Databases Theory and Applications: 32nd Australasian Database Conference, ADC 2021, Dunedin, New Zealand, January 29 – February 5, 2021, Proceedings ... Applications, incl. Internet/Web, and HCI)

This book constitutes the refereed proceedings of the 32nd Australasian Database Conference, ADC 2021, held in Dunedin, New Zealand, in January/February 2021. The 17 full papers presented were carefully reviewed and selected from 21 submissions. The Australasian Database Conference is an annual international forum for sharing the latest research advancements and novel applications of database systems, data-driven applications, and data analytics between researchers and practitioners from around the globe, particularly Australia and New Zealand. ADC shares novel research solutions to problems of todays information society that fullfil the needs of heterogeneous applications and environments and to identify new issues and directions for future research and development work. Preface General Chair’s Welcome Message Organization Contents Intention Recognition from Spatio-Temporal Representation of EEG Signals 1 Introduction 1.1 Motivation 1.2 Challenges 1.3 Solution 2 Related Work 3 Method 3.1 Data Acquisition 3.2 Image Mapping Layer 3.3 Architecture of the Neural Network 4 Experiments 4.1 Datasets 4.2 Benchmarking Methods 4.3 Results and Discussion 5 Conclusions References Adaptive Graph Learning for Semi-supervised Classification of GCNs 1 Introduction 2 Related Work 2.1 Hypergraph Theory 2.2 The GCN Model 3 Methodology 3.1 Our Proposed Method 4 Experiment 4.1 Datasets 4.2 Experimental Setting 4.3 Comparison Methods 4.4 Experimental Results 4.5 Convergence Analysis 5 Conclusions References Semi-supervised Feature Selection Based on Cost-Sensitive and Structural Information 1 Introduction 2 Approach 2.1 Notations 2.2 Cost-Sensitive Feature Selection 2.3 Feature Selection with Graph Structural Information 2.4 Mathematical Formulation 2.5 Optimization 2.6 Convergence Analysis 3 Experiments 3.1 Datasets and Comparison Methods 3.2 Experimental Settings 3.3 Experiment Results and Analysis 3.4 Conclusion References Contextual Bandit Learning for Activity-Aware Things-of-Interest Recommendation in an Assisted Living Environment 1 Introduction 2 Related Work 2.1 Recommender System for the IoT 2.2 Contextual Bandit Approach for Recommendation 3 Contextual-Bandit-Based Reminder Care System 3.1 Complex Activity Detection 3.2 Prompt Detection 3.3 Conducting Recommendations 4 Evaluation 4.1 Dataset 4.2 Features Engineering 4.3 Experiment Results 5 Conclusion References Deep Multi-view Spatio-Temporal Network for Urban Crime Prediction 1 Introduction 2 Problem Formulation 3 Data Collection and Feature Extraction 4 Methodology 4.1 Information Gathering 5 Experiments 5.1 Comparison Methods 5.2 Hyper-parameters Tuning 5.3 Ablation Study 6 Conclusion and Future Work References Experimental Analysis of Locality Sensitive Hashing Techniques for High-Dimensional Approximate Nearest Neighbor Searches 1 Introduction 1.1 Locality Sensitive Hashing 1.2 Motivation for Using LSH 1.3 Motivation of Our Experimental Survey 1.4 Contributions of This Experimental Survey Paper 2 Related Work 3 State-of-the-Art Techniques 4 Experimental Analysis 4.1 Datasets 4.2 Evaluation Criteria and Parameters 4.3 Discussion of the Performance Results 5 Conclusion References ANSWER: Generating Information Dissemination Network on Campus 1 Introduction 2 Related Work 2.1 Network Representation Learning (NRL) 2.2 Social Relationship 2.3 Information Dissemination Network 3 Problem Formulation 4 Design of ANSWER 4.1 Construction of Friendship Network 4.2 Processing of Node Attributes 4.3 Attributed Network Representation Learning (ANRL) 4.4 Link Prediction 5 Experiments 5.1 Dataset 5.2 Prediction 6 Conclusion References Twitter Data Modelling and Provenance Support for Key-Value Pair Databases 1 Introduction 2 Related Work 3 Proposed Provenance Framework 3.1 Data Model Design 3.2 Zero-Information Loss Key-Value Pair Database 3.3 Provenance Generation Algorithms 3.4 Querying Provenance 4 Results and Discussions 5 Conclusion and Future Work References Analyzing Tweets to Understand Factors Affecting Opinion