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Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part II / / edited by Xiangyu Song, Ruyi Feng, Yunliang Chen, Jianxin Li, Geyong Min
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part II / / edited by Xiangyu Song, Ruyi Feng, Yunliang Chen, Jianxin Li, Geyong Min
Autore Song Xiangyu
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (536 pages)
Disciplina 005.7
Altri autori (Persone) FengRuyi
ChenYunliang
LiJianxin
MinGeyong
Collana Lecture Notes in Computer Science
Soggetto topico Big data
Data structures (Computer science)
Information theory
Application software
Image processing - Digital techniques
Computer vision
Data mining
Big Data
Data Structures and Information Theory
Computer and Information Systems Applications
Computer Imaging, Vision, Pattern Recognition and Graphics
Data Mining and Knowledge Discovery
ISBN 981-9723-90-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part II -- Computing Maximal Likelihood Subset Repair for Inconsistent Data -- 1 Introduction -- 2 Problem Statement -- 2.1 Function Dependency -- 2.2 Subset Repair -- 2.3 Problem Definition -- 3 Statistical Learning and Inference -- 3.1 Probability Modeling -- 3.2 Scalable Inference -- 4 Subset Repair with Maximum Likelihood -- 4.1 From Maximum Likelihood to Minimum Cost -- 4.2 Approximate Algorithm -- 5 Experiments -- 5.1 Experimental Steup -- 5.2 Performance Evaluation -- 5.3 Runtime Evaluation -- 6 Related Work -- 7 Conclusions -- References -- Design of Data Management System for Sustainable Development of Urban Agglomerations' Ecological Environment Based on Data Lake Architecture -- 1 Introduction -- 2 Related Work -- 3 System Architecture Design -- 4 System Implementation -- 4.1 Metadata Design -- 4.2 Data Management -- 4.3 Data Product Production -- 4.4 System Presentation -- 5 Future Work -- 6 Conclusion -- References -- P-QALSH+: Exploiting Multiple Cores to Parallelize Query-Aware Locality-Sensitive Hashing on Big Data -- 1 Introduction -- 1.1 Our Contribution -- 2 Preliminaries -- 2.1 c-ANN Search Problem -- 2.2 Framework of QALSH -- 3 Parallel Table Design -- 3.1 Inter-Table Parallel Design -- 3.2 Intra-table Parallel Design -- 4 Parallel Query Design -- 4.1 Overview of Parallel Query -- 4.2 Parallel Collision Counting Technology -- 4.3 Search Radius Estimation Strategy -- 5 Experiments -- 5.1 Experiment Setup -- 5.2 Results and Analysis of the Index Phase -- 5.3 Results and Analysis of the Query Phase -- 6 Conclusion -- References -- Face Super-Resolution via Progressive-Scale Boosting Network -- 1 Introduction -- 2 Face Super-Resolution -- 3 Our Methods -- 3.1 Network Architectures -- 3.2 Attention Feature Fusion Block -- 4 Experimental Results and Analysis.
4.1 Datasets and Implementation Details -- 4.2 Compared with State-of-the-Arts -- 4.3 Ablation Study -- 4.4 Effectiveness of the Proposed Method -- 5 Conclusion -- References -- An Investigation of the Effectiveness of Template Protection Methods on Protecting Privacy During Iris Spoof Detection -- 1 Introduction -- 2 Related Work -- 2.1 Iris Spoof Detection -- 2.2 Iris Template Protection Methods -- 3 Methodology -- 3.1 TPISD -- 3.2 Image Pre-processing -- 3.3 Iris Template Protection Methods -- 3.4 Spoof Detection Model -- 3.5 Security Analysis -- 4 Experiment -- 4.1 Dataset and Evaluation Metrics -- 4.2 Experimental Setup -- 4.3 Transformation Parameter Experiment -- 5 Conclusion -- References -- Stock Volatility Prediction Based on Transformer Model Using Mixed-Frequency Data -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Basic Theory of Volatility -- 3.2 Definition of Indicators -- 3.3 Prediction Method -- 4 Empirical Analysis -- 4.1 Experiment Setup -- 4.2 Experiment Result -- 5 Conclusion -- References -- A Hierarchy-Based Analysis Approach for Blended Learning: A Case Study with Chinese Students -- 1 Introduction -- 2 Related Work -- 2.1 Elements Regarding Evaluating Blended Learning -- 2.2 Evaluation Frameworks -- 3 Method -- 3.1 Gradient Boosting Regression -- 3.2 Gini Importance and Permutation Importance -- 3.3 Analytic Hierarchy Process -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Experimental Setup -- 4.3 Results and Analysis -- 5 Conclusion -- References -- A Multi-teacher Knowledge Distillation Framework for Distantly Supervised Relation Extraction with Flexible Temperature -- 1 Introduction -- 2 Related Work -- 2.1 Distantly Supervised Relation Extraction -- 2.2 Knowledge Distillation -- 3 Method -- 3.1 Task Definition -- 3.2 Model Overview -- 3.3 Flexible Temperature Regulation.
