Database and Expert Systems Applications

Name: Database and Expert Systems Applications | 32nd International Conference, DEXA 2021, Virtual Event, September 27-30, 2021, Proceedings, Part I
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32nd International Conference, DEXA 2021, Virtual Event, September 27-30, 2021, Proceedings, Part I

Christine Strauss Gabriele Kotsis A. Min Tjoa Ismail Khalil(Editor)

Springer (Publisher)

Published on 31. August 2021

XXVIII, 393 pages

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978-3-030-86472-9 (ISBN)

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Content

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
5 Performance Evaluation
5.1 Experimental Setup
5.2 Results and Discussion
6 Conclusion
References
A Quantum-Inspired Neural Network Model for Predictive BPaaS Management
1 Introduction
2 Related Work
3 Resource Usage Prediction Model
3.1 Multi-layer Perceptron for Resource Usage Prediction
3.2 Quantum Genetic Algorithm for the Neural Network's Training
4 Experiments
4.1 Evaluation of the Prediction Model
4.2 Evaluation of the Placement Quality
5 Conclusion and Future Work
References
Predicting Psychiatric Diseases Using AutoAI: A Performance Analysis Based on Health Insurance Billing Data
1 Introduction
2 Method
2.1 Data
2.2 AutoAI Frameworks, Development Environment, and Configuration
3 Results
3.1 Watson AutoAI
3.2 Auto-Sklearn
4 Discussion
5 Conclusion
References
Improving Billboard Advertising Revenue Using Transactional Modeling and Pattern Mining
1 Introduction
2 Proposed Framework of the Problem
3 Proposed Billboard Allocation Framework
4 Performance Evaluation
5 Conclusion
References
Sarcasm Detection for Japanese Text Using BERT and Emoji
1 Introduction
2 Related Works
3 Proposed Method
3.1 Definition of Sarcasm
3.2 Overview of Proposed Method
3.3 BERT: Bidirectional Encoder Representations from Transformers
3.4 Word2Vec
4 Experiment
4.1 Dataset and Preprocessing
4.2 Experimental Setup
4.3 Experimental Results
5 Conclusion
References
Sigmalaw PBSA - A Deep Learning Model for Aspect-Based Sentiment Analysis for the Legal Domain
1 Introduction
2 Related Work
2.1 Legal Information Extraction
2.2 Existing Aspect-Based Sentiment Analysis Models
3 Methodology
3.1 Word Embedding Layer
3.2 RNN Layer
3.3 Position Aware Attention Mechanism
3.4 Graph Convolution Network
3.5 Sentiment Classification
3.6 Model Training
4 Experiments
4.1 Dataset
4.2 Parameter Setting
4.3 Word Embedding Models Comparison
4.4 RNN Models Comparison
4.5 Overall Performance
4.6 Ablation Study
5 Conclusion
References
BERT-Based Sentiment Analysis: A Software Engineering Perspective
1 Introduction
1.1 BERT
2 Related Work
3 Proposed Work
3.1 Data Augmentation
3.2 Fine-Tuning BERT Model
3.3 Ensemble BERT Models
3.4 Compressed Model
4 Experiments
4.1 Training and Testing
5 Results and Discussion
6 Conclusion
References
A Stochastic Block Model Based Approach to Detect Outliers in Networks
1 Introduction
2 Model Definition
3 Experiments
References
Medical-Based Text Classification Using FastText Features and CNN-LSTM Model
1 Introduction
2 Related Works
3 Materials and Methods
3.1 Dataset
3.2 Feature Extraction
3.3 Machine Learning Algorithms
3.4 CNN-LSTM
4 Experimentations and Results
4.1 Experimental Flow
4.2 Analysis and Discussion of the Results
5 Conclusion
References
Data Mining
Diversified Pattern Mining on Large Graphs
1 Introduction
2 Related Work
3 Graphs, Patterns and Pattern Mining
3.1 Graph Pattern Matching
3.2 Diversified Top-k Pattern Mining
4 Diversified Top-k Pattern Mining
5 Experimental Study
6 Conclusion
References
