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Introduction
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November 2008 - present
Publications
Publications (147)
Today’s universities are more and more focused on improving their educational programs and supporting their students throughout their academic journey. A key aspect of such an effort is understanding which factors contribute to poor students’ performance. This research illustrates how educational process mining techniques can be used to effectively...
Key performance indicators (KPIs) are essential tools for organizations across industries, providing a means to assess and enhance performance, efficiency, and quality. However, predicting KPIs presents challenges due to data nonlinearity, uncertainty, and variability. Traditional approaches, like trend analysis, may struggle to cope with these iss...
Data integration and discovery are open issues in Data Lakes potentially storing hundreds of data sources. The present paper addresses these issues targeting multidimensional data sources, that is sources containing atomic or derived measures aggregated along a number of dimensions, typically derived from raw data for analytical and reporting purpo...
Key performance indicators (KPIs) express the company’s strategy and vision in terms of goals and enable alignment with stakeholder expectations. In business intelligence, forecasting KPIs is pivotal for strategic decision-making. For this reason, in this work, we focus on forecasting KPIs. We built a transformer model architecture that outperforms...
The management of modern solutions for Big Data management and analytics, most notably Data Lakes and Data Lakehouses, is faced with new challenges stemming from the versatility offered by such technologies, as well as the continuously evolving variety and volume of data sources, necessitating the tracking of data quality concerns. In this scenario...
Today’s organizations store lots of data tracking the execution of their business processes. These data often contain valuable information that can be used to predict the evolution of running process executions. The present paper investigates the combined use of Instance Graphs and Deep Graph Convolutional Neural Networks to predict which activity...
Key Performance Indicators (KPIs) are crucial tools that are remarkably used to evaluate business performance. Recently, the management of KPIs has fascinated the focus of both academic and business professionals, and that has led to the development of research on various methods dealing with issues such as modeling, maintenance, and expressiveness...
The integration of the huge data streams produced by the Industrial Internet of Things (IIoT) can provide invaluable knowledge in the context of Industry 4.0, and is also an open research issue. The present paper proposes a semantic approach to this issue, centered around the notion of process as the backbone. We build an ontology describing the fu...
Today’s organizations often have to manage hundreds of process models. This requires organizations to be able to efficiently manage process models as a kind of organizational data. Most of previous approaches for process model representation exploit graph data structures to represent (part of) the process control-flow. While these representations w...
The increased flexibility brought by Data Lake technologies, along with size and heterogeneity of quickly changing data sources, bring novel challenges to their management. Making sense of disparate data and supporting users to identify the most relevant sources for a given analytic request are indeed critical requirements to make data actionable....
Purpose
Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to p...
Environmental, Social, and Corporate Governance (ESG) criteria allow to evaluate business's overall awareness and attention to social and environmental aspects. They are fundamental tools to direct investments towards sustainable projects and activities. However, each ESG rating agency has its own definitions, criteria and methodologies for the sel...
Nowadays, a lot of data regarding business process executions are maintained in event logs. The next activity prediction task exploits such event logs to predict how process executions will unfold up until their completion. The present paper proposes a new approach to address this task: instead of using traces to perform predictions, we propose to...
The present paper explores the opportunity of applying reinforcement learning to various typical tasks in the field of predictive process monitoring. The tasks considered are the prediction of both next event activity and time completion as well as the prediction of the whole progression of running cases. Experiments have been conducted on the popu...
The huge diffusion of social networks has made available an unprecedented amount of publicly-available user-generated data, which may be analyzed in order to determine people’s opinions and
emotions. In this paper we investigate the use of Bidirectional
Encoder Representations from Transformers (BERT) models for both
sentiment analysis and emotion...
The massive adoption of social networks has made available an unprecedented amount of user-generated content, which may be analyzed in order to determine people's opinions and emotions on a large variety of topics. Research has made many efforts in defining accurate algorithms for the analysis of emotions conveyed by texts, however their performanc...
In the last years, data lakes are emerging as an effective and an efficient support for information and knowledge extraction from a huge amount of highly heterogeneous and quickly changing data sources. Data lake management requires the definition of new techniques, very different from the ones adopted for data warehouses in the past. In this scena...
In systems with many components that are required to be constantly active, such as refineries, predicting the components that will break in a time interval after a stoppage may significantly increase their reliability. However, predicting the set of components to be repaired is a challenging task, especially when several conditions (e.g. breakage p...