3.4 Multi-view Knowledge Distillation -- 3.5 Total Loss of Student Model -- 4 Experiments -- 4.1 Datasets -- 4.2 Evaluation Metrics and Settings -- 4.3 Baselines -- 4.4 Main Results -- 4.5 Ablation Study -- 5 Conclusion -- References -- PAEE: Parameter-Efficient and Data-Effective Image Captioning Model with Knowledge Prompter and Cross-Modal Representation Aligner -- 1 Introduction -- 2 Related Work -- 2.1 Frozen Parameters Captioning Models -- 2.2 Knowledge Retrieval-Based Prompting -- 2.3 Visual and Language Connection -- 2.4 Prompting Caption Generation -- 3 Method -- 3.1 Architecture -- 3.2 Pre-trained Image Encoder -- 3.3 Pre-trained Language Model -- 3.4 Prompter-Based Caption Generation -- 3.5 Cross-Modal Representation Aligner -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Performance Comparison -- 4.3 Data Utilization Capabilities -- 4.4 Exploration of Small-Data Learning -- 4.5 Ablation Analysis -- 4.6 Qualitative Analysis -- 5 Conclusion and Future Work -- References -- TSKE: Two-Stream Knowledge Embedding for Cyberspace Security -- 1 Introduction -- 2 Related Work -- 2.1 Knowledge Representation Models -- 2.2 Knowledge Embedding Methods -- 3 Preliminaries -- 3.1 System Model -- 3.2 Problem Definition -- 4 TSKE: A Two-Stream Knowledge Embedding Method Based on the MDATA Model -- 4.1 Static Stream Model -- 4.2 Spatio-Temporal Stream Model -- 4.3 Weighted Fusion -- 4.4 Learning -- 5 Experiment Results -- 5.1 Implementation -- 5.2 Baselines -- 5.3 Attack Link Prediction -- 5.4 Results -- 6 Conclusion and Future Work -- References -- Research on the Impact of Executive Shareholding on New Investment in Enterprises Based on Multivariable Linear Regression Model -- 1 Introduction -- 2 Related Work -- 2.1 Executive Shareholding and Corporate Innovation Investment -- 2.2 Two Types of Agency Costs -- 3 Method.
3.1 Data Sources and Variable Definition -- 3.2 Research Hypothesis -- 3.3 Research Model Design -- 4 Analysis of Empirical Test Results -- 4.1 Descriptive Statistics -- 4.2 Correlation Analysis -- 4.3 Analysis of Regression Results -- 4.4 Robustness Test -- 5 Conclusion -- References -- MCNet: A Multi-scale and Cascade Network for Semantic Segmentation of Remote Sensing Images -- 1 Introduction -- 2 Methods -- 2.1 Overall -- 2.2 Multi-scale Feature Extraction Module -- 2.3 Channel Activation Module -- 2.4 Cross-Layer Feature Selection Module -- 2.5 Multi-scale Object Guidance Module -- 2.6 Loss Function -- 3 Datasets and Experimental Implementation -- 3.1 Dataset Description -- 3.2 Implementation Details -- 3.3 Evaluation Indicators -- 4 Experimental Results and Analysis -- 4.1 Results -- 4.2 Analysis -- 4.3 Ablation Experiments -- 5 Conclusion -- References -- WikiCPRL: A Weakly Supervised Approach for Wikipedia Concept Prerequisite Relation Learning -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Proposed Approach -- 4.1 Overview of WikiCPRL -- 4.2 Weak Label Generation -- 4.3 Concept Feature Acquisition -- 4.4 Graph Attentional Layer -- 4.5 Encoding-Decoding Layer -- 4.6 Edge Direction Inferring -- 5 Performance Analysis -- 5.1 Datasets -- 5.2 Compare with Baselines -- 5.3 Case Study -- 6 Conclusion -- References -- An Effective Privacy-Preserving and Enhanced Dummy Location Scheme for Semi-trusted Third Parties -- 1 Introduction -- 2 Model and Design Goal -- 2.1 System Model -- 2.2 Security Model -- 2.3 Design Goal -- 3 EPED Scheme Design -- 3.1 Preliminaries -- 3.2 Location Anonymization Model -- 3.3 Optimization Based on the Stackelberg Game -- 4 Performance Evaluation and Security Analysis -- 4.1 Performance Analysis -- 4.2 Security Analysis -- 5 Related Work -- 6 Conclusion -- References.
W-MRI: A Multi-output Residual Integration Model for Global Weather Forecasting -- 1 Introduction -- 2 Related Work -- 2.1 Numerical Weather Prediction -- 2.2 Deep Learning Weather Forecasting Methods -- 2.3 Residual Network -- 3 Preliminaries -- 3.1 Dataset -- 3.2 Multi-variable Forecasting Problems -- 4 Method -- 4.1 ViT and Residual Model -- 4.2 Integration and Constraint of Residual -- 5 Experiments -- 5.1 Evaluation Metrics -- 5.2 Quantitative Forecasting Performance of W-MRI -- 5.3 Effect of Integration Constraint Module -- 6 Conclusion -- References -- HV-Net: Coarse-to-Fine Feature Guidance for Object Detection in Rainy Weather -- 1 Introduction -- 2 Related Work -- 2.1 Object Detection -- 2.2 Single Image Deraining -- 3 Proposed Method -- 3.1 Generate the Edge Map -- 3.2 From Edge-Attentional Features to Image -- 3.3 Object Detection Stage -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Qualitative and Quantitative Results -- 4.4 Ablation Study -- 5 Conclusion -- References -- Vehicle Collision Warning System for Blind Zone in Curved Roads Based on the Spatial-Temporal Correlation of Coordinate -- 1 Introduction -- 2 Materials and Methods -- 2.1 Target Tracking Method -- 2.2 Traffic Condition Analysis -- 2.3 Module of Communication -- 3 Results -- 3.1 Software Testing -- 3.2 Field Application -- 4 Conclusions -- References -- Local-Global Cross-Fusion Transformer Network for Facial Expression Recognition -- 1 Introduction -- 2 Related Work -- 2.1 Facial Expression Recognition -- 2.2 Transformer -- 3 Method -- 3.1 Overall Framework -- 3.2 Local Feature Decomposition (LFD) -- 3.3 Cross-Fusion Transformer -- 3.4 Loss Function -- 4 Experiment -- 4.1 Experiment Setup -- 4.2 Comparison with the State-of-the-Art Methods -- 4.3 Param and FLOPs Comparison -- 4.4 Ablation Study -- 5 Conclusions -- References.
