دانلود کتاب Collaborative Computing: Networking, Applications and Worksharing: 17th EAI International Conference, CollaborateCom 2021, Virtual Event, October 16-18, 2021, Proceedings, Part I

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Preface Organization Contents – Part I Contents – Part II Optimization for Collaborate System (Workshop Papers) Chinese Named Entity Recognition Based on Dynamically Adjusting Feature Weights 1 Introduction 2 Model Approach 2.1 BERT 2.2 CNN 2.3 BILSTM 2.4 CRF 3 BERT+EL-LGWF+CRF 3.1 Weighted Fusion According to CNN and BILSTM 3.2 EL 3.3 Loss Function 4 Experiment and Analysis 4.1 Dataset 4.2 Evaluation Indices 4.3 Experimental Results and Analysis 5 Summary References Location Differential Privacy Protection in Task Allocation for Mobile Crowdsensing Over Road Networks Abstract 1 Introduction 2 Preliminary 2.1 Privacy Model 2.2 Adversary Model 3 PPTA Framework 3.1 Location Obfuscation 3.2 Task Allocation Based on Obfuscated Locations 3.3 Speed-Up with δ-Spanner Graph 4 Evaluation 4.1 Experiment Configurations 4.2 Experimental Results 5 Related Work 6 Conclusion Acknowledgments References “Failure” Service Pattern Mining for Exploratory Service Composition Abstract 1 Introduction 2 Related Work 2.1 Log-Based Service Pattern Mining 2.2 Process-Based Service Pattern Mining 3 Model Definition 3.1 Exploratory Service Composition Instance Model 3.2 Service Pattern Model 4 FSPMA 5 Prototype Implementation 6 Experiment 6.1 Dataset and Environment 6.2 Experimental Verification 7 Application 7.1 Service Recommendation Using “Failure” Service Patterns 7.2 An Example 8 Conclusion Acknowledgements References Optimal Control and Reinforcement Learning for Robot: A Survey 1 Introduction 2 Optimal Control Problem Statement 3 Solutions of Optimal Control for Robot 3.1 Overview the Related Approaches 3.2 Improve Precision and System Complexity 3.3 Overcome Model Bias 3.4 Reduce Computation 4 Future Prospects and Discussion 5 Summary and Conclusions References KTOBS: An Approach of Bayesian Network Learning Based on K-tree Optimizing Ordering-Based Search Abstract 1 Introduction 2 Bayesian Network and k-tree 2.1 Bayesian Network 2.2 Tree Width and k-tree 3 BN Learning Based on K-tree Optimizing Ordering-Based Search 3.1 Obtaining Candidate Parent Set 3.2 Initial Network Construction 3.3 Optimizing Network Using Ordering-Based Search 4 Experiment 4.1 Dataset and Evaluation Method 4.2 Experiment Results and Analysis 5 Conclusions Acknowledgement References Recommendation Model Based on Social Homogeneity Factor and Social Influence Factor Abstract 1 Introduction 2 Related Work 3 Preliminary and Problem Definition 3.1 Novel Graph Attention Network 3.2 Notations 3.3 Problem Definition 4 The Proposed Model 4.1 Model Details 4.1.1 Original Input and Similar Item Network 4.1.2 Embedding Layer 4.1.3 NGAT Layer 4.1.4 Pairwise Neural Interaction Layer 4.1.5 Policy-Based Fusion Layer 4.1.6 Output Layer and Loss Function 4.2 Model Training 4.2.1 Mini-Batch Training 4.2.2 Alleviate Overfitting 5 Experiments 5.1 Dataset Introduction 5.2 Experimental Setup 5.2.1 Experimental Environment Setting 5.2.2 Evaluation Metrics 5.2.3 Compare Models 5.3 Comparative Experiments: RQ1 5.4 Ablation Experiments: RQ2 5.5 Parameter Sensitivity Experiments: RQ3 6 Conclusion References Attention Based Spatial-Temporal Graph Convolutional Networks for RSU Communication Load Forecasting 1 Introduction 2 Related Works 3 System Model 4 Communication Load Evaluation 5 The Communication Load