-discrimination for end-users of recommender systems by introducing consumer fairness is a key problem, widely studied in both academia and industry. Current research has led to a variety of notions, metrics, and unfairness mitigation procedures. The evaluation of each procedure has been heterogeneous and limited to a mere comparison wi...
Article
In urban scenarios, biometric recognition technologies are being increasingly adopted to empower citizens with a secure and usable access to personalized services. Given the challenging environmental scenarios, combining evidence from multiple biometrics at a certain step of the recognition pipeline has been often proved to increase the performance...
Poster
Full-text available
Anyone working in the field of network intrusion detection has been able to observe how it involves an ever-increasing number of techniques and strategies aimed to overcome the issues that affect the state-of-the-art solutions. Data unbalance and heterogeneity are only some representative examples of them, and each misclassification operates in thi...
Presentation
Full-text available
Anyone working in the field of network intrusion detection has been able to observe how it involves an ever-increasing number of techniques and strategies aimed to overcome the issues that affect the state-of-the-art solutions. Data unbalance and heterogeneity are only some representative examples of them, and each misclassification operates in thi...
Article
Full-text available
The classification and recognition of foliar diseases is an increasingly developing field of research, where the concepts of machine and deep learning are used to support agricultural stakeholders. Datasets are the fuel for the development of these technologies. In this paper, we release and make publicly available the field dataset collected to di...
Article
Full-text available
In the last decades, modern societies are experiencing an increasing adoption of interconnected smart devices. This revolution involves not only canonical devices such as smartphones and tablets, but also simple objects like light bulbs. Named as the Internet of Things (IoT), this ever-growing scenario offers enormous opportunities in many areas of...
Article
Full-text available
Online education platforms play an increasingly important role in mediating the success of individuals’ careers. Therefore, while building overlying content recommendation services, it becomes essential to guarantee that learners are provided with equal recommended learning opportunities, according to the platform principles, context, and pedagogy....
Chapter
Nowadays, Smart Cities applications are becoming steadily popular, thanks to their main objective of improving people daily habits. The services provided by the aforementioned applications may be either addressed to the entire digital population or narrowed towards a specific kind of audience, like drivers and pedestrians. In this sense, the propos...
Conference Paper
Full-text available
Anyone working in the field of network intrusion detection has been able to observe how it involves an ever-increasing number of techniques and strategies aimed to overcome the issues that affect the state-of-the-art solutions. Data unbalance and heterogeneity are only some representative examples of them, and each misclassification operates in thi...
Article
Full-text available
Considering the impact of recommendations on item providers is one of the duties of multi-sided recommender systems. Item providers are key stakeholders in online platforms, and their earnings and plans are influenced by the exposure their items receive in recommended lists. Prior work showed that certain minority groups of providers, characterized...
Preprint
The human voice conveys unique characteristics of an individual, making voice biometrics a key technology for verifying identities in various industries. Despite the impressive progress of speaker recognition systems in terms of accuracy, a number of ethical and legal concerns has been raised, specifically relating to the fairness of such systems....
Preprint
Full-text available
Since their appearance, Smart Cities have aimed at improving the daily life of people, helping to make public services smarter and more efficient. Several of these services are often intended to provide better security conditions for citizens and drivers. In this vein, we present Heimdall, an AI-based video surveillance system for traffic monitorin...
Conference Paper
Full-text available
Since their appearance, Smart Cities have aimed at improving the daily life of people, helping to make public services smarter and more efficient. Several of these services are often intended to provide better security conditions for citizens and drivers. In this vein, we present HEIMDALL, an AI-based video surveillance system for traffic monitorin...
Article
Full-text available
Early diagnosis of leaf diseases is a fundamental tool in precision agriculture, thanks to its high correlation with food safety and environmental sustainability. It is proven that plant diseases are responsible for serious economic losses every year. The aim of this work is to study an efficient network capable of assisting farmers in recognizing...
Article
Full-text available
Every year, plant diseases cause a significant loss of valuable food crops around the world. The plant and crop disease management practice implemented in order to mitigate damages have changed considerably. Today, through the application of new information and communication technologies, it is possible to predict the onset or change in the severit...