Answering Spatial Commonsense Questions by Learning Domain-Invariant Generalization Knowledge.
Record Nr. UNINA-9910855375403321
Song Xiangyu  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part III / / edited by Xiangyu Song, Ruyi Feng, Yunliang Chen, Jianxin Li, Geyong Min
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part III / / edited by Xiangyu Song, Ruyi Feng, Yunliang Chen, Jianxin Li, Geyong Min
Autore Song Xiangyu
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (540 pages)
Disciplina 005.7
Altri autori (Persone) FengRuyi
ChenYunliang
LiJianxin
MinGeyong
Collana Lecture Notes in Computer Science
Soggetto topico Big data
Data structures (Computer science)
Information theory
Application software
Image processing - Digital techniques
Computer vision
Data mining
Big Data
Data Structures and Information Theory
Computer and Information Systems Applications
Computer Imaging, Vision, Pattern Recognition and Graphics
Data Mining and Knowledge Discovery
ISBN 981-9723-87-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part III -- Adaptive Graph Attention Hashing for Unsupervised Cross-Modal Retrieval via Multimodal Transformers -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Notation and Problem Definition -- 3.2 Framework Overview -- 3.3 Objective Function -- 4 Experiments -- 4.1 Evaluation Metrics -- 4.2 Implementation Details -- 4.3 Comparison Results and Analysis -- 4.4 Ablation Study -- 4.5 Parameter Sensitivity Analysis -- 4.6 Convergence Testing -- 5 Conclusion -- References -- Answering Property Path Queries over Federated RDF Systems -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 The Proposed Method -- 4.1 Query Decomposition and Source Localization -- 4.2 Thompson-Based MinDFA Construction -- 4.3 Query Execution Strategy Base on B-DFS -- 5 Evaluation -- 5.1 Experimental Environment -- 5.2 Performance Comparison of Five Property Path Query Symbols -- 5.3 Performance and Resource Consumption of Different Matching Strategies of MinDFA -- 5.4 Performance Robustness of Five Property Path Query Symbols -- 6 Conclusion -- References -- Distributed Knowledge Graph Query Acceleration Algorithm -- 1 Introduction -- 2 Related Works -- 3 Offline Module for Distributed Construction of Indexes -- 3.1 MapReduce-Based Data Pre-processing -- 3.2 Coding-Oriented Construction of Distributed Hierarchical Clustering -- 4 Online Module for Distributed Parallel Processing of SPARQL Queries -- 4.1 Splitting and Loading of BitSet-Tree -- 4.2 Candidate Solution Acquisition -- 4.3 Shuffle -- 4.4 Merge Splicing of Candidate Vertices -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Results and Discussion -- 6 Conclusions -- References -- Truth Discovery of Source Dependency Perception in Dynamic Scenarios -- 1 Introduction -- 2 Problem Setting -- 2.1 Notation Definition -- 2.2 Task Description.
3 Preliminary -- 3.1 Source Dependency Detection Based on Bayesian Model -- 3.2 Truth Discovery Framework Based on Optimization Model -- 4 Methodology -- 4.1 Source Dependency Detection in Dynamic Scenarios -- 4.2 Dynamic Incremental Model Framework -- 4.3 Truth Discovery with Source Dependency Perception -- 5 Experiment -- 5.1 Experimental Setup -- 5.2 The Results on Real-World Datasets -- 5.3 The Results on Synthetic Datasets -- 6 Related Work -- 7 Conclusion -- References -- Truth Discovery Against Disguised Attack Mechanism in Crowdsourcing -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 3.1 Disguised Attack Mechanism -- 3.2 Problem Formulation -- 3.3 Truth Discovery -- 4 Methodology -- 4.1 Behavior-Based Truth Discovery -- 4.2 Task Assignment Based on WAM -- 4.3 TD-DA Framework -- 5 Experiments -- 5.1 Experiment Setting -- 5.2 Verification of the Proportion of Malicious Workers -- 5.3 Experiment on Real-World Datasets -- 5.4 Experiment on Synthetic Datasets -- 6 Conclusion -- References -- Continuous Group Nearest Group Search over Streaming Data -- 1 Introduction -- 2 Preliminary -- 2.1 Related Works -- 2.2 Problem Definition -- 3 The Framework KMPT -- 3.1 The Basic Idea -- 3.2 The Initialization Algorithm -- 3.3 The Incremental Maintenance Algorithm -- 4 The Experiment -- 4.1 Experiment Settings -- 4.2 Performance Comparison -- 5 Conclusion -- References -- Approximate Continuous Skyline Queries over Memory Limitation-Based Streaming Data -- 1 Introduction -- 2 Preliminary -- 2.1 Related Works -- 2.2 Problem Definition -- 3 The Self-adaptive-based Framework -SEAK -- 3.1 The -CSS Definition -- 3.2 The Initialization Algorithm -- 3.3 The Incremental Maintenance Algorithm -- 3.4 The Partition-Based Optimization Algorithm -- 4 Performance Evaluation -- 4.1 Experiment Settings -- 4.2 Experimental Evaluation -- 5 Conclusion -- References.