Prediction Model 5.1 Temporal Attention 5.2 Spatial Attention 5.3 Graph Convolution in Spatial Dimension 5.4 Convolution in Temporal Dimension 5.5 Fully Connected Layer 6 Simulation and Analysis 6.1 Dataset 6.2 Model Parameters 6.3 Comparison and Result Analysis 7 Conclusion References UVA and Traffic System Mobile Encrypted Traffic Classification Based on Message Type Inference 1 Introduction 2 Related Work 2.1 Traditional Unencrypted Traffic Classification 2.2 Sequence Feature-Based Encrypted Traffic Classification 2.3 Attribute Feature-Based Encrypted Traffic Classification 3 System Introduction 3.1 System Overview 3.2 Data Preprocessing 3.3 Message Type Inference 3.4 Machine Learning 4 Evaluation 4.1 Preliminary 4.2 Analysis of the Message Type Inference 4.3 Analysis of Adopted Features 4.4 Comparisons with Existing Approaches 5 Discussion and Conclusion References Fine-Grained Spatial-Temporal Representation Learning with Missing Data Completion for Traffic Flow Prediction 1 Introduction 2 Related Work 3 Methodology 3.1 Feature Extractors 3.2 Data Completer 4 Experiments and Analysis 4.1 Experimental Settings 4.2 Performance of Traffic Flow Prediction 4.3 Effect of Data Completer 5 Conclusion and Future Work References Underwater Information Sensing Method Based on Improved Dual-Coupled Duffing Oscillator Under Lévy Noise Description Abstract 1 Introduction 2 Related Work 2.1 Lévy Noise Model 2.2 Chaotic Oscillator Signal Sensing System 3 Approach 3.1 Lévy Noise Model Describes Underwater Natural Environment Interference 3.2 Improved Signal Sensing Method of Dual Coupling Duffing Oscillator 4 Experiment and Analysis 4.1 Experiment Deployment 4.2 Performance 5 Conclusion Acknowledgement References Unpaired Learning of Roadway-Level Traffic Paths from Trajectories 1 Introduction 2 Related Work 3 Preliminary Concepts 4 Overview 4.1 Definition 4.2 Problem Analysis and Approach Overview 5 Trajectory Data Transition 5.1 Feature Extraction 5.2 Orientation Converted to Color Information 6 Training Model 7 Experiment and Analysis 7.1 Dataset and Experimental Environment 7.2 Parameter Setting and Data Division 7.3 Results and Performance Comparison 8 Conclusion References Multi-UAV Cooperative Exploring for the Unknown Indoor Environment Based on Dynamic Target Tracking 1 Introduction 2 Related Work and Scenario Description 2.1 Related Work 2.2 Scenario Description 3 Method 3.1 Wall-Around Algorithm 3.2 Tracking-D*Lite 4 Experiments 4.1 Tracking-D*Lite Algorithm Experiment 4.2 Simulation Experiment 5 Conclusion References Recommendation System MR-FI: Mobile Application Recommendation Based on Feature Importance and Bilinear Feature Interaction Abstract 1 Introduction 2 Related Work 3 Proposed Method 3.1 Embedding Layer 3.2 SENET Layer 3.3 Bilinear-Interaction Layer 3.4 Connectivity Layer 3.5 Deep Network 3.6 Prediction Layer 4 Experimental Result and Analysis 4.1 Data Set and Experiment Setup 4.2 Evaluation Metrics 4.3 Baseline Methods 4.4 Experimental Performance 4.5 Hyperparameters Analysis 5 Conclusion and Future Work Acknowledgement References Dual-Channel Graph Contextual Self-Attention Network for Session-Based Recommendation Abstract 1 Introduction 2 Related Work 2.1 Neural Network Model 2.2 Attention Mechanism 3 Proposed Method 3.1 Problem Statement 3.2 Model Overview 3.3 Session Graph Construction 3.4 Item Embedding Learning 3.5 Self-attention Network 3.6 Prediction Layer 4 Experiments and Analyses 4.1 Datasets 4.2 Evaluation Metric 4.3 Experiment Settings 4.4 Comparison with Baseline Methods 4.5 The Influence of Model Parameters on Experimental Results 5 Conclusions References Context-aware Graph Collaborative Recommendation Without Feature Entanglement 1 Introduction 2 Problem Formulation 3 Methodology 3.1 General Framework 3.2 Optimization 3.3 Time Complexity Analysis of CGCR 4 Experiments 4.1 Dataset Description 4.2 Experimental Settings 4.3 RQ1: Does the Proposed Method Perform Better Than Other Comparison Methods? 