EHUCM: An Efficient Algorithm for Mining High Utility Co-location Patterns from Spatial Datasets with Feature-specific Utilities
1 Introduction
2 Problem Definition
3 The EHUCM Algorithm
3.1 The Search Space
3.2 Feature-Object Neighbor Tree (FONT)
3.3 Two Pruning Strategies
3.4 The EHUCM Algorithm
4 Experimental Evaluation
5 Conclusions
References
BERT-Based Multi-Task Learning for Aspect-Based Opinion Mining
1 Introduction
1.1 Problem Definition
1.2 Contributions
2 Literature Review
3 Proposed Approach
3.1 Multi-Task Learning Model
3.2 Aspect Term and Category Related Opinion Polarity
4 Steps of BERT-MTL
4.1 Steps of BERT-MTL for ATE and ACD Algorithm
4.2 Steps of BERT-MTL for Fine and Coarse-Grained Algorithm
5 Experimental Evaluation
5.1 Dataset
5.2 Hyper-Parameters
5.3 Result Analysis
6 Conclusions and Future Work
References
GPU-Accelerated Vertex Orbit Counting for 5-Vertex Subgraphs
1 Introduction
2 Preliminaries
2.1 Orbit Counting
2.2 EVOKE
3 Proposed Method
3.1 {3, 4}-Vertex Orbit Counting
3.2 5-Vertex Orbit Counting
4 Experiments
4.1 Experimental Setup
4.2 Execution Time Comparison
5 Related Work
6 Conclusion
References
Databases and Data Management
Efficient Discovery of Partial Periodic-Frequent Patterns in Temporal Databases
1 Introduction
1.1 Background and Related Work
1.2 Motivation
1.3 The Contributions of This Paper
2 Proposed Algorithm
3 Experimental Results
3.1 Experimental Setup
4 Conclusions and Future Work
References
Database Framework for Supporting Retention Policies
1 Introduction
2 Retention Definitions and Requirements
3 Related Work
4 Policy Setting
5 Policy Execution
6 Experiments
7 Conclusion and Future Work
References
Internal Data Imputation in Data Warehouse Dimensions
1 Introduction
2 Preliminaries
3 Internal Data Imputation for Dimensions
4 Experimental Assessments
4.1 Datasets and Experimental Method
4.2 Intra-dimensional Imputation Experiments
4.3 Inter-dimensional Imputation Experiments
5 Conclusion and Future Work
References
Purging Data from Backups by Encryption
1 Introduction
1.1 Motivation
2 Background
2.1 Compliance Terminology
2.2 Database Backups and Types
2.3 Related Work
3 Our Process
3.1 Defining Policies
3.2 Encryption Process
3.3 Encryption on Update
3.4 Purging Process
3.5 Restore Process
4 Experiments
5 Discussion
5.1 Implementation
5.2 ACID Guarantees
5.3 Future Work
6 Conclusion
References
Information Retrieval
Improving Quality of Ensemble Technique for Categorical Data Clustering Using Granule Computing
1 Introduction
2 Background and Notations
2.1 Information Granulation
2.2 Hybridization of Fuzzy Sets and Rough Sets
3 The Proposed Techniques
3.1 Information Granulation Selection Criteria
3.2 Fuzzy Rough Refinement Matrix
4 Experiments and Results
4.1 Evaluation of the Proposed Selection Criteria IGQS
4.2 Evaluation of the Proposed Refinement Techniques
4.3 Statistical Significance Tests
5 Conclusions and Future Work
References
Online Optimized Product Quantization for Dynamic Database Using SVD-Updating
1 Introduction
2 Preliminaries
2.1 Approximate k-Nearest Neighbor Search
2.2 Vector Quantization, Product Quantization, and Its Variants
2.3 Online Product Quantization for Dynamic Data
2.4 Other Methods Based on PQ
3 Proposed Method
3.1 Updating Codebook
3.2 Update Rotation Matrix Using SVD-Updating
3.3 Orthogonality
3.4 Computational Complexity
4 Experiments
4.1 Experimental Setting
4.2 Effects of Low-Rrank Approximation
4.3 Comparison with Non-online Methods
4.4 Comparison with Online Methods
5 Conclusion
References
Querying Collections of Tree-Structured Records in the Presence of Within-Record Referential Constraints
1 Introduction
2 Defining the Data Model
3 Within-Record Constraints
4 Querying Tree-Structured Data