Identifying Backdoor Attacks in Federated Learning via Anomaly Detection -- 1 Introduction -- 2 Related Work -- 2.1 Attacks on Model Faithfulness -- 2.2 Defenses Against Backdoor Attack -- 3 Preliminaries and Attack Formulation -- 3.1 Federated Learning -- 3.2 Threat Model -- 3.3 Choice of Backdoor Triggers -- 4 Methodology -- 4.1 Motivation -- 4.2 Segmenting Local Updates -- 4.3 Identifying Outliers in Fragments -- 4.4 Pruning Backdoored Participants -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Effectiveness of Our Defense -- 5.3 Comparison with Prior Arts -- 5.4 Effectiveness on Advanced Attacks -- 5.5 Ablation Study -- 6 Conclusion -- References -- PaTraS: A Path-Preserving Trajectory Simplification Method for Low-Loss Map Matching -- 1 Introduction -- 2 Related Work -- 2.1 Error-Bounded Line Simplification -- 2.2 Semantic-Preserving Trajectory Simplification -- 2.3 Analysis of Existing Work -- 3 Preliminaries -- 3.1 Basic Definitions -- 3.2 Methodology Analysis -- 4 Path-Preserving Trajectory Simplification -- 4.1 Overview of PaTraS -- 4.2 Preserving Shortest Paths -- 4.3 Candidates Pairing -- 4.4 Similarity Computation -- 4.5 Pairing Optimization -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Evaluation Oriented to Map-Matching -- 5.3 Parameter Sensitivity Study -- 6 Conclusion -- References -- Coordinate Descent for k-Means with Differential Privacy -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 3.1 k-Means -- 3.2 Coordinate Descent for k-Means -- 3.3 A Fast Version of CDKM -- 3.4 Differential Privacy -- 4 Proposed Our Method -- 4.1 Approximate CDKM -- 4.2 Proposed DP-ACDKM -- 4.3 Privacy Analysis -- 5 Experiments -- 5.1 Privacy-Utility Trade-Off -- 5.2 Convergence -- 6 Conclusion -- References -- DADR: A Denoising Approach for Dense Retrieval Model Training -- 1 Introduction -- 2 Related Work -- 3 Method.
3.1 Task Formulation -- 3.2 Denoising Approach Based on Dynamical Weight -- 4 Experiment -- 4.1 Dataset and Metrics -- 4.2 Experiment Settings -- 4.3 Experiment Results -- 5 Conclusions -- References -- Multi-pair Contrastive Learning Based on Same-Timestamp Data Augmentation for Sequential Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Self-supervised Learning -- 2.2 Sequential Recommendation -- 3 The Proposed Model -- 3.1 Problem Definition -- 3.2 Model Framework -- 3.3 Data Augmentaion -- 3.4 Masking Operation -- 3.5 Embedding Layer -- 3.6 BERT Encoder -- 3.7 Prediction Layer -- 3.8 Multi-pair Contrastive Learning -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Hyperparameter Experiments -- 4.4 Ablation Study -- 5 Conclusion -- References -- Enhancing Collaborative Features with Knowledge Graph for Recommendation -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Methodology -- 4.1 KG Explore Module -- 4.2 Multi-IMP-GCN -- 4.3 Model Prediction -- 4.4 Model Optimization -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Performance Comparison -- 5.3 Ablation Studies -- 5.4 Impacts of Multi-IMP-GCN -- 6 Conclusion and Future Work -- References -- PageCNNs: Convolutional Neural Networks for Multi-label Chinese Webpage Classification with Multi-information Fusion -- 1 Introduction -- 2 Multi-label Chinese Webpage Classification Models -- 3 Experimental Results and Discussions -- 3.1 Multi-label Chinese Webpage Dataset -- 3.2 Implementation Details and Evaluation Metrics -- 3.3 Multi-label Chinese Webpage Classification Results -- 4 Conclusion -- References -- MFF-Trans: Multi-level Feature Fusion Transformer for Fine-Grained Visual Classification -- 1 Introduction -- 2 Related Works -- 2.1 CNN-Based FGVC Methods -- 2.2 ViT-Based FGVC Methods -- 3 Proposed Method -- 3.1 Vision Transformer Encoder.