Article
Recommender systems learn from historical users’ feedback that is often non-uniformly distributed across items. As a consequence, these systems may end up suggesting popular items more than niche items progressively, even when the latter would be of interest for users. This can hamper several core qualities of the recommended lists (e.g., novelty,...
Article
Full-text available
Decision Support Systems (DSSs) are used in Precision Farming to address climate and environmental changes due to human action. However, increments in the amount of data produced continuously by the latest sensor and satellite technologies, have recently incentivized the integration of Artificial Intelligence (AI). A review of research dedicated to...
Poster
Full-text available
The anomaly-based Intrusion Detection Systems (IDSs) represent one of the most efficient methods in countering the intrusion attempts against the ever growing number of network-based services. Despite the central role they play, their effectiveness is jeopardized by a series of problems that reduce the IDS effectiveness in a real-world context, mai...
Conference Paper
Full-text available
Open innovation is a new paradigm embraced by companies to introduce transformations. It assumes that firms can and should use external and internal ideas to innovate. Recently, commercial and research projects have undergone an exponential growth, leading the open challenge of identifying possible insights on interesting aspects to work on. The ex...
Chapter
To allow individuals to complete voice-based tasks (e.g., send messages or make payments), modern automated systems are required to match the speaker’s voice to a unique digital identity representation for verification. Despite the increasing accuracy achieved so far, it still remains under-explored how the decisions made by such systems may be inf...
Article
Recently, the DSSs application is strongly increasing in the agricultural sector due to continuous climate changes and the need to conduct more productive and sustainable agriculture. In this paper, we describe the prototype agricultural DSS LANDS developed for monitoring the main crop productions in Sardinia. The DSS collects, organizes, integrate...
Conference Paper
Full-text available
The anomaly-based Intrusion Detection Systems (IDSs) represent one of the most efficient methods in countering the intrusion attempts against the ever growing number of network-based services. Despite the central role they play, their effectiveness is jeopardized by a series of problems that reduce the IDS effectiveness in a real-world context, mai...
Chapter
Full-text available
Crop diseases are strongly affected by weather and environmental factors. Weather fluctuations represent the main factors that lead to potential economic losses. The integration of forecasting models based on weather data can provide a framework for agricultural decision-making able to suggest key information for overcoming these problems. In the p...
Preprint
Considering the impact of recommendations on item providers is one of the duties of multi-sided recommender systems. Item providers are key stakeholders in online platforms, and their earnings and plans are influenced by the exposure their items receive in recommended lists. Prior work showed that certain minority groups of providers, characterized...
Preprint
Recommender systems learn from historical data that is often non-uniformly distributed across items, so they may end up suggesting popular items more than niche items. This can hamper user interest and several qualities of the recommended lists (e.g., novelty, coverage, diversity), impacting on the future success of the platform. In this paper, we...
Preprint
Full-text available
Online educational platforms are promising to play a primary role in mediating the success of individuals' careers. Hence, while building overlying content recommendation services, it becomes essential to ensure that learners are provided with equal learning opportunities, according to the platform values, context, and pedagogy. Even though the imp...
Conference Paper
Full-text available
With tons of healthcare reviews being collected online, finding helpful opinions among this collective intelligence is becoming harder. Existing literature in this domain usually tackled helpfulness prediction with machine-learning models optimized for binary classification. While they can filter out a subset of reviews, users might be still overwh...
Chapter
From border controls to personal devices, from online exam proctoring to human-robot interaction, biometric technologies are empowering individuals and organizations with convenient and secure authentication and identification services. However, most biometric systems leverage only a single modality, and may face challenges related to acquisition d...
Article
Full-text available
In recent years, complex networks have become more and more tools of interest to study dynamics related to land analysis. A further step forward was made studying ecological corridors, useful sets of land patches that connect areas of interest otherwise disjointed and independent. Ecological corridors have proven themselves as particularly useful i...
Chapter
Full-text available
The increasing amount of credit offered by financial institutions has required intelligent and efficient methodologies of credit scoring. Therefore, the use of different machine learning solutions to that task has been growing during the past recent years. Such procedures have been used in order to identify customers who are reliable or unreliable,...