4.4 RQ2: Does the Proposed Method Elucidate the Meanings of Each Dimension of the Embedding? 4.5 RQ3: How Does Number of Graph Convolution Layer Impact? 4.6 RQ4: How Does Non-sampling Strategy Impact? 5 Related Work 5.1 Collaborative Filtering 5.2 Non-sampling Learning for Top-K Recommendation 6 Conclusion and Future Work References Improving Recommender System via Personalized Reconstruction of Reviews 1 Introduction 2 Related Work 2.1 Review-based Recommendation with Topic Modeling 2.2 Document-Level Recommendation 2.3 Review-Level Recommendation 3 Methodology 3.1 Probem Definition 3.2 Overall Framework of PPRR 3.3 Review Document Reconstruction Network (Re-Doc-Net) 3.4 Document-Level Encode Network(Doc-Net) 3.5 Review-Level Encode Network(Review-Net) 3.6 Rating Score Prediction Layer 4 Experiments and Analysis 4.1 DataSets and Experiments Settings 4.2 Performance Evaluation 4.3 Discussion 4.4 Hyper-Parameters Analyses 5 Conclusion References Recommendation System and Network and Security Dynamic Traffic Network Based Multi-Modal Travel Mode Fusion Recommendation Abstract 1 Introduction 2 Concepts Used in the Paper 2.1 Definition of the Fusion Recommendation Problem 2.2 Heterogeneous Transport Travel Networks 2.3 Meta-paths Extraction Based on User Trajectory 2.4 Meta-path Guided Neighbors 3 Heterogeneous Transport Travel Network Recommendation Model 3.1 Initial Embedding 3.2 Practice of Meta-path 3.3 Meta-path Aggregation Functions 3.4 Semantic Aggregation 3.5 Evaluation Prediction 4 Experiments and Analysis 4.1 Dataset 4.2 Experimental Setup 4.3 Result Analysis 4.4 Result Analysis 4.5 Effect of Aggregation Functions on Recommended Performance 4.6 Performance of the Model on Specific Datasets 5 Conclusion Acknowledgment References Improving Personalized Project Recommendation on GitHub Based on Deep Matrix Factorization 1 Introduction 2 Related Work 2.1 GitHub Project Recommendations 2.2 Deep Learning in Recommendation Systems 3 Proposed Methods 3.1 Data Collection 3.2 Recommender System 3.3 Result and Evaluation 4 Experimental Setup 4.1 Datasets 4.2 Evaluation and Metrics 4.3 Statistic Test 5 Experimental Results 5.1 RQ1:Does the Proposed Method Perform Better Than Other Comparison Methods? 5.2 RQ2:What Is the Effect of the Dimension of the Low-Dimensional Vector and the Number of Recommended Lists on the Performance of the Proposed Method? 6 Threats to Validity 6.1 Internal Validity 6.2 External Validity 7 Conclusions References An Intelligent SDN DDoS Detection Framework 1 Introduction 2 Related Works 3 Security-oriented Flow Monitoring and Sampling 3.1 Performance Analysis of Security-Oriented Flow Table Sampling 3.2 Flow Monitoring and Sampling with Low-Latency Based on Optimization Theory 4 Service Flow-Oriented Attack Recognition Model 4.1 Service Flow Features Required by the Model 4.2 DDoS Attack Detection Model Based on Clustering and VAE 4.3 DDoS Attack Defense Based on Recognition Result 5 Simulation and Performance Evaluation 5.1 Simulation Setup 5.2 Network Traffic Sampling Efficiency Evaluation 5.3 Attack