Advances in Knowledge Discovery and Data Mining

Name: Advances in Knowledge Discovery and Data Mining | 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7-10, 2024, Proceedings, Part V
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28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7-10, 2024, Proceedings, Part V

De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei Lin(Editor)

Springer (Publisher)

Published on 24. April 2024

XXXIV, 404 pages

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978-981-97-2262-4 (ISBN)

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Content

Intro
General Chairs' Preface
PC Chairs' Preface
Organization
Contents - Part V
Multimedia and Multimodal Data
Re-thinking Human Activity Recognition with Hierarchy-Aware Label Relationship Modeling
1 Introduction
2 Related Work
2.1 Human Activity Recognition (HAR)
2.2 Hierarchical Label Modeling
3 Problem Formulation
4 Our Proposals
4.1 Hierarchy-Aware Label Encoding
4.2 Activity Data Encoding
4.3 Label-Data Joint Embedding Learning
5 Experiments
5.1 Experimental Settings
5.2 Experimental Results
5.3 Ablation Study
6 Discussions and Conclusion
References
Geometrically-Aware Dual Transformer Encoding Visual and Textual Features for Image Captioning
1 Introduction
2 Related Works
3 Proposed Approach
3.1 Features Extractor
3.2 Caption Generator
3.3 Attention Block
3.4 Training and Objectives
4 Experiments
4.1 Experiments Setup
4.2 Experiment Result
5 Conclusions
References
MHDF: Multi-source Heterogeneous Data Progressive Fusion for Fake News Detection
1 Introduction
2 Related Work
3 MHDF Model
3.1 Model Overview
3.2 Multi-source Heterogeneous Data Amplification
3.3 News Textual Feature Fusion
3.4 News Visual Feature Fusion
3.5 Sentiment Feature Extractor
3.6 Feature Integration Classifier
4 Experiments
4.1 Dataset
4.2 Experimental Settings
4.3 Performance Comparison
4.4 Ablation Experiments and Validity Verification
4.5 Conclusions
References
Accurate Semi-supervised Automatic Speech Recognition via Multi-hypotheses-Based Curriculum Learning
1 Introduction
2 Related Works
2.1 Automatic Speech Recognition Methods
2.2 Connectionist Temporal Classification (CTC) Loss
3 Proposed Method
3.1 Multiple Hypotheses for Unlabeled Instances
3.2 Training ASR Model with Multiple Hypotheses
3.3 Curriculum Learning
3.4 Theoretical Analysis
4 Experiments
4.1 Experimental Settings
4.2 Transcription Performance (Q1)
4.3 Speed of Convergence (Q2)
4.4 Ablation Study (Q3)
5 Conclusions
References
MM-PhyQA: Multimodal Physics Question-Answering with Multi-image CoT Prompting
1 Introduction
2 Related Works
2.1 Available Datasets
2.2 Large Multimodal Models and Chain-of-Thought
3 Novel Dataset
3.1 Original Dataset Creation
3.2 Data Augmentation Procedure
3.3 Chain of Thought Variant
3.4 MM-PhyQA Dataset Topics
4 Methodology
4.1 Multi-image Chain-of-Thought (MI-CoT)
5 Experiments
5.1 Models
6 Results and Discussion
6.1 Model Performance
6.2 Zero Shot Prompting Vs Supervised Fine-Tuning
6.3 Effect of Chain of Thought Prompting
6.4 Error Analysis
7 Conclusion
References
Adversarial Text Purification: A Large Language Model Approach for Defense
1 Introduction
2 Related Work
3 Background
3.1 Large Language Models
3.2 Adversarial Text Purification
4 LLM-Guided Adversarial Text Purification
5 Experiments
5.1 Experimental Setting
5.2 Results and Discussion