Conference Paper
Full-text available
In the recent years, Big Data Analytics and Machine Learning techniques are playing an increasingly key role in the agriculture sector in order to tackle the increasing challenges due to the climate changes which are causing serious damage production. The analysis of environmental, climatic and cultural factors allows to establish the irrigation an...
Preprint
Full-text available
Biologists use optical microscopes to study plankton in the lab, but their size, complexity and cost makes widespread deployment of microscopes in lakes and oceans challenging. Monitoring the morphology, behavior and distribution of plankton in situ is essential as they are excellent indicators of marine environment health and provide a majority of...
Conference Paper
Full-text available
The unbreakable bond that exists today between devices and network connections makes the security of the latter a crucial element for our society. For this reason, in recent decades we have witnessed an exponential growth in research efforts aimed at identifying increasingly efficient techniques able to tackle this type of problem, such as the Intr...
Conference Paper
Full-text available
The automated credit scoring tools play a crucial role in many financial environments, since they are able to perform a real-time evaluation of a user (e.g., a loan applicant) on the basis of several solvency criteria, without the aid of human operators. Such an automation allows who work and offer services in the financial area to take quick decis...
Presentation
Full-text available
The automated credit scoring tools play a crucial role in many financial environments, since they are able to perform a real-time evaluation of a user (e.g., a loan applicant) on the basis of several solvency criteria, without the aid of human operators. Such an automation allows who work and offer services in the financial area to take quick decis...
Presentation
Full-text available
The unbreakable bond that exists today between devices and network connections makes the security of the latter a crucial element for our society. For this reason, in recent decades we have witnessed an exponential growth in research efforts aimed at identifying increasingly efficient techniques able to tackle this type of problem, such as the Intr...
Conference Paper
In this paper, we assess vulnerability of speaker verification systems to dictionary attacks. We seek master voices, i.e., adversarial utterances optimized to match against a large number of users by pure chance. First, we perform menagerie analysis to identify utterances which intrinsically hold this property. Then, we propose an adversarial optim...
Book
Full-text available
ICDSST – the International Conference on Decision Support System Technology – is the flagship event of the Euro Working Group of Decision Support Systems (EWG-DSS). The ICDSST series of conference is relatively young and vibrant (since 2015), while its predecessor, including EWG-DSS workshops and summer schools, has a long tradition. The EWG-DSS wa...
Conference Paper
Full-text available
DSS have evolved significantly since their early development in the 1970s. They have been applied in different sectors as business, financial, medical and many others. Recently their application is strongly increasing in the agricultural sector due to continuous climate changes and the need to conduct more productive and sustainable agriculture. In...
Conference Paper
Social media are providing the humus for the sharing of knowledge and experiences and the growth of community activities (e.g., debating about different topics). The analysis of the user-generated content in this area usually relies on Sentiment Analysis. Word embeddings and Deep Learning have attracted extensive attention in various sentiment dete...
Chapter
Most recommender systems are evaluated on how they accurately predict user ratings. However, individuals use them for more than an anticipation of their preferences. The literature demonstrated that some recommendation algorithms achieve good prediction accuracy, but suffer from popularity bias. Other algorithms generate an item category bias due t...
Conference Paper
Full-text available
The exponential growth of wireless-based solutions, such as those related to the mobile smart devices (e.g., smart-phones and tablets) and Internet of Things (IoT) devices, has lead to countless advantages in every area of our society. Such a scenario has transformed the world a few decades back, dominated by latency, into a new world based on an e...
Poster
Full-text available
The exponential growth of wireless-based solutions, such as those related to the mobile smart devices (e.g., smart-phones and tablets) and Internet of Things (IoT) devices, has lead to countless advantages in every area of our society. Such a scenario has transformed the world a few decades back, dominated by latency, into a new world based on an e...
Article
Full-text available
More and more financial transactions through different E-commerce platforms have appeared now-days within the big data era bringing plenty of opportunities but also challenges and risks of stealing information for potential frauds that need to be faced. This is due to the massive use of tools such as credit cards for electronic payments which are t...
Chapter
During the last decades, a huge amount of data have been collected in clinical databases in the form of medical reports, laboratory results, treatment plans, etc., representing patients health status. Hence, digital information available for patient-oriented decision making has increased drastically but it is often not mined and analyzed in depth s...