Databases Theory and Applications: 31st Australasian Database Conference, ADC 2020, Melbourne, Vic, Australia, February 3-7, 2020, Proceedings [1 ed.] 3030394689, 9783030394684

Table of contents :
Preface
General Chair’s Welcome Message
Organization
Contents
Full Research Papers
Semantic Round-Tripping in Conceptual Modelling Using Restricted Natural Language
1 Introduction
2 Motivation
3 Proposed Approach
3.1 Scenario
4 RNL Specification to DL ALCQI Representation
5 DL ALCQI Representation to SQL Script
6 Conceptual Model Generation
7 Database Schema to DL ALCQI Representation
8 DL ALCQI Representation to RNL verbalisation
9 Evaluation
10 Conclusion
References
PAIC: Parallelised Attentive Image Captioning
1 Introduction
2 Related Work
2.1 Image Captioning
2.2 Attention Model
3 Methodology
3.1 Problem Formulation
3.2 Preliminaries
3.3 The Attentive Encoder-Decoder
3.4 Visual Feature Encoder
3.5 Language Decoder
4 Experiments
4.1 Experimental Settings
4.2 Quantitative Analysis
4.3 Qualitative Analysis
4.4 Training Efficiency Analysis
4.5 Model Structure Comparison
5 Conclusion
References
Efficient kNN Search with Occupation in Large-Scale On-demand Ride-Hailing
1 Introduction
2 Related Work
2.1 kNN Queries
2.2 Shortest Path Queries
3 Preliminary
4 AkNN Query Algorithms
4.1 Dijkstra AkNN
4.2 Grid-Based AkNN
5 Experimental Study
5.1 Experiment Setup
5.2 Case Study
5.3 Different Indexes
5.4 AkNN Search Algorithms
6 Conclusion
References
Trace-Based Approach for Consistent Construction of Activity-Centric Process Models from Data-Centric Process Models
1 Introduction
2 Motivating Example
3 Preliminaries
4 Transformation Approach
4.1 Model Construction
4.2 Extract Model Traces
4.3 Trace-Based Analysis
5 Case Study
6 Related Work and Discussion
7 Conclusion
References
Approximate Fault Tolerance for Sensor Stream Processing
1 Introduction
2 Preliminaries
2.1 Data Streams
2.2 Estimation Based on a Multivariate Gaussian Distribution
2.3 Aggregation Queries
3 Problem Definition
3.1 Backup Cost
3.2 Confidence Score of Recovery
3.3 Problem Definition
4 Backup Selection for Approximate Fault Tolerance
4.1 Upper Bounds Derivation for Variance of Sensors
4.2 Greedy-Based Backup Selection
5 Experimental Evaluation
5.1 Experimental Settings
5.2 Experimental Results
6 Conclusion
References
Function Interpolation for Learned Index Structures
1 Introduction
2 Related Work
3 Background
3.1 Range Indexes as Cumulative Distribution Functions
3.2 Polynomial Interpolation
4 Indexes by Function Approximation
4.1 Interpolant Construction
4.2 Query Processing
5 Experimental Results
5.1 Model Creation Time
5.2 Memory Footprint
5.3 Query Accuracy and Time
5.4 Rate of Convergence of Polynomial Models
6 Conclusion
References
DEFINE: Friendship Detection Based on Node Enhancement
1 Introduction
2 Related Work
2.1 Network Representation Learning
2.2 Friendship Prediction
3 Problem Formulation
4 Design of DEFINE
5 Experiments
5.1 Datasets
5.2 Prediction
6 Conclusion
References
Semi-supervised Cross-Modal Hashing with Graph Convolutional Networks
1 Introduction
2 Related Work
3 Proposed Method
3.1 Preliminaries
3.2 Problem Formulation
3.3 Dual-Branch Graph Convolutional Network Hashing
3.4 Objective Function
3.5 Learning and Testing
4 Experiments
4.1 Datasets and Features
4.2 Experiment Settings
4.3 Implementation Details
4.4 Experiment Results and Analysis
5 Conclusion
References
Typical Snapshots Selection for Shortest Path Query in Dynamic Road Networks
1 Introduction
2 Related Work
2.1 Shortest Path Algorithm
2.2 Graph Similarity Measurement
3 Problem Definition
4 Time-Based Typical Snapshot Selection
4.1 Uniform Sampling
4.2 Non-uniform Sampling
5 Graph Representation-Based Selection
5.1 Edge-Based Representation
5.2 Vertex-Based Representation
5.3 Graph Clustering and Snapshot Matching
6 Experiments
6.1 Experimental Setup
6.2 Typical Snapshot Selection
6.3 Snapshot Matching
7 Conclusion
References
A Survey on Map-Matching Algorithms
1 Introduction
2 Preliminaries
2.1 Problem Definition
2.2 Related Work
3 Survey of Map-Matching Algorithm
3.1 Similarity Model
3.2 State-Transition Model
3.3 Candidate-Evolving Model
3.4 Scoring Model
4 Challenges and Evaluations
