Umfang:
1 Online-Ressource (669 Seiten)
ISBN:
9783030908881
Serie:
Lecture Notes in Computer Science Ser. v.13080
Anmerkung:
Description based on publisher supplied metadata and other sources
,
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- BlockChain and Crowdsourcing -- Crowdsourcing Software Vulnerability Discovery: Models, Dimensions, and Directions -- 1 Introduction -- 2 Models for Crowdsourcing Vulnerability Discovery -- 2.1 Direct Vulnerability Discovery -- 2.2 Platform Managed Vulnerability Discovery -- 2.3 Cyber Security Contests -- 3 Dimensions of Crowdsourcing Vulnerability Discovery -- 3.1 Crowd Size -- 3.2 Incentives -- 3.3 Duration of the Task -- 3.4 Task Context -- 3.5 Task Management -- 3.6 Selecting Security Professionals -- 3.7 Information Protection -- 3.8 Legal Terms -- 4 Discussion and Future Research Directions -- 4.1 Improving the Quality of Vulnerability Tasks Descriptions and Reports -- 4.2 Protecting Against Intellectual Property Leakage -- 4.3 Crowdsourcing Vulnerability Discovery Quality Analytics -- 5 Conclusion -- References -- Expertise-Aware Crowdsourcing Taxonomy Enrichment -- 1 Introduction -- 2 Problem Formulation -- 3 Our Method -- 3.1 Uncertain Instances Finding and Skill Matching -- 3.2 Subtree Recommendation -- 3.3 Skill Estimation -- 3.4 Truth Inference -- 4 Experiments -- 4.1 Baseline Methods -- 4.2 Evaluation Metrics -- 4.3 Simulated Experiment -- 4.4 Real-World Experiment -- 5 Related Works -- 6 Conclusion and Future Work -- References -- Transaction Confirmation Time Estimation in the Bitcoin Blockchain -- 1 Introduction -- 2 Background and Related Work -- 2.1 Blockchain Management -- 2.2 Transaction Confirmation in the Bitcoin Blockchain -- 2.3 Related Works on Transaction Confirmation Time Estimation -- 3 Problem Definition -- 4 Methods for Confirmation Time Estimation -- 4.1 Decayed Mean (DcyMean) -- 4.2 Confirmation Time Estimation Network (CTEN) -- 5 Experiments -- 5.1 Experiment Settings -- 5.2 Result Analysis -- 6 Conclusion -- References
,
Automatic Malicious Worker Detection in Crowdsourced Paraphrases -- 1 Introduction -- 2 Cheating Behaviors -- 3 Cheating Detection -- 3.1 Feature Engineering -- 3.2 Malicious Worker Detection -- 4 Experiment and Results -- 4.1 Evaluation -- 4.2 Error Analysis -- 5 Related Work -- 6 Conclusion -- References -- A Blockchain-Based Approach for Trust Management in Collaborative Business Processes -- 1 Introduction -- 2 Related Work -- 3 Motivating Example -- 4 Methodology -- 4.1 Metrics to Support On-Chain Elements Selection -- 4.2 Abstract Smart Contracts Generation -- 5 Implementation and Validation Issues -- 6 Concluding Remarks and Future Research -- References -- Database System and Workflow -- Exploiting Unblocking Checkpoint for Fault-Tolerance in Pregel-Like Systems -- 1 Introduction -- 2 Background of Pregel-Like Systems -- 2.1 Execution Workflow -- 2.2 Checkpointing -- 3 Queuing Strategy -- 3.1 Resource Contention -- 3.2 Checkpoint Queuing -- 4 Skipping Policy -- 4.1 Checkpoint Staleness -- 4.2 Checkpoint Tardiness -- 4.3 Staleness/Tardiness-Aware Skipping -- 5 Experimental Studies -- 5.1 Experimental Setting -- 5.2 Efficiency of Queuing Strategy -- 5.3 Efficiency of Skipping Policy -- 6 Related Work -- 7 Conclusions -- References -- A Low-Latency Metadata Service for Geo-Distributed File Systems -- 1 Introduction -- 2 The Geo-Distributed File System Framework -- 3 A Low-Latency Metadata Service -- 4 Experiment Evaluation -- 4.1 Experiment Settings -- 4.2 Experiment Comparison Analysis -- 4.3 Evaluation Result -- 5 Related Works -- 6 Conclusion -- References -- XTuning: Expert Database Tuning System Based on Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 Expert Knowledge-Based Tuning Architecture -- 3.1 Correlation Rules Table of Knobs -- 3.2 Knobs Correlation with Internal Expert Knowledge
,
3.3 Workloads Correlation with External Expert Knowledge -- 3.4 Progressive Expert Knowledge Tuning Algorithm -- 4 Experiment Study -- 4.1 Training Time Reduction with Expert Rules -- 4.2 Throughput Improvement -- 4.3 Latency Reduction -- 4.4 Architectural Optimization Performance in XTuning -- 5 Conclusion -- References -- CELA: An Accurate Learned Cardinality Estimator with Strong Generalization Ability and Dimensional Adaptability -- 1 Introduction -- 2 Related Work -- 3 Vectorization -- 4 Model -- 4.1 Considerations -- 4.2 Dynamic Vectorization -- 4.3 Dynamic Architecture -- 5 Experiment -- 5.1 Generating Data -- 5.2 Model Training -- 5.3 Evaluation -- 6 Conclusions -- References -- Cost-Based Lightweight Storage Automatic Decision for In-Database Machine Learning -- 1 Introduction -- 2 System Overview -- 3 Data Preparation -- 3.1 Data Partition -- 3.2 Feature Selection -- 3.3 Data Collection -- 4 Storage Decision Model -- 5 Experiments -- 5.1 Accuracy Evaluation -- 5.2 Feature Section Effectiveness Evaluation -- 