on Climate Change 1 Introduction 2 Literature Review 3 Experimental Methods 3.1 Data Collection 3.2 Data Preprocessing 3.3 Classification Models 3.4 Topic Modeling 4 Result and Discussion 4.1 Opinion Shapers: Ideologies 4.2 Opinion Shapers: Leadership 4.3 Opinion Shapers: Media 5 Conclusion References Optimal Placement of Taxis in a City Using Dominating Set Problem 1 Introduction 2 Literature Review 3 Context of the Problem 3.1 Preliminaries 4 Methodology 4.1 Neighbour Search 4.2 k-hop Dominating Set Algorithm 4.3 Modified k-hop Dominating Set Algorithm 4.4 Task Assignments 5 Experiment Setup 5.1 Size of the Dominating Set Varying k-Value 5.2 Varying the Number of Drivers 5.3 Varying the K-Value 5.4 Comparison with Other Clustering Algorithms 6 Conclusion and Future Work References Adaptive Fault Diagnosis for Data Replication Systems 1 Introduction 2 Literature Review and Background 3 Adaptive Fault Diagnosis (FD) Module Design 3.1 Information Acquisition (IA) Module 3.2 Diagnostic Reinforcement Learning (DRL) for FD Module 3.3 System Diagnostic (SD) Module 4 Data Replication Environment (DRE)’s State Representation 5 DRE’s Action of Diagnostic Prediction 6 Empirical Analysis 6.1 The Experimental Set-Up 6.2 True Negative Test Results 6.3 Evaluation Criteria and Benchmarking 6.4 Test Results 6.5 Service Outage Classification Results 6.6 Service Outage’s Prediction Accuracy 7 Conclusion References Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning 1 Introduction 2 Related Work 3 Methodology 3.1 Problem Definition 3.2 Dual Generative Model 3.3 Triplet Regularization 3.4 Predicting with Uncertainty Calibration 4 Experiments 4.1 Datasets and Compared Methods 4.2 Evaluation Protocol 4.3 GZSL Results 4.4 Conventional ZSL Results 4.5 Ablation Study 4.6 Latent Space Distribution Analysis 5 Conclusion References A Real Time Analysis of Offensive Texts to Prevent Cyberbullying 1 Introduction 1.1 State-of-the-Art in Detecting Offensive Text 1.2 Our Novel Approach and Contributions 2 Related Work 3 Proposed Architecture 4 Application Development and Implementation Aspects 4.1 Data Preprocessing 4.2 Input Transformation 4.3 Embedding Enrichment 4.4 Recurrent Neural Network 4.5 Alternative Word Suggestion 5 Real-Time Offensive Text Detection 6 Performance Evaluation and Results 6.1 Dataset Used 6.2 Experimental Setup and Results 7 Conclusion References An Experimental Study on Exact Multi-constraint Shortest Path Finding 1 Introduction 2 Related Work 2.1 Skyline Path 2.2 Single-CSP 2.3 Multi-CSP 3 Preliminary 3.1 Problem Definition 3.2 Skyline Path 4 Multi-CSP Algorithms 4.1 Skyline-Dijkstra's Multi-CSP 4.2 Search-Based kPath Multi-CSP 4.3 Enhanced kPath Multi-CSP 5 Experiments 5.1 Experimental Settings 5.2 Query Distance 5.3 Constraint Ratio 5.4 Number of Constraints 5.5 Influence of Stricter Constraints 5.6 Constraint Correlation 6 Conclusion References The Effect of Regional Economic Clusters on Housing Price 1 Introduction 2 Conceptual Framework 2.1 Feature Vector 1: Housing Attributes 2.2 Feature Vectors 2 and 3: The Housing Location 2.3 Feature Vector 4: Socio-demographic Attributes 3 Experimental Settings 3.1 Data Description 3.2 Algorithms 4 Results and Analysis 4.1 Overall Performance 4.2 The Importance of the Regional Cluster Variable 5 Discussions and Implications 5.1 Implications for Home Buyers 5.2 Implications for Councils and Urban Planning 5.3 Implications for Real-Estate Investors and Developers 6 Related Work 7 Conclusions and Future Work References Modeling Daily Crime Events Prediction Using Seq2Seq Architecture 1 Introduction 2 Related Work 3 Methodology 3.1 Data Collection 3.2 Data Pre-processing 3.3 Proposed Seq2seq Model 4 Results and Discussions 4.1 ARIMA, Simple RNN, LSTM and Conv1D 4.2 Prediction Performance Comparison Using Different Timesteps 4.3 Prediction Performance Comparison with Baselines 5 Conclusion References Modelling and Factorizing Large-Scale Knowledge Graph (DBPedia) for Fine-Grained Entity Type Inference 1 Introduction 2 DBpedia Knowledge Graph 2.1 Modeling DBpedia 2.2 Factorizing DBpedia 3 Experiments 3.1 Evaluation and Apply on DBpedia and Freebase 4 Related Work 5 Conclusion References Author Index