| Nome |
# |
|
Analysis of Twitter Data Using a Multiple-level Clustering Strategy, file e384c42e-2bcc-d4b2-e053-9f05fe0a1d67
|
2.711
|
|
Analysis of diabetic patients through their examination history, file e384c42e-2de2-d4b2-e053-9f05fe0a1d67
|
887
|
|
An On-line BIST RAM Architecture with Self Repair Capabilities, file e384c42d-e3fd-d4b2-e053-9f05fe0a1d67
|
842
|
|
Online and Offline BIST in IP-Core Design, file e384c42d-e0ff-d4b2-e053-9f05fe0a1d67
|
795
|
|
On integrating a proprietary and a commercial architecture for optimal BIST performances in SoCs, file e384c42d-f649-d4b2-e053-9f05fe0a1d67
|
604
|
|
Energy Signature Analysis: Knowledge at Your Fingertips, file e384c42d-ba62-d4b2-e053-9f05fe0a1d67
|
562
|
|
A Self-Repairing Execution Unit for Microprogrammed Processors, file e384c42d-ee35-d4b2-e053-9f05fe0a1d67
|
527
|
|
Modeling correlations among air pollution-related data through generalized association rules, file e384c42f-1713-d4b2-e053-9f05fe0a1d67
|
490
|
|
Automated Synthesis of SEU Tolerant Architectures from OO Descriptions, file e384c42d-ece1-d4b2-e053-9f05fe0a1d67
|
479
|
|
Digging deep into weighted patient data through multiple-level patterns, file e384c42d-b1f8-d4b2-e053-9f05fe0a1d67
|
467
|
|
Testing Embedded Memories in Telecommunication Systems, file e384c42d-ee2f-d4b2-e053-9f05fe0a1d67
|
453
|
|
On applying the set covering model to reseeding, file e384c42d-ed00-d4b2-e053-9f05fe0a1d67
|
426
|
|
NEMICO: Mining network data through cloud-based data mining techniques, file e384c42e-38c8-d4b2-e053-9f05fe0a1d67
|
422
|
|
Early prediction of the highest workload in incremental cardiopulmonary tests, file e384c42e-2de4-d4b2-e053-9f05fe0a1d67
|
411
|
|
Pattern Set Mining with Schema-based Constraint, file e384c42d-ac9e-d4b2-e053-9f05fe0a1d67
|
389
|
|
DFT and BIST of a multichip module for high-energy physics experiments, file e384c42d-ee30-d4b2-e053-9f05fe0a1d67
|
385
|
|
Analyzing Air Pollution on the Urban Environment, file e384c42f-1ab4-d4b2-e053-9f05fe0a1d67
|
384
|
|
Monitoring the citizens’ perception on urban security
in Smart City environments, file e384c42e-cf96-d4b2-e053-9f05fe0a1d67
|
373
|
|
MeTA: Characterization of medical treatments at different abstraction levels, file e384c42d-b258-d4b2-e053-9f05fe0a1d67
|
359
|
|
Discovering High-Utility Itemsets at Multiple Abstraction Levels, file e384c42f-a7e6-d4b2-e053-9f05fe0a1d67
|
344
|
|
HD2BIST: a hierarchical framework for BIST scheduling, data patterns delivering and diagnosis in SoCs, file e384c42d-f64b-d4b2-e053-9f05fe0a1d67
|
314
|
|
Exploiting clustering algorithms in a multiple-level fashion: A comparative study in the medical care scenario, file e384c42e-8ff7-d4b2-e053-9f05fe0a1d67
|
241
|
|
A High-level EDA Environment for the Automatic Insertion of HD-BIST Structures, file e384c42d-ee33-d4b2-e053-9f05fe0a1d67
|
193
|
|
Discovering air quality patterns in urban environments, file e384c42f-13e2-d4b2-e053-9f05fe0a1d67
|
191
|
|
DSLE: A Smart Platform for Designing Data Science Competitions, file e384c432-5eb3-d4b2-e053-9f05fe0a1d67
|
160
|
|
Data mining for better healthcare: A path towards automated data analysis?, file e384c42f-3998-d4b2-e053-9f05fe0a1d67
|
156