People’s daily life is increasingly intertwined with smart devices, which are more and more used in dynamic contexts. Therefore, searching and exploiting the wealth of information produced by the Internet of Things (IoT) requires novel models including a representation of the actual context of use. The definition of context is inherently difficult,...
In recent years, pellet has received increasing attention among other biofuels due to its low storage costs and high combustion efficiency. The traceability of pellet quality along the entire supply chain is a critical issue, since fraudulent behaviours, such as the replacement with lower quality pellet, may both cause an economic damage and harm c...
In the last years, the wide availability on the market of low-cost smart devices paved the way for the development of smart environments, which offer an unprecedented opportunity to recognize patterns of activities from the large amount of collected data, with the ultimate aim of monitoring user behavior. In this paper, we propose a methodology whi...
Deviance mining is an emerging area in the field of Process Mining, with the aim of explaining the differences between normal and deviant process executions. Deviance mining approaches typically extract representative subprocesses characterizing normal/deviant behaviors from an event log and use these subprocesses as features for classification. Ex...
In the last decades, Computer Engineering has shown an impressive development and has become a pervasive protagonist in daily life and scientific research. Databases and Artificial Intelligence represent two of the major players in this development. Today, they are quickly converging towards a new, much more sophisticated and inclusive, paradigm, n...
Effective maintenance policies can support companies to deal with process interruptions and consequently, to prevent significant profit losses. Moreover, the proliferation of structured and unstructured data due to production plants validates the application of knowledge discovery in databases techniques to increase processes’ reliability. In this...
With the evolution of the features smart devices are equipped with, the IoT realm is becoming more and more intertwined with people daily-life activities. This has, of course, impacts in the way objects are used, causing a strong increase in both the dynamism of their contexts and the diversification of their objectives. This results in an evolutio...
Science advances and, with it, the storage of large amounts of data. The need to use this data efficiently, quickly and safely is possible thanks to the Big Data Analytics (BDA) that allows us to store and relate data in order to obtain new knowledge. In this paper we present and explain how we constructed the new database, “BEyOND”, that provides...
The recent developments in web technologies, pervasive and ubiquitous systems and networks, cloud and highly distributed computing systems,
and the availability of massive amounts of data have changed the field of computer supported collaboration, particularly with the emergence of
new capabilities and forms of collaboration both locally and remote...
Purpose
The purpose of this paper is developing a data-driven maintenance policy through the analysis of vast amount of data and its application to an oil refinery plant. The maintenance policy, analyzing data regarding sub-plant stoppages and components breakdowns within a defined time interval, supports the decision maker in determining whether...
Measurement and comparison of performances in networked organisations is particularly critical because of heterogeneity and sparsity of data. In particular, each organization is autonomous in the definitions of which measures to use and their calculation formulas, i.e. the mathematical expressions stating how a measure is calculated from others. He...
Conformance checking allows organizations to compare process executions recorded by the IT system against a process model representing the normative behavior. Most of the existing techniques, however, are only able to pinpoint where individual process executions deviate from the normative behavior, without considering neither possible correlations...
Nowadays cloud services are gaining their momentum. A Service Level Agreement (SLA) represents an agreement between a service provider and a customer for a particular service provision. Cloud providers and services are often selected more dynamically than in traditional IT services. Hence, services need to be compared according both to technical as...
Metadata have always played a key role in favoring the cooperation of heterogeneous data sources. This role has become much more crucial with the advent of data lakes, in which case metadata represent the only possibility to guarantee an effective and efficient management of data source interoperability. For this reason, the necessity to define new...
In the last 30 years two important fields were born and have developed rapidly: knowledge discovery and knowledge management based on semantics. In the present chapter we provide an overview of the interlinks between them, taking the perspective of the evolution of systems and platforms supporting knowledge discovery with the help of data semantics...
In recent years, the massive diffusion of social networks has made available a large amount of user-generated content, for the most part in the form of textual data that contain people’s thoughts and emotions about a great variety of topics. In order to exploit these publicly available information, in this work we introduce a social information dis...
In this work, a framework is developed to integrate IoT-based energy management and company's existing information systems. This framework is a multi-layer model that includes three layers: 1) data collection layer, 2) data management layer and 3) data analytics layer. In order to test the proposed approach and assess its impact on improving energy...