Detection Model Evaluation 6 Conclusion References Inspector: A Semantics-Driven Approach to Automatic Protocol Reverse Engineering 1 Introduction 2 Related Work 3 System Design 3.1 Overview 3.2 Length Field Inference 3.3 Message Type Field Inference 3.4 Protocol Format Inference 4 Evaluation 4.1 Datasets 4.2 Evaluation Metrics 4.3 Tunable Parameters 4.4 Experimental Results 5 Conclusions References MFF-AMD: Multivariate Feature Fusion for Android Malware Detection 1 Introduction 2 Related Work 3 Multivariate Feature Extraction 3.1 Static Feature Extraction 3.2 Dynamic Feature Extraction 3.3 Application Coverage 3.4 Feature Selection 4 Implementation 4.1 Architecture 4.2 Weight Distribution Algorithm 5 Evaluation 5.1 Dataset and Setup 5.2 Results and Analysis 6 Conclusion and Future Work References Network and Security PSG: Local Privacy Preserving Synthetic Social Graph Generation 1 Introduction 2 Related Work 2.1 Social Network Privacy Protection 2.2 Synthetic Graph Generation 3 Preliminaries 3.1 System Overview 3.2 Problem Statement 4 Design Details 4.1 Privacy Protection Mechanism Design 4.2 Privacy Analysis 4.3 Synthetic Network Generation 5 Performance Evaluation 5.1 Datasets and Models 5.2 Evaluation Metrics 5.3 Experimental Results 6 Conclusion References Topology Self-optimization for Anti-tracking Network via Nodes Distributed Computing 1 Introduction 2 Related Works 3 Introduction to Convex-Polytope Topology 3.1 Basic Properties 3.2 The Optimum Structure of CPT 4 Topology Self-optimization 4.1 Calculation of Optimum Local Topology 4.2 Topology Self-optimization via Nodes’ Collaboration 5 Performance Evaluation 5.1 Evaluation of Network Optimization 5.2 Evaluation of Network Resilience 6 Conclusion References An Empirical Study of Model-Agnostic Interpretation Technique for Just-in-Time Software Defect Prediction 1 Introduction 2 Related Work 2.1 Just-in-time Software Defect Prediction 2.2 Explainability in Software Defect Prediction 3 Classifier-Agnostic Interpretation Technique 3.1 LIME 3.2 BreakDown 3.3 SHAP 4 Experimental Setup 4.1 Data Sets 4.2 Building Classification Models 4.3 Evaluation Metrics 5 Experimental Results and Analysis 5.1 Analysis for RQ1 5.2 Analysis for RQ2 6 Conclusion and Future Work References Yet Another Traffic Black Hole: Amplifying CDN Fetching Traffic with RangeFragAmp Attacks 1 Introduction 2 Background 2.1 CDN Overview 2.2 HTTP Range Request Mechanism on CDN 2.3 Differences in CDNs Handling Range Requests 2.4 Amplification Attacks 3 RangeFragAmp Attack 3.1 Threat Model 3.2 S-RFA Attack 3.3 O-RFA Attack 4 Real-World Evaluation 4.1 Consideration in Selecting CDN Providers 4.2 S-RFA Attack Evaluation 4.3 O-RFA Attack Evaluation 4.4 Severity Assessment 4.5 CDN Providers Feedback 5 Mitigation 5.1 Root Cause Analysis 5.2 Limitation 5.3 Solutions 6 Related Work 7 Conclusion References DCNMF: Dynamic Community Discovery with Improved Convex-NMF in Temporal Networks 1 Introduction 2 Related Work 3 Algorithm 3.1 Notation 3.2 The Unified DCNMF Model Formulation 3.3 Optimization 4 Experiments and Results 4.1 Evaluation Measures 4.2 Synthetic Dataset 1: Dynamic-GN Dataset 4.3 Synthetic Dataset 2: Dynamic-LFR Dataset 4.4 KIT-Email Data 5 Discussion and Conclusion References Network and Security and IoT and Social Networks Loopster++: Termination Analysis for Multi-path Linear Loop 1 Introduction 2 Preliminaries 2.1 Scope of Our Work 2.2 Path Dependency Automaton (PDA) 2.3 The Structure of Loopster 2.4 Termination of Linear Loop Program 3 