|
|
An effective distributed BIST architecture for RAMs, file e384c42d-f64e-d4b2-e053-9f05fe0a1d67
|
132
|
|
Predicting cardiopulmonary response to incremental exercise test, file e384c42e-9687-d4b2-e053-9f05fe0a1d67
|
86
|
|
Predicting Car Availability in Free Floating Car Sharing Systems: Leveraging Machine Learning in Challenging Contexts, file e384c432-811f-d4b2-e053-9f05fe0a1d67
|
73
|
|
An explainable data-driven approach to web directory taxonomy mapping, file e384c432-e2d5-d4b2-e053-9f05fe0a1d67
|
59
|
|
Forecasting Heating Consumption in Buildings: A Scalable Full-Stack Distributed Engine, file e384c430-c403-d4b2-e053-9f05fe0a1d67
|
49
|
|
Characterizing situations of dock overload in bicycle sharing stations, file e384c430-bc23-d4b2-e053-9f05fe0a1d67
|
43
|
|
Prompting the data transformation activities for cluster analysis on collections of documents, file e384c430-1f1c-d4b2-e053-9f05fe0a1d67
|
42
|
|
Towards automated visualisation of scientic literature, file e384c430-ca90-d4b2-e053-9f05fe0a1d67
|
41
|
|
MNEMONIC: atlante digitale della memoria del presente. Il patrimonio culturale e naturale nell’Italia in lockdown, file ea735117-4bfd-45a1-a43f-81399a6ead93
|
35
|
|
Towards an Automated, Fast and Interpretable Estimation Model of Heating Energy Demand: A Data-Driven Approach Exploiting Building Energy Certificates, file e384c431-a3e5-d4b2-e053-9f05fe0a1d67
|
34
|
|
A Novel DB CASE Tool for Relational Databases, file 369ef4f7-6c1a-43d8-9faa-6326b53ff110
|
29
|
|
Twitter data laid almost bare: An insightful exploratory analyser, file e384c433-93d4-d4b2-e053-9f05fe0a1d67
|
27
|
|
iDREAM: a multidisciplinary methodology and integrated toolset for flight vehicle engineering, file 15dcf6f0-b8ea-4248-83ed-774e4c1ff074
|
26
|
|
Advances in Databases and Information Systems - 26th European Conference, ADBIS 2022, Turin, Italy, September 5-8, 2022, Proceedings, file 5555d236-935e-44f8-b850-aec9f32409d2
|
26
|
|
New Trends in Database and Information Systems - ADBIS 2022 Short Papers, Doctoral Consortium and Workshops: DOING, K-GALS, MADEISD, MegaData, SWODCH, Turin, Italy, September 5-8, 2022, Proceedings, file 3bc279c7-e0f9-46d2-afd8-550088a0f0aa
|
23
|
|
Big data analytics for smart cities, file e384c434-168c-d4b2-e053-9f05fe0a1d67
|
21
|
|
Human lunar lander system design, cost estimation and technology roadmaps, file 6a9ea798-fa3b-4d11-8a3e-492c5376b219
|
20
|
|
On integrating a proprietary and a commercial architecture for optimal BIST performances in SoCs, file e384c42d-f64a-d4b2-e053-9f05fe0a1d67
|
18
|
|
Characterizing unpredictable patterns in Wireless Sensor Network data, file e384c431-80bb-d4b2-e053-9f05fe0a1d67
|
10
|
|
DSLE: A Smart Platform for Designing Data Science Competitions, file e384c432-3460-d4b2-e053-9f05fe0a1d67
|
7
|
|
CarPredictor: forecasting the number of free floating car sharing vehicles within restricted urban areas, file e384c430-f5e0-d4b2-e053-9f05fe0a1d67
|
6
|
|
Twitter data laid almost bare: An insightful exploratory analyser, file e384c431-7e84-d4b2-e053-9f05fe0a1d67
|
6
|
|
La costruzione di un progetto di conoscenza storica in ambiente digitale. L’Atlante dei palazzi comunali e dei luoghi del potere collettivo nel Medioevo, file 50c52512-7004-4337-b573-ff8e268b38a0