3.2 Important Token Election Module -- 3.3 Semantic Connection Enhancing Module -- 4 Experiments -- 4.1 DataSets and Implement Details -- 4.2 Comparisons with Advanced Methods -- 4.3 Ablation Studies -- 5 Conclusion -- References -- Summarizing Doctor's Diagnoses and Suggestions from Medical Dialogues -- 1 Introduction -- 2 Related Work -- 3 Model -- 3.1 Pointer Generator Network as Backbone -- 3.2 Input Token Enhancement by Speaker-level Embedding -- 3.3 Input Token Enhancement by Utterance-level Embedding -- 4 Experiment -- 4.1 Dataset -- 4.2 Baseline Models -- 4.3 Settings -- 4.4 Evaluation Metrics -- 4.5 Automatic Evaluation -- 4.6 Doctor Evaluation -- 4.7 Case Study -- 5 Conclusion -- References -- HSA: Hyperbolic Self-attention for Sequential Recommendation -- 1 Introduction -- 2 Preliminaries and Related Work -- 2.1 Empirical Analysis of Datasets -- 2.2 Lorentz Model of Hyperbolic Space -- 2.3 Self-attention Mechanism for Sequential Recommendation -- 3 Proposed Approach -- 3.1 Problem Formulation and Approach Overview -- 3.2 Item Embeddings in Hyperbolic Space -- 3.3 Sequence Learning with Self-attention Mechanism -- 3.4 Prediction Layer -- 3.5 Model Training -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Performance as a Plugin on Baselines -- 5 Conclusion -- References -- CFGCon: A Scheme for Accurately Generating Control Flow Graphs of Smart Contracts -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Proposed Scheme -- 4.1 Overview of the System Model -- 4.2 Transform Module -- 4.3 Division Module -- 4.4 Connection Module -- 5 Experiment and Performance Evaluation -- 5.1 Dataset -- 5.2 General Test for CFGCon -- 5.3 Performance Comparision with Existing Approaches -- 6 Conclusion -- References -- Hypergraph-Enhanced Self-supervised Heterogeneous Graph Representation Learning -- 1 Introduction.
2 Related Work.
Record Nr. UNINA-9910855389603321
Song Xiangyu  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part II / / edited by Xiangyu Song, Ruyi Feng, Yunliang Chen, Jianxin Li, Geyong Min
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part II / / edited by Xiangyu Song, Ruyi Feng, Yunliang Chen, Jianxin Li, Geyong Min
Autore Song Xiangyu
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (536 pages)
Disciplina 005.7
Altri autori (Persone) FengRuyi
ChenYunliang
LiJianxin
MinGeyong
Collana Lecture Notes in Computer Science
Soggetto topico Big data
Data structures (Computer science)
Information theory
Application software
Image processing - Digital techniques
Computer vision
Data mining
Big Data
Data Structures and Information Theory
Computer and Information Systems Applications
Computer Imaging, Vision, Pattern Recognition and Graphics
Data Mining and Knowledge Discovery
ISBN 981-9723-90-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part II -- Computing Maximal Likelihood Subset Repair for Inconsistent Data -- 1 Introduction -- 2 Problem Statement -- 2.1 Function Dependency -- 2.2 Subset Repair -- 2.3 Problem Definition -- 3 Statistical Learning and Inference -- 3.1 Probability Modeling -- 3.2 Scalable Inference -- 4 Subset Repair with Maximum Likelihood -- 4.1 From Maximum Likelihood to Minimum Cost -- 4.2 Approximate Algorithm -- 5 Experiments -- 5.1 Experimental Steup -- 5.2 Performance Evaluation -- 5.3 Runtime Evaluation -- 6 Related Work -- 7 Conclusions -- References -- Design of Data Management System for Sustainable Development of Urban Agglomerations' Ecological Environment Based on Data Lake Architecture -- 1 Introduction -- 2 Related Work -- 3 System Architecture Design -- 4 System Implementation -- 4.1 Metadata Design -- 4.2 Data Management -- 4.3 Data Product Production -- 4.4 System Presentation -- 5 Future Work -- 6 Conclusion -- References -- P-QALSH+: Exploiting Multiple Cores to Parallelize Query-Aware Locality-Sensitive Hashing on Big Data -- 1 Introduction -- 1.1 Our Contribution -- 2 Preliminaries -- 2.1 c-ANN Search Problem -- 2.2 Framework of QALSH -- 3 Parallel Table Design -- 3.1 Inter-Table Parallel Design -- 3.2 Intra-table Parallel Design -- 4 Parallel Query Design -- 4.1 Overview of Parallel Query -- 4.2 Parallel Collision Counting Technology -- 4.3 Search Radius Estimation Strategy -- 5 Experiments -- 5.1 Experiment Setup -- 5.2 Results and Analysis of the Index Phase -- 5.3 Results and Analysis of the Query Phase -- 6 Conclusion -- References -- Face Super-Resolution via Progressive-Scale Boosting Network -- 1 Introduction -- 2 Face Super-Resolution -- 3 Our Methods -- 3.1 Network Architectures -- 3.2 Attention Feature Fusion Block -- 4 Experimental Results and Analysis.
4.1 Datasets and Implementation Details -- 4.2 Compared with State-of-the-Arts -- 4.3 Ablation Study -- 4.4 Effectiveness of the Proposed Method -- 5 Conclusion -- References -- An Investigation of the Effectiveness of Template Protection Methods on Protecting Privacy During Iris Spoof Detection -- 1 Introduction -- 2 Related Work -- 2.1 Iris Spoof Detection -- 2.2 Iris Template Protection Methods -- 3 Methodology -- 3.1 TPISD -- 3.2 Image Pre-processing -- 3.3 Iris Template Protection Methods -- 3.4 Spoof Detection Model -- 3.5 Security Analysis -- 4 Experiment -- 4.1 Dataset and Evaluation Metrics -- 4.2 Experimental Setup -- 4.3 Transformation Parameter Experiment -- 5 Conclusion -- References -- Stock Volatility Prediction Based on Transformer Model Using Mixed-Frequency Data -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Basic Theory of Volatility -- 3.2 Definition of Indicators -- 3.3 Prediction Method -- 4 Empirical Analysis -- 4.1 Experiment Setup -- 4.2 Experiment Result -- 5 Conclusion -- References -- A Hierarchy-Based Analysis Approach for Blended Learning: A Case Study with Chinese Students -- 1 Introduction -- 2 Related Work -- 2.1 Elements Regarding Evaluating Blended Learning -- 2.2 Evaluation Frameworks -- 3 Method -- 3.1 Gradient Boosting Regression -- 3.2 Gini Importance and Permutation Importance -- 3.3 Analytic Hierarchy Process -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Experimental Setup -- 4.3 Results and Analysis -- 5 Conclusion -- References -- A Multi-teacher Knowledge Distillation Framework for Distantly Supervised Relation Extraction with Flexible Temperature -- 1 Introduction -- 2 Related Work -- 2.1 Distantly Supervised Relation Extraction -- 2.2 Knowledge Distillation -- 3 Method -- 3.1 Task Definition -- 3.2 Model Overview -- 3.3 Flexible Temperature Regulation.
