Francesco Ventura
Francesco Ventura
PhD student at DAUIN - Politecnico di Torino
Email verificata su polito.it
Titolo
Citata da
Citata da
Anno
Self-tuning techniques for large scale cluster analysis on textual data collections
E Di Corso, T Cerquitelli, F Ventura
Proceedings of the Symposium on Applied Computing, 771-776, 2017
232017
iSTEP, an integrated Self-Tuning Engine for Predictive maintenance in Industry 4.0
D Apiletti, C Barberis, T Cerquitelli, A Macii, E Macii, M Poncino, F Ventura
2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications …, 2018
152018
Data miners' little helper: data transformation activity cues for cluster analysis on document collections
T Cerquitelli, E Di Corso, F Ventura, S Chiusano
Proceedings of the 7th International Conference on Web Intelligence, Mining …, 2017
92017
A cloud-to-edge approach to support predictive analytics in robotics industry
S Panicucci, N Nikolakis, T Cerquitelli, F Ventura, S Proto, E Macii, ...
Electronics 9 (3), 492, 2020
82020
A new unsupervised predictive-model self-assessment approach that SCALEs
F Ventura, S Proto, D Apiletti, T Cerquitelli, S Panicucci, E Baralis, E Macii, ...
2019 IEEE International Congress on Big Data (BigDataCongress), 144-148, 2019
82019
Useful ToPIC: Self-tuning strategies to enhance latent Dirichlet allocation
S Proto, E Di Corso, F Ventura, T Cerquitelli
2018 IEEE International Congress on Big Data (BigData Congress), 33-40, 2018
82018
All in a twitter: Self-tuning strategies for a deeper understanding of a crisis tweet collection
E Di Corso, F Ventura, T Cerquitelli
2017 IEEE International Conference on Big Data (Big Data), 3722-3726, 2017
82017
Clustering-based assessment of residential consumers from hourly-metered data
T Cerquitelli, G Chicco, E Di Corso, F Ventura, G Montesano, M Armiento, ...
2018 International Conference on Smart Energy Systems and Technologies (SEST …, 2018
72018
Discovering electricity consumption over time for residential consumers through cluster analysis
T Cerquitelli, G Chicco, E Di Corso, F Ventura, G Montesano, A Del Pizzo, ...
2018 International Conference on Development and Application Systems (DAS …, 2018
72018
PREMISES, a scalable data-driven service to predict alarms in slowly-degrading multi-cycle industrial processes
S Proto, F Ventura, D Apiletti, T Cerquitelli, E Baralis, E Macii, A Macii
2019 IEEE International Congress on Big Data (BigDataCongress), 139-143, 2019
62019
Towards a real-time unsupervised estimation of predictive model degradation
T Cerquitelli, S Proto, F Ventura, D Apiletti, E Baralis
Proceedings of Real-Time Business Intelligence and Analytics, 1-6, 2019
52019
What's in the box? Explaining the black-box model through an evaluation of its interpretable features
F Ventura, T Cerquitelli
arXiv preprint arXiv:1908.04348, 2019
42019
Black-box model explained through an assessment of its interpretable features
F Ventura, T Cerquitelli, F Giacalone
European Conference on Advances in Databases and Information Systems, 138-149, 2018
42018
Automating concept-drift detection by self-evaluating predictive model degradation
T Cerquitelli, S Proto, F Ventura, D Apiletti, E Baralis
arXiv preprint arXiv:1907.08120, 2019
22019
Enhancing manufacturing intelligence through an unsupervised data-driven methodology for cyclic industrial processes
T Cerquitelli, F Ventura, D Apiletti, E Baralis, E Macii, M Poncino
Expert Systems with Applications, 115269, 2021
2021
Discussion Paper Prompting the data transformation activities for cluster analysis on collections of documents
T Cerquitelli, E Di Corso, F Ventura, S Chiusano
2020
DSLE: A Smart Platform for Designing Data Science Competitions
G Attanasio, F Giobergia, A Pasini, F Ventura, E Baralis, L Cagliero, ...
2020 IEEE 44th Annual Computers, Software, and Applications Conference …, 2020
2020
Enabling predictive analytics for smart manufacturing through an IIoT platform
T Cerquitelli, N Nikolakis, P Bethaz, S Panicucci, F Ventura, E Macii, ...
IFAC-PapersOnLine 53 (3), 179-184, 2020
2020
Expand your Training Limits! Generating Training Data for ML-based Data Management
F Ventura, Z Kaoudi, V Markl
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–19