A main challenge of today's organizations is the monitoring of their processes to check whether these processes comply with process models specifying the prescribed behavior. Deviations from the prescribed behavior can represent either legitimate work practices not described by the models, which highlight the need of improving it to better reflect...
A growing number of public institutions all over the world has recently started to publish statistical data according to the RDF Data Cube vocabulary, as open and machine-readable Linked Data. Although this approach allows easier data access and consumption, appropriate mechanisms are still needed to perform proper comparisons of statistical data....
Managers of public transport systems have been facing for years the strategic challenge of maintaining high quality of transport services to improve the mobility of citizens, while reducing costs and ensuring safety and low environmental impact. A well-established way to evaluate the performance achieved by the system or by specific activities is t...
Conformance checking allows organizations to verify whether their IT system complies with the prescribed behavior by comparing process executions recorded by the IT system against a process model (representing the norma-tive behavior). However, most of the existing techniques are only able to identify low-level deviations, which provide a scarce su...
University degrees are typically organized in courses with prerequisites among them. If prerequisite are not mandatory, students are left free to attend courses and take exams in almost any order. While favoring flexible organization of the work by students, this practice can also lead to unstructured learning practices and to performance issues. I...
Sentiment analysis calls for large amounts of annotated data, which are usually in short supply and require great efforts in terms of manual annotation. Furthermore, the analysis is often limited to text polarity and writer's emotions are ignored, even if they provide valuable information about writer's feelings that might support a large number of...
The problem of building detection in multi-source aerial data has a large variety of applications from map updating to the detection of illegal construction. The development of a capability to integrate multispectral and LiDAR technologies has been proved to be the most effective strategy in dealing with the problem. An automated and combined appro...
A growing number of public institutions all over the world have recently started to make government statistical data available in open formats, thus enhancing transparency and accountability, stimulating innovation, and promoting civic awareness and engagement. Integration issues related to fragmentation and heterogeneity of these datasets can be p...
The capability to perform comparisons of city performances can be an important guide for stakeholders to detect strengths and weaknesses and to set up strategies for future urban development. Today, the rise of the Open Data culture in public administrations is leading to a larger availability of statistical datasets in machine-readable formats, e....
Real world applications provide many examples of unstructured processes, where process execution is mainly driven by contingent decisions taken by the actors, with the result that the process is rarely repeated exactly in the same way. In these cases, traditional Process Discovery techniques, aimed at extracting complete process models from event l...
One of the most critical issues in Ambient Assisted Living (AAL) is the design of systems that can evolve to meet the requirements of individuals as their needs and health conditions change. Although much work has been done on home and building automation systems for AAL, often referred to as assistive domotics, there is in fact still a substantial...
Ambient Assisted Living (AAL) systems are playing an important role in the modern society, by helping elderly people to live more independently and support daily activities. Knowledge models have been proposed in the past to describe AAL devices. However, models and methodologies capable to provide assistance to system designers during the developm...
Organizations increasingly rely on business process analysis to improve operations performance. Process Mining can be exploited to distill models from real process executions recorded in event logs, but existing techniques show some limitations when applied in complex domains, where human actors have high degree of freedom in the execution of activ...
This chapter presents a new method of Feature Ranking (FR) that calculates the relative weight of features in their original domain with an algorithmic procedure. The method supports information selection of real world features and is useful when the number of features has costs implications. The Feature Extraction (FE) techniques, although accurat...
Performance measurement is the subject of interdisciplinary research on information systems, organizational modeling and decision support systems. The data cube model is usually adopted to represent performance indicators (PI) and enable flexible analysis, visualization and reporting. However, the major obstacles against effective design and manage...
Measurement of Performances Indicators (PIs) in highly distributed environments, especially in networked organisations, is particularly critical because of heterogeneity issues and sparsity of data. In this paper we present a semantics-based approach for dynamic calculation of PIs in the context of sparse distributed data marts. In particular, we p...
Monitoring provides a valid support to detect problems, prevent undesired situations, avoid repeating mistakes, as well as identifying virtuous behaviors both in daily production activities and innovation-oriented initiatives. Key performance indicators (KPIs) are metrics that provide quantifiable data to assess how organizations, business units or...