3.4 Multi-view Knowledge Distillation -- 3.5 Total Loss of Student Model -- 4 Experiments -- 4.1 Datasets -- 4.2 Evaluation Metrics and Settings -- 4.3 Baselines -- 4.4 Main Results -- 4.5 Ablation Study -- 5 Conclusion -- References -- PAEE: Parameter-Efficient and Data-Effective Image Captioning Model with Knowledge Prompter and Cross-Modal Representation Aligner -- 1 Introduction -- 2 Related Work -- 2.1 Frozen Parameters Captioning Models -- 2.2 Knowledge Retrieval-Based Prompting -- 2.3 Visual and Language Connection -- 2.4 Prompting Caption Generation -- 3 Method -- 3.1 Architecture -- 3.2 Pre-trained Image Encoder -- 3.3 Pre-trained Language Model -- 3.4 Prompter-Based Caption Generation -- 3.5 Cross-Modal Representation Aligner -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Performance Comparison -- 4.3 Data Utilization Capabilities -- 4.4 Exploration of Small-Data Learning -- 4.5 Ablation Analysis -- 4.6 Qualitative Analysis -- 5 Conclusion and Future Work -- References -- TSKE: Two-Stream Knowledge Embedding for Cyberspace Security -- 1 Introduction -- 2 Related Work -- 2.1 Knowledge Representation Models -- 2.2 Knowledge Embedding Methods -- 3 Preliminaries -- 3.1 System Model -- 3.2 Problem Definition -- 4 TSKE: A Two-Stream Knowledge Embedding Method Based on the MDATA Model -- 4.1 Static Stream Model -- 4.2 Spatio-Temporal Stream Model -- 4.3 Weighted Fusion -- 4.4 Learning -- 5 Experiment Results -- 5.1 Implementation -- 5.2 Baselines -- 5.3 Attack Link Prediction -- 5.4 Results -- 6 Conclusion and Future Work -- References -- Research on the Impact of Executive Shareholding on New Investment in Enterprises Based on Multivariable Linear Regression Model -- 1 Introduction -- 2 Related Work -- 2.1 Executive Shareholding and Corporate Innovation Investment -- 2.2 Two Types of Agency Costs -- 3 Method.
3.1 Data Sources and Variable Definition -- 3.2 Research Hypothesis -- 3.3 Research Model Design -- 4 Analysis of Empirical Test Results -- 4.1 Descriptive Statistics -- 4.2 Correlation Analysis -- 4.3 Analysis of Regression Results -- 4.4 Robustness Test -- 5 Conclusion -- References -- MCNet: A Multi-scale and Cascade Network for Semantic Segmentation of Remote Sensing Images -- 1 Introduction -- 2 Methods -- 2.1 Overall -- 2.2 Multi-scale Feature Extraction Module -- 2.3 Channel Activation Module -- 2.4 Cross-Layer Feature Selection Module -- 2.5 Multi-scale Object Guidance Module -- 2.6 Loss Function -- 3 Datasets and Experimental Implementation -- 3.1 Dataset Description -- 3.2 Implementation Details -- 3.3 Evaluation Indicators -- 4 Experimental Results and Analysis -- 4.1 Results -- 4.2 Analysis -- 4.3 Ablation Experiments -- 5 Conclusion -- References -- WikiCPRL: A Weakly Supervised Approach for Wikipedia Concept Prerequisite Relation Learning -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Proposed Approach -- 4.1 Overview of WikiCPRL -- 4.2 Weak Label Generation -- 4.3 Concept Feature Acquisition -- 4.4 Graph Attentional Layer -- 4.5 Encoding-Decoding Layer -- 4.6 Edge Direction Inferring -- 5 Performance Analysis -- 5.1 Datasets -- 5.2 Compare with Baselines -- 5.3 Case Study -- 6 Conclusion -- References -- An Effective Privacy-Preserving and Enhanced Dummy Location Scheme for Semi-trusted Third Parties -- 1 Introduction -- 2 Model and Design Goal -- 2.1 System Model -- 2.2 Security Model -- 2.3 Design Goal -- 3 EPED Scheme Design -- 3.1 Preliminaries -- 3.2 Location Anonymization Model -- 3.3 Optimization Based on the Stackelberg Game -- 4 Performance Evaluation and Security Analysis -- 4.1 Performance Analysis -- 4.2 Security Analysis -- 5 Related Work -- 6 Conclusion -- References.
