Databases Theory and Applications: 31st Australasian Database Conference, ADC 2020, Melbourne, Vic, Australia, February 3-7, 2020, Proceedings

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