6 Conclusion
References
lil'HDoC: An Algorithm for Good Arm Identification Under Small Threshold Gap
1 Introduction
2 Background
2.1 Good Arm Identification
3 Problem Setting
4 Preliminary
5 Algorithm
5.1 Correctness of lil'HDoC
5.2 First Arms Sampling Complexity
5.3 Total Sample Complexity
6 Experiment
6.1 Dataset
6.2 Baseline
6.3 Results
7 Conclusion
References
Recommender Systems
ScaleViz: Scaling Visualization Recommendation Models on Large Data
1 Introduction
2 Related Works
3 Problem Formulation
4 Proposed Solution
4.1 Cost Profiling
4.2 RL Agent
5 Evaluations
5.1 Experimental Setup
5.2 Speed-Up in Visualization Generation
5.3 Budget vs. Error Trade-Off
5.4 Need for Dataset-Specific Feature Selection
5.5 Scalability with Increasing Data Size
6 Conclusion
References
Collaborative Filtering in Latent Space: A Bayesian Approach for Cold-Start Music Recommendation
1 Introduction
2 Related Work and Problem Formulation
2.1 Problem Formulation
3 Methodology
3.1 Overview
3.2 Statistical Model in CFLS
3.3 Optimization
3.4 Prediction
4 Experiments
4.1 Dataset
4.2 Experimental Settings
4.3 Performance Comparisons
4.4 Influence of Different Cold-Start Levels
4.5 Diversity, Interpretability and User Controllability
5 Conclusions
References
On Diverse and Precise Recommendations for Small and Medium-Sized Enterprises
1 Introduction
2 Related Work
3 Definitions and Problem Statement
4 Variants of a Session-Based Recommender System
4.1 Quality Metrics
5 Experiments and Evaluation
5.1 Selection of Real-World Datasets
5.2 Task Definition and Parameter Configuration
5.3 Evaluation of Experimental Results
6 Conclusion and Future Work
References
HMAR: Hierarchical Masked Attention for Multi-behaviour Recommendation
1 Introduction
2 Methodology
2.1 Problem Formulation
2.2 HMAR
2.3 Multi-task Learning
3 Experiments
3.1 Experimental Settings
3.2 Evaluation Protocol
3.3 Model Performance (RQ1)
3.4 Effect of Auxiliary Behaviors and Individual Model Components (RQ2 & RQ3)
4 Related Work
5 Conclusion
References
Residual Spatio-Temporal Collaborative Networks for Next POI Recommendation
1 Introduction
2 Related Works
3 Method
3.1 Problem Formulation
3.2 Long-Term Dependence Module
3.3 Short-Term Dependence Module
3.4 Sample Balancer
4 Experiments
4.1 Experimental Settings
4.2 Recommendation Performance
4.3 Ablation Study
5 Conclusions
References
Conditional Denoising Diffusion for Sequential Recommendation
1 Introduction
2 Related Work
3 Methodology
3.1 Stepwise Diffuser
3.2 Sequence Encoder
3.3 Cross-Attentive Conditional Denoising Decoder
3.4 Optimization
4 Experiments
4.1 Plateau of Ranking Prediction
4.2 Overall Experiments
4.3 Ablation Study
4.4 Hyperparameter Sensitivity
4.5 Case Study for Stepwise Generation
5 Conclusion
References
UIPC-MF: User-Item Prototype Connection Matrix Factorization for Explainable Collaborative Filtering
1 Introduction
2 Related Work
2.1 Collaborative Filtering
2.2 Explainable and Transparent Recommender Models
2.3 The Prototype-Based Collaborative Filtering
3 Methodology
3.1 User-Item Prototypes Connections Matrix Factorization (UIPC-MF)
3.2 Loss Function
4 Experiments and Discussion
4.1 Evaluation Metrics
4.2 Baseline Models
4.3 Training Details
4.4 Evaluation Results
4.5 Explaining UIPC-MF Recommendations
4.6 The Impact of L1-Norm in Reduction of Learning Bias
5 Conclusion
References
