Intro
Preface
Organization
Abstracts of Keynote Talks
Privacy in the Era of Big Data, Machine Learning, IoT, and 5G
Don't Handicap AI without Explicit Knowledge
Extreme-Scale Model-Based Time Series Management with ModelarDB
Big Minds Sharing their Vision on the Future of AI (Panel)
Contents
Part I
Contents
Part II
Big Data
Reference Architecture for Running Large Scale Data Integration Experiments
1 Introduction
2 Reference Architecture: Logical Level
3 Reference Architecture: Implementation Level
4 Summary
References

Subgroup Discovery with Consecutive Erosion on Discontinuous Intervals
1 Introduction
2 Related Works
3 SD-CEDI Algorithm
3.1 Preliminaries
3.2 SD-CEDI
4 Experimental Results
4.1 Best Quality on Raw Dataset
4.2 Best Quality on Resized Datasets
4.3 Time Comparison
5 Conclusion
References
Fast SQL/Row Pattern Recognition Query Processing Using Parallel Primitives on GPUs
1 Introduction
2 Related Work
2.1 Implementation of SQL/RPR Based on Spark SQL
2.2 SQL Query Processing on GPUs
3 SQL/Row Pattern Recognition
4 Implementation of SQL/RPR on GPUs

4.1 Partition
4.2 Sorting
4.3 Pattern Definition Using Regular Expression
4.4 Pattern Matching
5 Evaluation
5.1 Method Used for Comparison
5.2 Experiment Setup
5.3 Experimental Results
6 Conclusion
References
Scalable Tabular Metadata Location and Classification in Large-Scale Structured Datasets
1 Introduction
2 Definitions
2.1 Non-relational Table Representation
3 Methodology
3.1 Ensemble Architecture
3.2 Large-Scale Evaluation Architecture
4 Experimental Study
4.1 Training the Models
4.2 Training Data
4.3 Test Data
5 Evaluation

6 Related Work
7 Conclusion
References
Unified and View-Specific Multiple Kernel K-Means Clustering
1 Introduction
2 Background
2.1 Kernel k-means (KKM)
2.2 Multiple Kernel k-means (MKKM)
3 The Proposed Method
3.1 A Variant of Kernel k-means
3.2 Unified and View-Specific Multiple Kernel Clustering
3.3 Optimization
4 Experiments and Analysis
4.1 DataSets
4.2 Compared Algorithms
4.3 Experimental Setup
4.4 Clustering Performance
4.5 Kernel Structure and Parameter Sensitivity Study
5 Conclusion
References
Data Analysis and Data Modeling

Augmented Lineage: Traceability of Data Analysis Including Complex UDFs
1 Introduction
2 Related Work
3 Data Model
4 Augmented Lineage
5 Augmented Lineage Derivation
5.1 Segment
5.2 Tracing Query
5.3 Augmented Lineage Derivation Procedure
6 Implementation of Augmented Lineage Derivation
7 Experiment
8 Conclusions and Future Work
References
Neural Ordinary Differential Equations for the Regression of Macroeconomics Data Under the Green Solow Model
1 Introduction
2 The Green Solow Model
3 Related Work
4 Methodology
4.1 Baseline Method
4.2 Proposed Models.