W-MRI: A Multi-output Residual Integration Model for Global Weather Forecasting -- 1 Introduction -- 2 Related Work -- 2.1 Numerical Weather Prediction -- 2.2 Deep Learning Weather Forecasting Methods -- 2.3 Residual Network -- 3 Preliminaries -- 3.1 Dataset -- 3.2 Multi-variable Forecasting Problems -- 4 Method -- 4.1 ViT and Residual Model -- 4.2 Integration and Constraint of Residual -- 5 Experiments -- 5.1 Evaluation Metrics -- 5.2 Quantitative Forecasting Performance of W-MRI -- 5.3 Effect of Integration Constraint Module -- 6 Conclusion -- References -- HV-Net: Coarse-to-Fine Feature Guidance for Object Detection in Rainy Weather -- 1 Introduction -- 2 Related Work -- 2.1 Object Detection -- 2.2 Single Image Deraining -- 3 Proposed Method -- 3.1 Generate the Edge Map -- 3.2 From Edge-Attentional Features to Image -- 3.3 Object Detection Stage -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Qualitative and Quantitative Results -- 4.4 Ablation Study -- 5 Conclusion -- References -- Vehicle Collision Warning System for Blind Zone in Curved Roads Based on the Spatial-Temporal Correlation of Coordinate -- 1 Introduction -- 2 Materials and Methods -- 2.1 Target Tracking Method -- 2.2 Traffic Condition Analysis -- 2.3 Module of Communication -- 3 Results -- 3.1 Software Testing -- 3.2 Field Application -- 4 Conclusions -- References -- Local-Global Cross-Fusion Transformer Network for Facial Expression Recognition -- 1 Introduction -- 2 Related Work -- 2.1 Facial Expression Recognition -- 2.2 Transformer -- 3 Method -- 3.1 Overall Framework -- 3.2 Local Feature Decomposition (LFD) -- 3.3 Cross-Fusion Transformer -- 3.4 Loss Function -- 4 Experiment -- 4.1 Experiment Setup -- 4.2 Comparison with the State-of-the-Art Methods -- 4.3 Param and FLOPs Comparison -- 4.4 Ablation Study -- 5 Conclusions -- References.
Answering Spatial Commonsense Questions by Learning Domain-Invariant Generalization Knowledge.
Record Nr. UNISA-996594168303316
Song Xiangyu  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part III / / edited by Xiangyu Song, Ruyi Feng, Yunliang Chen, Jianxin Li, Geyong Min
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part III / / edited by Xiangyu Song, Ruyi Feng, Yunliang Chen, Jianxin Li, Geyong Min
Autore Song Xiangyu
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (540 pages)
Disciplina 005.7
Altri autori (Persone) FengRuyi
ChenYunliang
LiJianxin
MinGeyong
Collana Lecture Notes in Computer Science
Soggetto topico Big data
Data structures (Computer science)
Information theory
Application software
Image processing - Digital techniques
Computer vision
Data mining
Big Data
Data Structures and Information Theory
Computer and Information Systems Applications
Computer Imaging, Vision, Pattern Recognition and Graphics
Data Mining and Knowledge Discovery
ISBN 981-9723-87-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part III -- Adaptive Graph Attention Hashing for Unsupervised Cross-Modal Retrieval via Multimodal Transformers -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Notation and Problem Definition -- 3.2 Framework Overview -- 3.3 Objective Function -- 4 Experiments -- 4.1 Evaluation Metrics -- 4.2 Implementation Details -- 4.3 Comparison Results and Analysis -- 4.4 Ablation Study -- 4.5 Parameter Sensitivity Analysis -- 4.6 Convergence Testing -- 5 Conclusion -- References -- Answering Property Path Queries over Federated RDF Systems -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 The Proposed Method -- 4.1 Query Decomposition and Source Localization -- 4.2 Thompson-Based MinDFA Construction -- 4.3 Query Execution Strategy Base on B-DFS -- 5 Evaluation -- 5.1 Experimental Environment -- 5.2 Performance Comparison of Five Property Path Query Symbols -- 5.3 Performance and Resource Consumption of Different Matching Strategies of MinDFA -- 5.4 Performance Robustness of Five Property Path Query Symbols -- 6 Conclusion -- References -- Distributed Knowledge Graph Query Acceleration Algorithm -- 1 Introduction -- 2 Related Works -- 3 Offline Module for Distributed Construction of Indexes -- 3.1 MapReduce-Based Data Pre-processing -- 3.2 Coding-Oriented Construction of Distributed Hierarchical Clustering -- 4 Online Module for Distributed Parallel Processing of SPARQL Queries -- 4.1 Splitting and Loading of BitSet-Tree -- 4.2 Candidate Solution Acquisition -- 4.3 Shuffle -- 4.4 Merge Splicing of Candidate Vertices -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Results and Discussion -- 6 Conclusions -- References -- Truth Discovery of Source Dependency Perception in Dynamic Scenarios -- 1 Introduction -- 2 Problem Setting -- 2.1 Notation Definition -- 2.2 Task Description.
