Michela Fazzolari

Michela Fazzolari
  • Italian National Research Council

About

30
Publications
9,557
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738
Citations
Current institution
Italian National Research Council

Publications

Publications (30)
Chapter
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Artificial Intelligence (AI) has become an integral part of our lives, and Explainable Artificial Intelligence (XAI) is becoming more essential to ensure trustworthiness and comply with regulations. XAI methodologies help to explain the automatic processing behind data analysis. This paper provides an overview of the use of XAI in the educational d...
Preprint
Full-text available
The recent spread of cloud services has enabled many companies to take advantage of them. Nevertheless, the main concern about the adoption of cloud services remains the lack of transparency perceived by customers regarding security and privacy. To overcome this issue, Cloud Service Certifications (CSCs) have emerged as an effective solution to inc...
Chapter
Full-text available
Artificial Intelligence-based methods have been thoroughly applied in various fields over the years and the educational scenario is not an exception. However, the usage of the so-called explainable Artificial Intelligence, even if desirable, is still limited, especially whenever we consider educational datasets. Moreover, the time dimension is not...
Conference Paper
Full-text available
Virtual Learning Environments (VLEs) are online educational platforms that combine static educational content with interactive tools to support the learning process. Click-based data, reporting the students' interactions with the VLE, are continuously collected, so automated methods able to manage big, non-stationary, and changing data are necessar...
Article
Full-text available
The problem analyzed in this paper deals with the classification of Internet traffic. During the last years, this problem has experienced a new hype, as classification of Internet traffic has become essential to perform advanced network management. As a result, many different methods based on classical Machine Learning and Deep Learning have been p...
Chapter
In this paper, we introduce the rationale, goals, and structure of Presente Digitale, an ambitious Italian project for the realization of an online education system on Digital Culture. Presente Digitale is dedicated to teachers and their students. Its aim is to offer paths of reflection closely linked to the digital world, which can respond to the...
Article
Over the past few years, online reviews have become very important, since they can influence the purchase decision of consumers and the reputation of businesses. Therefore, the practice of writing fake reviews can have severe consequences on customers and service providers. Various approaches have been proposed for detecting opinion spam in online...
Preprint
Full-text available
Over the last years, online reviews became very important since they can influence the purchase decision of consumers and the reputation of businesses, therefore, the practice of writing fake reviews can have severe consequences on customers and service providers. Various approaches have been proposed for detecting opinion spam in online reviews, e...
Article
Full-text available
Nowadays, a huge amount of data are generated, often in very short time intervals and in various formats, by a number of different heterogeneous sources such as social networks and media, mobile devices, internet transactions, networked devices and sensors. These data, identified as Big Data in the literature, are characterized by the popular Vs fe...
Article
Nowadays, companies and enterprises are more and more incline to exploit the pervasive action of on-line social media, such as Facebook, Twitter and Instagram. Indeed, several promotional and marketing campaigns are carried out by concurrently adopting several social medial channels. These campaigns reach very quickly a wide range of different cate...
Article
Full-text available
The purpose of this paper is to show the application of a set of intelligent data analysis techniques to about 7 million of online travel reviews, with the aim of automatically extracting useful information. The reviews, collected from two popular online tourism-related review platforms, are all those posted by reviewers about one specific Italian...
Chapter
In this paper, we propose and test an approach based on regression models, to predict the review score of an item, across different reviewer categories. The analysis is based on a public dataset with more than 2.5 million hotel reviews, belonging to five specific reviewers’ categories. We first compute the relation between the average scores associ...
Article
Full-text available
In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the sa...
Preprint
In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the sa...
Conference Paper
In this paper, we propose a novel approach for aggregating online reviews, according to the opinions they express. Our methodology is unsupervised, due to the fact that it does not rely on pre-labeled reviews, and it is agnostic, since it does not make any assumption about the domain or the language of the review content. We measure the adherence o...
Article
Full-text available
In this paper, we propose a novel approach for aggregating online reviews, according to the opinions they express. Our methodology is unsupervised - due to the fact that it does not rely on pre-labeled reviews - and it is agnostic - since it does not make any assumption about the domain or the language of the review content. We measure the adherenc...
Article
Full-text available
How to deploy and manage, in an efficient and adaptive way, complex applications across multiple heterogeneous cloud platforms is one of the problems that have emerged with the cloud revolution. In this paper we present context, motivations and objectives of the EU research project SeaClouds, which aims at enabling a seamless adaptive multi-cloud m...
Article
Multi-objective evolutionary algorithms represent an effective tool to improve the accuracy-interpretability trade-off of fuzzy rule-based classification systems. To this aim, a tuning process and a rule selection process can be combined to obtain a set of solutions with different trade-offs between the accuracy and the compactness of models. Never...
Article
In the framework of genetic fuzzy systems, the computational time required by genetic algorithms for generating fuzzy rule-based models from data increases considerably with the increase of the number of instances in the training set, mainly due to the fitness evaluation. Also, the amount of data typically affects the complexity of the resulting mo...
Conference Paper
A multi-objective evolutionary fuzzy rule selection process extracts a subset of fuzzy rules from an initial set, by applying a multi-objective evolutionary algorithm. Two approaches can be used to determine the number of terms (i.e. the granularity) associated with the linguistic variables that appear in the rules: a pre-established single granula...
Article
Over the past few decades, fuzzy systems have been widely used in several application fields, thanks to their ability to model complex systems. The design of fuzzy systems has been successfully performed by applying evolutionary and, in particular, genetic algorithms, and recently, this approach has been extended by using multiobjective evolutionar...
Conference Paper
When considering data sets characterized by a large number of instances, the computational time required to apply Genetic Algorithms for generating Fuzzy Rule-Based Classifiers increases considerably, mainly due to the fitness evaluation. Another important problem associated to these kinds of data sets is an undesired increase of the obtained model...
Article
Full-text available
In this work, an intelligent system for automatic detection of fault in PV fields is proposed. This system is based on a Takagi-Sugeno-Kahn Fuzzy Rule-Based System (TSK-FRBS), which provides an estimation of the instant power production of the PV field in normal functioning, i.e, when no faults occur. Then, the estimated power is compared with the...

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