Grossi Valerio
Valerio Grossi holds a Ph.D. in Computer Science from the University of Pisa. His research interests focus on the analysis of massive and complex data including mining data streams, ontology-driven mining, business intelligence and knowledge discovery systems. He took part in several European research projects as a member of the UNIPI research group, among which figure BRITE (Business Register Interoperability throughout Europe), MUSING (MUlti-industry, Semantic-based next generation business INtelliGence) and ICON (Inductive Constraint Programming), where he focused on the development of brand new data mining and knowledge discovery applications and on the research for the development of new business intelligence approaches.
Topics:
Mining Data Streams
Constrained Data Mining
PHD in Computer Science at University of Pisa
- Position
- Researcher
- Affiliation
- Istituto di Scienza e Tecnologie dell’Informazione, National Research Council of Italy (ISTI-CNR)
- Phone
- +39 050 221 2701
- Homepage
Projects
SoBigData.eu - SoBigData: Social Mining and Big Data Ecosystem
Publications
2018
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, “SoBigData: Social Mining & Big Data Ecosystem”, in Companion of the The Web Conference 2018 on The Web Conference 2018, 2018.
2017
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, “HyWare: a HYbrid Workflow lAnguage for Research E-infrastructures”, D-Lib Magazine, vol. 23, 2017.
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, “Survey on using constraints in data mining”, Data Mining and Knowledge Discovery, vol. 31, pp. 424–464, 2017.
2016
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, “Data Mining and Constraints: An Overview”, in Data Mining and Constraint Programming, Springer International Publishing, 2016, pp. 25–48.
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, “Partition-Based Clustering Using Constraint Optimization”, in Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach, Springer International Publishing, 2016, pp. 282–299.
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, “Driving Profiles Computation and Monitoring for Car Insurance CRM”, Journal ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, pp. 14:1–14:26, 2016.
2015
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, “Clustering Formulation Using Constraint Optimization”, in Software Engineering and Formal Methods - {SEFM} 2015 Collocated Workshops: ATSE, HOFM, MoKMaSD, and VERY*SCART, York, UK, September 7-8, 2015, Revised Selected Papers, 2015.
2008
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, “Discovering Strategic Behaviour in Multi- Agent Scenarios by Ontology-Driven Mining”, in Advances in Robotics, Automation and Control, 2008.
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, “A Case Study in Sequential Pattern Mining for IT-Operational Risk”, in ECML/PKDD (1), 2008, pp. 424-439.
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, “Ontological Support for Association Rule Mining”, in IASTED International Conference on Artificial Intelligence and Applications (AIA), Innsbruck, Austria , 2008.
