A5066196370- Data Management and Algorithms
- Advanced Database Systems and Queries
- Data Quality and Management
- Data Stream Mining Techniques
- Data Visualization and Analytics
- Data Mining Algorithms and Applications
- Semantic Web and Ontologies
- Smart Agriculture and AI
- Web Data Mining and Analysis
- Data-Driven Disease Surveillance
- Big Data and Business Intelligence
- Privacy-Preserving Technologies in Data
- Automated Road and Building Extraction
- Human Mobility and Location-Based Analysis
- Greenhouse Technology and Climate Control
- Scientific Computing and Data Management
- Advanced Text Analysis Techniques
- IoT and Edge/Fog Computing
- Machine Learning and Data Classification
- Time Series Analysis and Forecasting
- Irrigation Practices and Water Management
- Modular Robots and Swarm Intelligence
- Media Influence and Politics
- Anomaly Detection Techniques and Applications
- Educational Assessment and Pedagogy
University of Bologna
2014-2024
Azienda-Unita' Sanitaria Locale Di Cesena
2017-2024
The University of Queensland
2021
Polish-Japanese Academy of Information Technology
2021
Hong Kong University of Science and Technology
2021
Trajectory data has become ubiquitous nowadays, which can benefit various real-world applications such as traffic management and location-based services. However, trajectories may disclose highly sensitive information of an individual including mobility patterns, personal profiles gazetteers, social relationships, etc, making it indispensable to consider privacy protection when releasing trajectory data. Ensuring on demands more than hiding single locations, since are intrinsically sparse...
In this study, we analyze how crop management will benefit from the Internet of Things (IoT) by providing an overview its architecture and components agronomic technological perspectives. The present analysis highlights that IoT is a mature enabling technology with articulated hardware software components. Cheap networked devices can sense fields at finer grain to give timeliness warnings on presence stress conditions diseases wider range farmers. Cloud computing allows reliable storage,...
Autonomous robots in the agri-food sector are increasing yearly, promoting application of precision agriculture techniques. The same applies to online services and techniques implemented over Internet, such as Internet Things (IoT) cloud computing, which make big data, edge digital twins technologies possible. Developers autonomous vehicles understand that for must take advantage these on strengthen their usability. This integration can be achieved using different strategies, but existing...
Social BI (SBI) is the emerging discipline that aims at combining corporate data with textual user-generated content (UGC) to let decision-makers analyze their business based on trends perceived from environment. Despite increasing diffusion of SBI applications, no specific and organic design methodology available yet. In this paper we propose an iterative for designing maintaining applications reorganizes activities tasks normally carried out by practitioners. Effective support quick...
Trajectory-based spatiotemporal entity linking is to match the same moving object in different datasets based on their movement traces. It a fundamental step support data integration and analysis. In this paper, we study problem of using effective concise signatures extracted from trajectories. This formalized as k-nearest neighbor (k-NN) query signatures. Four representation strategies (sequential, temporal, spatial, spatiotemporal) two quantitative criteria (commonality unicity) are...
Engineering resilient distributed systems remains extremely challenging, particularly in mapping from collective specifications to individual device behavior. Aggregate programming aims address this problem using a computational field abstraction provide inherent guarantees of resilience, scalability, and safe composition. These capabilities are provided, however, by an expressive but terse set operators too low-level for pragmatic use complex development. We thus present API raise the level...
The Intentional Analytics Model (IAM) has been recently envisioned as a new paradigm to couple OLAP and analytics. It relies on two basic ideas: (i) letting the user explore data by expressing her analysis intentions rather than she needs, (ii) returning enhanced cubes, i.e., multidimensional annotated with knowledge insights in form of interesting model components (e.g., clusters). In this paper we contribute give proof-of-concept for IAM vision delivering an end-to-end implementation...
<div>Trajectory data has become ubiquitous nowadays, which can benefit various real-world applications such as traffic management and location-based services. However, trajectories may disclose highly sensitive information of an individual including mobility patterns, personal profiles gazetteers, social relationships, etc, making it indispensable to consider privacy protection when releasing trajectory data. Ensuring on demands more than hiding single locations, since are...
Abstract Multistores are data management systems that enable query processing across different and heterogeneous databases; besides the distribution of data, complexity factors like schema heterogeneity replication must be resolved through integration fusion activities. Our multistore solution relies on a dataspace to provide user with an integrated view available enables formulation execution GPSJ queries. In this paper, we propose technique optimize queries by formulating evaluating plans...
Spatio-temporal mobility patterns are at the core of strategic applications such as urban planning and monitoring. Depending on strength spatio-temporal constraints, different can be defined. While existing approaches work well in extraction groups objects sharing fine-grained paths, huge volume large-scale data asks for coarse-grained solutions. In this paper, we introduce Colossal Trajectory Mining (CTM) to efficiently extract heterogeneous out a multidimensional space that, along with...
<div>Trajectory data has become ubiquitous nowadays, which can benefit various real-world applications such as traffic management and location-based services. However, trajectories may disclose highly sensitive information of an individual including mobility patterns, personal profiles gazetteers, social relationships, etc, making it indispensable to consider privacy protection when releasing trajectory data. Ensuring on demands more than hiding single locations, since are...