4.1 Experimental Settings
4.2 Data Quality Challenges
5 Conclusion
References
Gaussian Embedding of Large-Scale Attributed Graphs
1 Introduction
2 Related Work
3 GLACE Methodology
3.1 Notations and Problem Definition
3.2 Overall Architecture
3.3 Node Attribute Encoding
3.4 Graph Structure Encoding
3.5 Model Optimization
3.6 Complexity Analysis
4 Experiments
4.1 Datasets
4.2 Compared Algorithms and Setup
4.3 Link Prediction
4.4 Multi-class Node Classification
4.5 Inductive Learning
4.6 Scalability
4.7 Visualization
5 Conclusion
References
Geo-Social Temporal Top-k Queries in Location-Based Social Networks
1 Introduction
2 Related Work
3 Preliminaries
3.1 Problem Definition
3.2 Framework Overview
4 Proposed Techniques
4.1 Social-First Based Approach
4.2 Spatial-First Based Approach
4.3 Hybrid Approach
5 Experiments
5.1 Experimental Setup
5.2 Performance Evaluation
5.3 Conclusions
References
Effective and Efficient Community Search in Directed Graphs Across Heterogeneous Social Networks
1 Introduction
2 Related Work
2.1 Community Search
2.2 User Identity Linkage
3 Problem Definition
4 Our User Identity Linkage Approach
4.1 Retrieval of Valid User Sets
4.2 Comparisons of Users
4.3 Matching Users
4.4 Combination of Social Networks
5 Our Community Search Approach
5.1 Cores Decomposition
5.2 Index Construction
6 Cost Analysis
7 Experiment Evaluation
7.1 Experimental Setup
7.2 Evaluation Methodology
7.3 Effectiveness Evaluation
7.4 Efficiency Comparison
8 Conclusion
References
Entity Extraction with Knowledge from Web Scale Corpora
1 Introduction
2 Related Work
3 The 2ED Algorithm
3.1 Features of the 2ED Algorithm
3.2 Drawbacks of the 2ED Algorithm
4 Improvement on 2ED
4.1 Distinguishing a Typo from an Intended Token
4.2 Using Language Models
4.3 Estimating Word Similarity
4.4 Other Improvements
5 Implementation
5.1 Obtain Candidate Pairs
5.2 Rescore Candiadte Pairs
6 Experimental Studies
7 Conclusion and Future Work
References
Short Papers
Graph-Based Relation-Aware Representation Learning for Clothing Matching
1 Introduction
2 Related Work
2.1 Fashion Compatibility Learning
2.2 Graph Neural Networks
3 Proposed Approach
3.1 Problem Formulation
3.2 Part 1: Item Representation Generation
3.3 Part 2: Type-Aware Compatibility Prediction
3.4 Training Strategy
4 Experiments
4.1 Dataset
4.2 Baselines
4.3 Implementation Details
4.4 Task Description
4.5 Performance Comparison
5 Conclusion
References
Evaluating Random Walk-Based Network Embeddings for Web Service Applications
1 Introduction
2 Web Service Networks and Their Properties
2.1 Composition - Service Network
2.2 Popularity and Fitness-Based Service Evolving Networks
3 Analysis and Results
4 Conclusion and Future Work
References
Query-Oriented Temporal Active Intimate Community Search
1 Introduction
2 Related Work
3 Preliminary and Problem Definition
4 AIC Detection Algorithm
4.1 Baseline Solution
4.2 Improved Greedy Algorithm
5 Experiment and Result
5.1 Efficiency
5.2 Community Quality Evaluation
6 Conclusion
References
A Contextual Semantic-Based Approach for Domain-Centric Lexicon Expansion
1 Introduction
2 Proposed Approach
2.1 Candidate Words Extraction
2.2 Contextual Semantic-Based Graph Construction
2.3 Words Ranking and Lexicon Expansion
3 Experimental Setup and Results
3.1 Dataset and Embedding Learning
3.2 Evaluation Results
3.3 Comparative Analysis
4 Conclusion
References
Data-Driven Hierarchical Neural Network Modeling for High-Pressure Feedwater Heater Group
1 Introduction
2 Industrial Background
2.1 Thermal Power Plant Regenerative System
2.2 High-Pressure Feedwater Heater Group
3 Data-Driven Hierarchical Neural Network Modeling
3.1 Architecture of the Proposed Model
3.2 Model Training Process
4 Experiments
4.1 Experimental Data
4.2 Performance Evaluation Criteria
4.3 Experimental Setting and Results
5 Conclusion
References
Early Detection of Diabetic Eye Disease from Fundus Images with Deep Learning
1 Introduction
2 Literature Review
3 Research Challenges
4 Contribution to Knowledge
4.1 Analysis of Diabetic Eye Disease Using Deep Learning
4.2 Statement of Significance
5 Conclusions
References
Author Index

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