|
4
|
|
Microlauncher design, cost estimation and technology roadmaps, file 463b87a2-dfdf-4554-b301-cada384863e8
|
3
|
|
Analyzing Air Pollution on the Urban Environment, file e384c42f-13e3-d4b2-e053-9f05fe0a1d67
|
3
|
|
An explainable data-driven approach to web directory taxonomy mapping, file e384c432-6855-d4b2-e053-9f05fe0a1d67
|
3
|
|
Complementing Location-Based Social Network Data With Mobility Data: A Pattern-Based Approach, file 8f88c9ea-77d1-4552-b7ba-2dce5df55981
|
2
|
|
Enhancing energy awareness through the analysis of thermal energy consumption, file e384c42e-3991-d4b2-e053-9f05fe0a1d67
|
2
|
|
Scalable out-of-core itemset mining, file e384c42e-d651-d4b2-e053-9f05fe0a1d67
|
2
|
|
Predicting critical conditions in bicycle sharing systems, file e384c42e-f1f5-d4b2-e053-9f05fe0a1d67
|
2
|
|
null, file e384c42f-14c0-d4b2-e053-9f05fe0a1d67
|
2
|
|
A Clustering-Based Approach to Analyse Examinations for Diabetic Patients, file e384c42f-3b11-d4b2-e053-9f05fe0a1d67
|
2
|
|
Exploiting clustering algorithms in a multiple-level fashion: A comparative study in the medical care scenario, file e384c433-4ee2-d4b2-e053-9f05fe0a1d67
|
2
|
|
Misleading generalized itemset mining in the cloud, file e384c42e-2fc9-d4b2-e053-9f05fe0a1d67
|
1
|
|
Analysis of diabetic patients through their examination history, file e384c42e-a47c-d4b2-e053-9f05fe0a1d67
|
1
|
|
Discovering air quality patterns in urban environments, file e384c42f-174d-d4b2-e053-9f05fe0a1d67
|
1
|
|
Supporting the analysis of urban data through NOSQL technologies, file e384c42f-2b36-d4b2-e053-9f05fe0a1d67
|
1
|
|
New Trends in Databases and Information Systems, 17th East European Conference on Advances in Databases and Information Systems, ADBIS 2013, Genoa, Italy, September 1-4, 2013. Proceedings II, file e384c42f-41e3-d4b2-e053-9f05fe0a1d67
|
1
|
|
P-Mine: Parallel itemset mining on large datasets, file e384c42f-4214-d4b2-e053-9f05fe0a1d67
|
1
|
|
Data miners' little helper: data transformation activity cues for cluster analysis on document collections, file e384c42f-8ba7-d4b2-e053-9f05fe0a1d67
|
1
|
|
New Trends in Databases and Information Systems: Contributions from ADBIS 2017 workshops, file e384c42f-8ba8-d4b2-e053-9f05fe0a1d67
|
1
|
|
Characterizing Air-Quality Data Through Unsupervised Analytics Methods, file e384c430-405a-d4b2-e053-9f05fe0a1d67
|
1
|
|
A Knowledge-Based Multi-Criteria Decision Support System Encompassing Cascading Effects For Disaster Management, file e384c431-80c6-d4b2-e053-9f05fe0a1d67
|
1
|
|
Digging deep into weighted patient data through multiple-level patterns, file e384c431-b207-d4b2-e053-9f05fe0a1d67
|
1
|
|
Breakthroughs on Cross-Cutting Data Management, Data Analytics, and Applied Data Science, file e384c434-3afd-d4b2-e053-9f05fe0a1d67
|
1
|
|
null, file e51b8a52-3698-4503-a77b-1cad78857c1a
|
1
|
|
Diversity and Inclusion Activities in Database Conferences: A 2021 Report, file ea738920-9c7b-4e68-bedf-91f7bc66b441
|
1
|
|
Editorial special issue on data analytics for engineering, science and society, file ef84a8a4-73ca-4350-9d6c-a82f8e4c0fae
|
1
|
| Totale |
14.420 |
Archivio Istituzionale della Ricerca