Daniele Apiletti

Orcid: 0000-0003-0538-9775

According to our database¹, Daniele Apiletti authored at least 45 papers between 2006 and 2024.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

DriftLens: A Concept Drift Detection Tool.

[BibT_eX]

[DOI]

Proceedings of the Proceedings 27th International Conference on Extending Database Technology, 2024

2023

ba휌tti at GeoLingIt: Beyond Boundaries, Enhancing Geolocation Prediction and Dialect Classification on Social Media in Italy.

[BibT_eX]

[DOI]

Proceedings of the Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2023), 2023

Combining fault-tolerant persistence and low-latency streaming access to binary data for AI models.

[BibT_eX]

[DOI]

Gabriele Scaffidi Militone

Daniele Apiletti

Giovanni Malnati

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Trusting deep learning natural-language models via local and global explanations.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2022

Exploring waste-collection fleet data: challenges in a real-world use case.

[BibT_eX]

[DOI]

Proceedings of the Workshops of the EDBT/ICDT 2022 Joint Conference, 2022

A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Experimental Comparison of Theory-Guided Deep Learning Algorithms.

[BibT_eX]

[DOI]

Simone Monaco

Daniele Apiletti

Proceedings of the New Trends in Database and Information Systems, 2022

2021

Enhancing manufacturing intelligence through an unsupervised data-driven methodology for cyclic industrial processes.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2021

Explaining the Deep Natural Language Processing by Mining Textual Interpretable Features.

[BibT_eX]

[DOI]

CoRR, 2021

Double-Step deep learning framework to improve wildfire severity classification.

[BibT_eX]

[DOI]

Proceedings of the Workshops of the EDBT/ICDT 2021 Joint Conference, 2021

Cyst segmentation on kidney tubules by means of U-Net deep-learning models.

[BibT_eX]

[DOI]

Christodoulos Xinaris

Vincenzo Viola

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Effective video hyperlinking by means of enriched feature sets and monomodal query combinations.

[BibT_eX]

[DOI]

Mohammad Reza Kavoosifar

Int. J. Multim. Inf. Retr., 2020

Forecasting: theory and practice.

[BibT_eX]

[DOI]

CoRR, 2020

Data-driven exploratory models of an electric distribution network for fault prediction and diagnosis.

[BibT_eX]

[DOI]

Computing, 2020

REDTag: A Predictive Maintenance Framework for Parcel Delivery Services.

[BibT_eX]

[DOI]

IEEE Access, 2020

Evaluating espresso coffee quality by means of time-series feature engineering.

[BibT_eX]

[DOI]

Proceedings of the Workshops of the EDBT/ICDT 2020 Joint Conference, 2020

DSLE: A Smart Platform for Designing Data Science Competitions.

[BibT_eX]

[DOI]

Proceedings of the 44th IEEE Annual Computers, Software, and Applications Conference, 2020

Improving Wildfire Severity Classification of Deep Learning U-Nets from Satellite Images.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Automating concept-drift detection by self-evaluating predictive model degradation.

[BibT_eX]

[DOI]

CoRR, 2019

Transparently Mining Data from a Medium-voltage Distribution Network: A Prognostic-diagnostic Analysis.

[BibT_eX]

[DOI]

Proceedings of the Workshops of the EDBT/ICDT 2019 Joint Conference, 2019

Towards a real-time unsupervised estimation of predictive model degradation.

[BibT_eX]

[DOI]

Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics, 2019

A New Unsupervised Predictive-Model Self-Assessment Approach That SCALEs.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Congress on Big Data, 2019

PREMISES, a Scalable Data-Driven Service to Predict Alarms in Slowly-Degrading Multi-Cycle Industrial Processes.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Congress on Big Data, 2019

2018

iSTEP, an Integrated Self-Tuning Engine for Predictive Maintenance in Industry 4.0.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Parallel & Distributed Processing with Applications, 2018

2017

Frequent Itemsets Mining for Big Data: A Comparative Analysis.

[BibT_eX]

[DOI]

Big Data Res., 2017

A Parallel MapReduce Algorithm to Efficiently Support Itemset Mining on High Dimensional Data.

[BibT_eX]

[DOI]

Big Data Res., 2017

2016

SeLINA: A Self-Learning Insightful Network Analyzer.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Serv. Manag., 2016

SaFe-NeC: A scalable and flexible system for network data characterization.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE/IFIP Network Operations and Management Symposium, 2016

BAC: A Bagged Associative Classifier for Big Data Frameworks.

[BibT_eX]

[DOI]

Luca Venturini

Paolo Garza

Daniele Apiletti

Proceedings of the New Trends in Databases and Information Systems, 2016

2015

PaMPa-HD: A Parallel MapReduce-Based Frequent Pattern Miner for High-Dimensional Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

Enhancing Energy Awareness Through the Analysis of Thermal Energy Consumption.

[BibT_eX]

[DOI]

Federico Boni Castagnetti

Proceedings of the Workshops of the EDBT/ICDT 2015 Joint Conference (EDBT/ICDT), 2015

Energy Signature Analysis: Knowledge at Your Fingertips.

[BibT_eX]

[DOI]

Federico Boni Castagnetti

Proceedings of the 2015 IEEE International Congress on Big Data, New York City, NY, USA, June 27, 2015

A Review of Scalable Approaches for Frequent Itemset Mining.

[BibT_eX]

[DOI]

Daniele Apiletti

Paolo Garza

Fabio Pulvirenti

Proceedings of the New Trends in Databases and Information Systems, 2015

2013

SeaRum: A Cloud-Based Service for Association Rule Mining.

[BibT_eX]

[DOI]

Proceedings of the 12th IEEE International Conference on Trust, 2013

Association Rule Mining as a Cloud-Based Service.

[BibT_eX]

Proceedings of the 21st Italian Symposium on Advanced Database Systems, 2013

Desidoo, a Big-Data Application to Join the Online and Real-World Marketplaces.

[BibT_eX]

[DOI]

Daniele Apiletti

Fabio Forno

Proceedings of the New Trends in Databases and Information Systems, 2013

2012

MaskedPainter: Feature selection for microarray data analysis.

[BibT_eX]

[DOI]

Intell. Data Anal., 2012

2011

Energy-saving models for wireless sensor networks.

[BibT_eX]

[DOI]

Daniele Apiletti

Elena Baralis

Tania Cerquitelli

Knowl. Inf. Syst., 2011

2009

Extraction of Constraints from Biological Data.

[BibT_eX]

[DOI]

Proceedings of the Biomedical Data and Applications, 2009

Real-Time Analysis of Physiological Data to Support Medical Applications.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Technol. Biomed., 2009

Characterizing network traffic by means of the NetMine framework.

[BibT_eX]

[DOI]

Comput. Networks, 2009

2008

Real-Time Individuation of Global Unsafe Anomalies and Alarm Activation.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Techniques and Tools for Novel System Architectures, 2008

Generalized association rules to support Network Digest analysis.

[BibT_eX]

Proceedings of the Sixteenth Italian Symposium on Advanced Database Systems, 2008

2007

SAPhyRA: Stream Analysis for Physiological Risk Assessment.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007), 2007

2006

Data Cleaning and Semantic Improvement in Biological Databases.

[BibT_eX]

[DOI]

J. Integr. Bioinform., 2006

Daniele Apiletti

Timeline

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