5.3 Compare the Applicable Workloads of Row/Column Model -- 5.4 Comparisons on Various Workloads -- 6 Conclusions -- References -- Data Mining and Applications -- NP-PROV: Neural Processes with Position-Relevant-Only Variances -- 1 Introduction -- 2 Background -- 3 Neural Processes with Position-Relevant-Only Variances -- 3.1 Off-the-Grid Scenario -- 3.2 On-the-Grid Scenario -- 4 Experiments -- 4.1 Off-the-Grid Datasets -- 4.2 On-the-Grid Datasets -- 5 Related Work -- 6 Conclusions and Discussions -- A Compuational Complexity -- B Off-the-Grid Datasets Experiments -- C On-the-Grid Datasets Experiments -- References -- A Minority Class Boosted Framework for Adaptive Access Control Decision-Making -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Workflow of the Proposed Framework -- 3.2 Boosting Window Algorithm
,
4 Experiment Results -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Experimental Setting -- 4.4 Performance of Boosting Misclassified Samples -- 4.5 Performance Comparison with Different Negative Sample Rates -- 4.6 Discussion -- 5 Conclusion -- References -- Recognizing Hand Gesture in Still Infrared Images by CapsNet -- 1 Introduction -- 2 Related Work -- 2.1 CapsNet -- 2.2 Hand Gesture Recognition -- 3 Proposed Approach -- 3.1 Capsule Module -- 3.2 Reconstruction Module -- 4 Experimental Settings -- 4.1 Dataset -- 4.2 Dataset Split Modes -- 4.3 Training Parameters of the Proposed Approach -- 5 Experimental Results and Analysis -- 5.1 Experimental Results of Our Approach -- 5.2 Comparison of Confusion Matrix of Different Dataset Split Modes -- 5.3 Comparison with Existing Approaches -- 5.4 Comparison of Training Curve and Validation Curve for Different Dataset Split Modes -- 6 Ablation Study -- 6.1 Evaluation on Different Networks -- 6.2 Evaluation on Different Routing Iterations -- 6.3 Discussion -- 7 Conclusion and Future Work -- References -- Vertical Federated Principal Component Analysis on Feature-Wise Distributed Data -- 1 Introduction -- 2 Notations and Background -- 2.1 Notation -- 2.2 PCA and Power Iteration -- 2.3 Federated Learning -- 3 Federated-PCA on Privacy-Preserving Vertical-Partitioned Data -- 3.1 Problem Formulation -- 3.2 Local Power Method -- 3.3 Federated Communication -- 3.4 Sever-Clients Architecture -- 3.5 Local Power Iteration with Warm Start -- 3.6 Weight Scaling Method -- 3.7 Fully Decentralized Architecture -- 3.8 Complexity Analysis -- 4 Experimental Results -- 4.1 Experiment on Structured Dataset -- 4.2 Case Studies -- 5 Concluding Remarks -- References -- Anchoring-and-Adjustment to Improve the Quality of Significant Features -- 1 Introduction -- 2 Proposed Two-Stage Anchoring-and-Adjustment Approach
,
2.1 Anchoring Stage Using Explainability Maximized Method -- 2.2 Adjustment Stage -- 3 Empirical Evaluation -- 4 Conclusion -- References -- Data Mining Based Artificial Intelligent Technique for Identifying Abnormalities from Brain Signal Data -- 1 Introduction -- 2 Workflow -- 2.1 Pre-processing the Brain Signal Data -- 2.2 Spectrogram Image Generation -- 2.3 Feature Extraction and Dimension Reduction -- 2.4 Classification of the Extracted Features -- 3 Performance Evaluation Materials and Parameters -- 3.1 Datasets -- 3.2 Classification Performance Measure -- 4 Experimental Results -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Where Should I Go? A Deep Learning Approach to Personalize Type-Based Facet Ranking for POI Suggestion -- 1 Introduction -- 2 Facet Ranking Related Research -- 3 Proposed Approach -- 4 Evaluation -- 5 Conclusions -- References -- Modeling Without Sharing Privacy: Federated Neural Machine Translation -- 1 Introduction -- 2 Proposed Method -- 2.1 Problem Definition -- 2.2 Architecture of FedNMT -- 2.3 Federated Vocabulary -- 2.4 Secure Model Training -- 2.5 Domain Expert -- 3 Experiment -- 3.1 Experiment Setups -- 3.2 Performance -- 4 Conclusion -- References -- Knowledge Graph and Entity Linking -- Encoding the Meaning Triangle (Object, Entity, and Concept) as the Semantic Foundation for Entity Alignment -- 1 Introduction -- 2 Problem Formulation -- 3 The C4EA Framework -- 3.1 Entity Representation Learning -- 3.2 Concept Representation Learning -- 3.3 Model Optimization -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Setup -- 4.3 Experimental Results -- 4.4 Analysis -- 5 Related Work -- 6 Conclusion -- References -- Incorporating Network Structure with Node Information for Semi-supervised Anomaly Detection on Attributed Graphs -- 1 Introduction -- 2 Background -- 2.1 Problem Definition
,
2.2 Related Work
Weitere Ausg.:
Erscheint auch als Druck-Ausgabe Zhang, Wenjie Web Information Systems Engineering - WISE 2021 Cham : Springer International Publishing AG,c2021 ISBN 9783030908874
Sprache:
Englisch
Schlagwort(e):
Anwendungssoftware
;
Data Mining
;
Datenbankverwaltung
;
Künstliche Intelligenz
;
Konferenzschrift
Bookmarklink