Towards Multi-subsession Conversational Recommendation
1 Introduction
2 Related Works
3 MSMCR Scenario
3.1 Definition
3.2 General Framework
4 Methodology
4.1 Context-Aware Recommendation
4.2 Policy Learning
4.3 Model Training
5 Experiments
5.1 Experimental Setup
5.2 Overall Performance
5.3 Further Experiments
6 Conclusion
References
False Negative Sample Aware Negative Sampling for Recommendation
1 Introduction
2 Related Work
3 Preliminary
4 Methodology
4.1 False Negatives Identification
4.2 False Negatives Elimination
5 Experiment
5.1 Experiment Settings
5.2 Performance Comparison
5.3 Study of EDNS
6 Conclusion
References
Multi-sourced Integrated Ranking with Exposure Fairness
1 Introduction
2 Problem Formulation
3 Proposed Model
3.1 Input Layer
3.2 Dual RNN Module
3.3 Multi-task Module
3.4 Model Training
4 Experiments
4.1 Experimental Settings
4.2 Baselines
4.3 Model Selection
4.4 Performance Comparison
4.5 Ablation Study
4.6 Online A/B Testing
5 Conclusion
References
Soft Contrastive Learning for Implicit Feedback Recommendations
1 Introduction
2 Related Work
3 Methodology
3.1 Notations
3.2 The SCLRec Framework
4 Experiments
4.1 Experimental Settings
4.2 Overall Performance (RQ1)
4.3 Ablation Study (RQ2)
4.4 Robustness to Interaction Noises (RQ3)
5 Conclusion
References
Dual-Graph Convolutional Network and Dual-View Fusion for Group Recommendation
1 Introduction
2 Problem Formulation
3 Approach
3.1 Dual-Graph Construction
3.2 Dual-Graph Network for Member Preference
3.3 Dual-View Fusion for Group Preference
3.4 Group Recommendation and Model Training
4 Experiments
4.1 Experimental Dataset and Setup
4.2 Experimental Results and Analysis
4.3 Parameter Sensitivity
5 Related Works
6 Conclusion and Future Work
References
TripleS: A Subsidy-Supported Storage for Electricity with Self-financing Management System
1 Introduction
2 Literature Review
2.1 Electricity Subsidy and Operating Reserve
2.2 Electricity Management System
2.3 Electricity Storage
3 Problem Definition and Simulation Environment
4 Proposed TripleS
5 Experimental Results
5.1 Performance Evaluation
5.2 Performance Evaluation Under MS Attack
5.3 Influence of Self-discharge
6 Conclusion
References
Spatio-temporal Data
Mask Adaptive Spatial-Temporal Recurrent Neural Network for Traffic Forecasting
1 Introduction
2 Related Work
3 Model Architecture
3.1 Problem Definition
3.2 Mask-Adaptive Matrix
3.3 Spatial Temporal Identity Embedding
3.4 Multi-head Attention Layer
3.5 Framework of MASTRNN
4 Experiments
4.1 Experimental Settings
4.2 Experimental Result
4.3 Ablation Study
5 Conclusion
References
Distributional Kernel: An Effective and Efficient Means for Trajectory Retrieval
1 Introduction
2 Related Work
2.1 Distance Measures for Trajectories
2.2 Similar Subtrajectory Search
3 Distributional Kernel for Trajectory Similarity Measure
4 Identity Property
5 Similar Subtrajectory Search
6 Empirical Evaluation
6.1 Experimental Design and Settings
6.2 Experimental Results
7 Discussion
7.1 How Important Is the Temporal Information?
7.2 Runtime Efficiency and Indexed Search
8 Conclusion
References
Multi-agent Reinforcement Learning for Online Placement of Mobile EV Charging Stations
1 Introduction
2 Preliminaries
2.1 Related Works
2.2 Problem Definition
2.3 Problem Complexity and NP-Hardness
3 Methodology
3.1 Static Placement: Shortest Traveling Heuristic Algorithm
3.2 Dynamic Management: Two-Phase Management Algorithm