4.1 Flattening Nested Data
4.2 Navigating Through References
References
Dealing with Plethoric Answers of SPARQL Queries
1 Introduction
2 Motivating Example
3 Related Work
4 Preliminaries and Problem Statement
4.1 Basic Notions
4.2 Notions of MFIS and XSS
5 Computing MFIS and XSS
5.1 Baseline
5.2 General Properties
5.3 Cardinality-Based Property
6 Experimental Evaluation
6.1 Results
7 Conclusion
References
Prediction and Decision Support
Feature Selection and Software Defect Prediction by Different Ensemble Classifiers
1 Introduction
2 Related Works
3 Methods and Results
3.1 The Dataset
3.2 Research Methods: Feature Selection
3.3 Research Methods: Classification
3.4 Research Methods: The Ensemble of Classifiers
4 Conclusions and Future Work
References
Traffic Flow Prediction Through the Fusion of Spatial-Temporal Data and Points of Interest
1 Introduction
2 Related Work
2.1 Convolution Neural Network-Based Traffic Prediction Method
2.2 Graph Neural Network-Based Traffic Prediction Method
3 Preliminaries
4 Method
4.1 Gated Fusion Network
4.2 Hierarchical Adaptive Graph Convolution
4.3 Gated Convolution Module
4.4 Multi-task Learning Loss
5 Experiments
5.1 Experimental Settings
5.2 Performance Results (RQ1)
5.3 Ablation Experiments (RQ2)
5.4 Evaluation on Framework Settings (RQ3)
5.5 Evaluation on Spatial-Temporal Fusion Methods (RQ4)
6 Conclusion and Future Work
References
Predicting Student Performance in Experiential Education
1 Introduction
2 Preliminaries, Key Concepts and Theories
3 Model and Methods
4 Experiments, Results and Discussion
References
Log-Based Anomaly Detection with Multi-Head Scaled Dot-Product Attention Mechanism
1 Introduction
2 Related Works
2.1 Log Parsing
2.2 Log-Based Anomaly Detection
3 LogAttention Design
3.1 Overview
3.2 Log Parsing
3.3 Log Pattern Vectorization
3.4 Log Anomaly Detection
4 Evaluation
4.1 Datasets and Criteria
4.2 Overall Results and Analysis
4.3 Experiments on Log Sequences with Different Window Lengths
4.4 Experiments on Log Pattern Vectorization Method
5 Conclusion
References
Enhancing Scan Matching Algorithms via Genetic Programming for Supporting Big Moving Objects Tracking and Analysis in Emerging Environments
1 Introduction
2 Background Concepts
3 Genetic Pre-alignment Phase
4 A Novel Family of Enhanced Hybrid Scan Matching Algorithms
5 Experimental Study
5.1 Genetic Pre-alignment: Performance Analysis
5.2 Proposed Hybrid Algorithms: Performance Analysis
6 Conclusions and Future Work
References
A Stacking Approach for Cross-Domain Argument Identification
1 Introduction
2 Related Work
2.1 Argument Mining
2.2 Ensemble Learning
3 Contribution
3.1 Problem Statement
3.2 Corpora Description
3.3 Classical Machine Learning Model - SVM
3.4 Transfer Learning Model (DistilBERT-Based)
3.5 Overall Model (SVM + DistilBERT)
4 Evaluation
5 Conclusion
References
Property Analysis of Stay Points for POI Recommendation
1 Introduction
2 Related Work
3 Method
3.1 Preliminaries
3.2 Weighted HITS-Based Algorithm
4 Experiments and Results
5 Conclusion
References
Beacon Technology for Retailers - Tracking Consumer Behavior Inside Brick-and-Mortar-Stores
1 Introduction
2 Theoretical Background
2.1 Challenges of Brick-and-Mortar Stores
2.2 Beacon Technology
2.3 Applications of Beacon Technology in Brick-and-Mortar Stores
2.4 Challenges of Beacon Technology in Brick-and-Mortar Stores
3 Recommendations for Implementation
3.1 Prerequisites for Adapting Beacon Technology
3.2 Recommendations for Establishing Beacon Technology
4 Conclusion
References
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Database and Expert Systems Applications

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