Methodology 3.1 Path Termination Analysis 3.2 Inter-Path Analysis 3.3 Cycle Analysis 4 Implementation and Evaluation 4.1 Effectiveness of Loopster++ 4.2 Performance of Loopster++ 5 Relate Work 6 Conclusion References A Stepwise Path Selection Scheme Based on Multiple QoS Parameters Evaluation in SDN 1 Introduction 2 Related Work 3 Proposed Scheme: SWQoS 3.1 SWQoS Scheme Architecture 3.2 Path Finding 3.3 QoS Requirements of Services 3.4 Path Selection 4 Experiments and Performance Evaluation 4.1 The Experimental Environment and Topology 4.2 The First Group Experiment: Simulating the Network Status of Selecting the Preferred Paths 4.3 The Second Group Experiment: Simulating the Network Status of Obtaining Satisfied Paths 4.4 The Third Group Experiment: Simulating the Network Status of Obtaining Reluctant Paths 5 Conclusions References A Novel Approach to Taxi-GPS-Trace-Aware Bus Network Planning 1 Introduction 2 Related Work 3 Main Steps 3.1 Candidate Bus Stop Identification 3.2 Bus Network Generation 4 Simulations 5 Conclusion References Community Influence Maximization Based on Flexible Budget in Social Networks 1 Introduction 2 Related Work 3 System Model and Problem Formulation 3.1 System Model 3.2 Problem Formulation 4 Our Solutions 4.1 General Solution 4.2 FBCIM Algorithm 4.3 FBBCIM Algorithm 5 Performance Evaluation 5.1 Datasets and Parameters Setting 5.2 Comparison of Algorithms and Metrics 5.3 Evaluation Results 6 Conclusion References An Online Truthful Auction for IoT Data Trading with Dynamic Data Owners 1 Introduction 2 System Model and Problem Formulation 2.1 System Model 2.2 Data Trading Model Based on an Auction Mechanism 2.3 Problem Formulation 3 Online Data Trading Algorithm 3.1 Online Matching Algorithm Based on a Greedy Strategy 3.2 Computing Trading Prices Based on Critical Data Owners 3.3 Theoretical Analysis 4 Numerical Illustration 4.1 Methodology and Simulation Settings 4.2 Numerical Results 5 Related Work 5.1 Decentralized Data Trading Based on the Blockchain Technology 5.2 Trading Data with Different Levels of Privacy 6 Conclusion References IoT and Social Networks and Images Handling and Human Recognition Exploiting Heterogeneous Information for IoT Device Identification Using Graph Convolutional Network 1 Introduction 2 Preliminaries 2.1 TLS Basics 2.2 Graph Convolutional Networks 2.3 Problem Definition 3 The THG-IoT Framework 3.1 Data Preprocessing 3.2 Graph Generation 3.3 GCN Classifier 4 Experimental Evaluation 4.1 Dataset 4.2 Evaluation Metrics 4.3 Experimental Setting 4.4 Parameter Study 4.5 Comparison Experiments 4.6 Variant of THG-IoT 5 Related Work 6 Conclusions and Future Work References Data-Driven Influential Nodes Identification in Dynamic Social Networks 1 Introduction 2 Related Work 3 Data-Driven Model for Influential Nodes Identification in Social Networks 3.1 Multi-scale Comprehensive Metric System 3.2 Data-Driven Weight Optimization Algorithm 3.3 Influential Nodes Identification Based on Data-Driven Weighted TOPSIS 4 Experiments and Analysis 4.1 Experimental Setup 4.2 Performance Comparison 5 Conclusion and Future Work References Human Motion Recognition Based on Wi-Fi Imaging Abstract 1 Introduction 2 Wi-Fi Imaging Algorithm Based on 3D Virtual Array 2.1 Imaging Algorithm Based on Virtual 3D Array 2.2 Description of Improved 3D Decoherence Algorithm 3 Environment Adaptive Human Continuous Motion Recognition 3.1 Continuous Action Segmentation 3.2 Action Feature Extraction 3.3 SVM Classification Based on GA Algorithm Optimization 4 