4 Experimental Results
4.1 Dataset and Preprocessing
4.2 Baselines and Experiment Settings
4.3 Performance Comparison
5 Conclusions
References
Localization Through Deep Learning in New and Low Sampling Rate Environments
1 Introduction
2 Problem Definition
3 Related Works
3.1 Coordinate Based Localization
3.2 Heatmap Based Localization
4 Method
5 Experimental Design and Results
5.1 Dataset
5.2 Comparing with SOTAs
5.3 Ablation Study
5.4 Visual Analysis
6 Conclusion and Future Work
References
MPRG: A Method for Parallel Road Generation Based on Trajectories of Multiple Types of Vehicles
1 Introduction
2 Related Work
3 Method
3.1 Framework
3.2 Feature Extraction
3.3 Parallel Road Generation Model
4 Evaluation
4.1 Data Set and Ground Truth
4.2 Metrics
4.3 Baselines
4.4 Evaluation Results
5 Conclusion
References
GSPM: An Early Detection Approach to Sudden Abnormal Large Outflow in a Metro System
1 Introduction
2 Related Work
2.1 Traffic Flow Prediction
2.2 Abnormal Traffic Flow Early-Warning
3 Model Overview
3.1 Definitions and Problem Formulation
3.2 Data-Driven Insights
3.3 Framework
4 SALODetector
4.1 SALO Discrimination
4.2 SALO Localization
4.3 Experiment Setting
4.4 Parameter Effect
4.5 Case Study
4.6 Comparison with Baseline Methods
5 Conclusion
References
FMSYS: Fine-Grained Passenger Flow Monitoring in a Large-Scale Metro System Based on AFC Smart Card Data
1 Introduction
2 Problem and Solution Overview
2.1 Preliminaries
2.2 Motivation
2.3 FMSYSOverview
3 Passenger State Transition Estimation
3.1 Individual Travel Pattern Analysis
3.2 State Transition Estimation for ND-Group
4 Online Analysis
5 Experimental Analysis
5.1 Experimental Setting
5.2 Experiment Result
6 Related Work
7 Conclusion
References
Enhanced HMM Map Matching Model Based on Multiple Type Trajectories
1 Introduction
2 Related Work
3 Preliminary
3.1 Some Definitions
3.2 HMM Map Matching
4 Algorithm
4.1 Overview
4.2 Offline Analysis
4.3 Online HMM Map Matching
5 Experiments
5.1 Experiment Results
6 Conclusion
References
A Multimodal and Multitask Approach for Adaptive Geospatial Region Embeddings
1 Introduction
2 Definitions and Problem Formulation
3 The MAGRE Approach
3.1 Grid Construction and Feature Extraction
3.2 MAGRE Model Architecture
3.3 Embedding Aggregation for Spatial Regions
4 Experimental Setup
5 Evaluation Results
6 Case Study: Crime Rate Prediction on ROIs
7 Related Work
8 Conclusion
References
Attention Mechanism Based Multi-task Learning Framework for Transportation Time Prediction
1 Introduction
2 Related Work
3 Preliminaries
4 Solution
4.1 Travel Pattern Learning
4.2 Stay Pattern Learning
4.3 Transportation Time Modeling
5 Experiments
5.1 Datasets and Settings
5.2 Metrics
5.3 Comparison Approaches
5.4 Overall Evaluation
5.5 Ablation
5.6 Parameter Experiments
5.7 Case Study
6 Conclusion
References
MSTAN: A Multi-view Spatio-Temporal Aggregation Network Learning Irregular Interval User Activities for Fraud Detection
1 Introduction
2 Problem Statement
3 Overall Architecture
3.1 Architecture
3.2 Short-Term Aggregation
3.3 View Aggregation
3.4 Long-Term Aggregation
3.5 Fraud Detection
4 Experiment
4.1 Experimental Setup
4.2 Experimental Results
5 Conclusion
References
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Advances in Knowledge Discovery and Data Mining

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