Experiment and Result Analysis 4.1 Experimental Configuration 4.2 Human Imaging and Motion Recognition 4.3 Result Analysis 4.4 Model Test 4.5 Comparison of Different Models 5 Conclusion Acknowledgment References A Pervasive Multi-physiological Signal-Based Emotion Classification with Shapelet Transformation and Decision Fusion Abstract 1 Introduction 2 Related Works 2.1 Emotion Classification Based on Physiological Signals 2.2 Shapelet-Based Algorithms 3 Methods 3.1 Overview 3.2 Data Preprocessing 3.3 Sub-classification Methods 3.3.1 Shapelet Transformation Algorithm 3.3.2 Feature Extraction 3.3.3 Sub-classifiers 3.4 Decision-Level Fusion Strategy 4 Experimental Results and Analysis 4.1 Database 4.2 Results of Emotion Classification of a Single Physiological Signal 4.3 Results Comparisons 5 Conclusion and Future Work Acknowledgments References A Novel and Efficient Distance Detection Based on Monocular Images for Grasp and Handover 1 Introduction 2 Related Works 2.1 RGB-D-Based Methods 2.2 Analytic-Based Methods 2.3 Model-Based Methods 3 Method 3.1 Distance Detection A 3.2 Distance Detection B 4 Experiments and Results 4.1 Experimental Equipment 4.2 Preliminary Work 4.3 Grasping Tests 4.4 Human-Robot Handover Tests 4.5 Time Cost 4.6 Qualitative Results and Future Work 5 Conclusion References Images Handling and Human Recognition and Edge Computing A Novel Gaze-Point-Driven HRI Framework for Single-Person 1 Introduction 2 Related Work 2.1 Gaze Point Estimation 2.2 Application of Gaze Points in HRI 3 Methods 3.1 Overview 3.2 Object Locations Distribution Obtaining 3.3 Gaze Points Distribution Estimating 3.4 Gaze Target Reasoning and Entity Matching 3.5 Moving and Grabbing 4 Results 4.1 Experimental Equipment and Setup 4.2 Experimental Results 5 Conclusion References Semi-automatic Segmentation of Tissue Regions in Digital Histopathological Image 1 Introduction 2 Related Work 2.1 Methods Based on Hand-Crafted Features 2.2 Methods Based on Deep Learning 3 Preliminaries 3.1 Methodology Overview 3.2 Histopathological Images Preprocessing: Staining Normalization 3.3 Pre-segmentation of Tissue Regions 3.4 Automatic Segmentation of Tissue Regions 4 Experiments and Results Analysis 4.1 Experimental Objective 4.2 Dataset 4.3 Experimental Setup 4.4 Experimental Results and Analysis 5 Conclusion and Future Work References T-UNet: A Novel TC-Based Point Cloud Super-Resolution Model for Mechanical LiDAR 1 Introduction 2 Related Works 3 Model Architecture 3.1 Point Cloud Projection and Back-Projection 3.2 T-UNet Model 4 Experimental Study 4.1 Datasets 4.2 Implementation Details 4.3 Model Evaluation 5 Conclusion References Computation Offloading for Multi-user Sequential Tasks in Heterogeneous Mobile Edge Computing 1 Introduction 2 Related Work 3 MUST Model and Problem Formulation 3.1 System Model 3.2 Problem Formulation 4 Regular Expression Based Algorithm for MUST 5 Performance Evaluation 5.1 Setup 5.2 Results 6 Conclusion References Model-Based Evaluation and Optimization of Dependability for Edge Computing Systems 1 Introduction 2 Related Work 3 Dependability Modeling and Analysis of Edge/Cloud Server 3.1 System State Transition Model 3.2 Analysis of Dependability Attributes 4 Dependability Modeling and Analysis of Edge Computing System 4.1 State Aggregation Technique 4.2 Dependability Model of Edge Computing Systems 5 Model and Approach of Dependability Optimization 6 Empirical Evaluation 6.1 Data Set and Experimental Settings 6.2 Experimental Results 7 Conclusion References Author Index