3 Preliminary -- 3.1 Source Dependency Detection Based on Bayesian Model -- 3.2 Truth Discovery Framework Based on Optimization Model -- 4 Methodology -- 4.1 Source Dependency Detection in Dynamic Scenarios -- 4.2 Dynamic Incremental Model Framework -- 4.3 Truth Discovery with Source Dependency Perception -- 5 Experiment -- 5.1 Experimental Setup -- 5.2 The Results on Real-World Datasets -- 5.3 The Results on Synthetic Datasets -- 6 Related Work -- 7 Conclusion -- References -- Truth Discovery Against Disguised Attack Mechanism in Crowdsourcing -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 3.1 Disguised Attack Mechanism -- 3.2 Problem Formulation -- 3.3 Truth Discovery -- 4 Methodology -- 4.1 Behavior-Based Truth Discovery -- 4.2 Task Assignment Based on WAM -- 4.3 TD-DA Framework -- 5 Experiments -- 5.1 Experiment Setting -- 5.2 Verification of the Proportion of Malicious Workers -- 5.3 Experiment on Real-World Datasets -- 5.4 Experiment on Synthetic Datasets -- 6 Conclusion -- References -- Continuous Group Nearest Group Search over Streaming Data -- 1 Introduction -- 2 Preliminary -- 2.1 Related Works -- 2.2 Problem Definition -- 3 The Framework KMPT -- 3.1 The Basic Idea -- 3.2 The Initialization Algorithm -- 3.3 The Incremental Maintenance Algorithm -- 4 The Experiment -- 4.1 Experiment Settings -- 4.2 Performance Comparison -- 5 Conclusion -- References -- Approximate Continuous Skyline Queries over Memory Limitation-Based Streaming Data -- 1 Introduction -- 2 Preliminary -- 2.1 Related Works -- 2.2 Problem Definition -- 3 The Self-adaptive-based Framework -SEAK -- 3.1 The -CSS Definition -- 3.2 The Initialization Algorithm -- 3.3 The Incremental Maintenance Algorithm -- 3.4 The Partition-Based Optimization Algorithm -- 4 Performance Evaluation -- 4.1 Experiment Settings -- 4.2 Experimental Evaluation -- 5 Conclusion -- References.
Identifying Backdoor Attacks in Federated Learning via Anomaly Detection -- 1 Introduction -- 2 Related Work -- 2.1 Attacks on Model Faithfulness -- 2.2 Defenses Against Backdoor Attack -- 3 Preliminaries and Attack Formulation -- 3.1 Federated Learning -- 3.2 Threat Model -- 3.3 Choice of Backdoor Triggers -- 4 Methodology -- 4.1 Motivation -- 4.2 Segmenting Local Updates -- 4.3 Identifying Outliers in Fragments -- 4.4 Pruning Backdoored Participants -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Effectiveness of Our Defense -- 5.3 Comparison with Prior Arts -- 5.4 Effectiveness on Advanced Attacks -- 5.5 Ablation Study -- 6 Conclusion -- References -- PaTraS: A Path-Preserving Trajectory Simplification Method for Low-Loss Map Matching -- 1 Introduction -- 2 Related Work -- 2.1 Error-Bounded Line Simplification -- 2.2 Semantic-Preserving Trajectory Simplification -- 2.3 Analysis of Existing Work -- 3 Preliminaries -- 3.1 Basic Definitions -- 3.2 Methodology Analysis -- 4 Path-Preserving Trajectory Simplification -- 4.1 Overview of PaTraS -- 4.2 Preserving Shortest Paths -- 4.3 Candidates Pairing -- 4.4 Similarity Computation -- 4.5 Pairing Optimization -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Evaluation Oriented to Map-Matching -- 5.3 Parameter Sensitivity Study -- 6 Conclusion -- References -- Coordinate Descent for k-Means with Differential Privacy -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 3.1 k-Means -- 3.2 Coordinate Descent for k-Means -- 3.3 A Fast Version of CDKM -- 3.4 Differential Privacy -- 4 Proposed Our Method -- 4.1 Approximate CDKM -- 4.2 Proposed DP-ACDKM -- 4.3 Privacy Analysis -- 5 Experiments -- 5.1 Privacy-Utility Trade-Off -- 5.2 Convergence -- 6 Conclusion -- References -- DADR: A Denoising Approach for Dense Retrieval Model Training -- 1 Introduction -- 2 Related Work -- 3 Method.
3.1 Task Formulation -- 3.2 Denoising Approach Based on Dynamical Weight -- 4 Experiment -- 4.1 Dataset and Metrics -- 4.2 Experiment Settings -- 4.3 Experiment Results -- 5 Conclusions -- References -- Multi-pair Contrastive Learning Based on Same-Timestamp Data Augmentation for Sequential Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Self-supervised Learning -- 2.2 Sequential Recommendation -- 3 The Proposed Model -- 3.1 Problem Definition -- 3.2 Model Framework -- 3.3 Data Augmentaion -- 3.4 Masking Operation -- 3.5 Embedding Layer -- 3.6 BERT Encoder -- 3.7 Prediction Layer -- 3.8 Multi-pair Contrastive Learning -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Hyperparameter Experiments -- 4.4 Ablation Study -- 5 Conclusion -- References -- Enhancing Collaborative Features with Knowledge Graph for Recommendation -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Methodology -- 4.1 KG Explore Module -- 4.2 Multi-IMP-GCN -- 4.3 Model Prediction -- 4.4 Model Optimization -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Performance Comparison -- 5.3 Ablation Studies -- 5.4 Impacts of Multi-IMP-GCN -- 6 Conclusion and Future Work -- References -- PageCNNs: Convolutional Neural Networks for Multi-label Chinese Webpage Classification with Multi-information Fusion -- 1 Introduction -- 2 Multi-label Chinese Webpage Classification Models -- 3 Experimental Results and Discussions -- 3.1 Multi-label Chinese Webpage Dataset -- 3.2 Implementation Details and Evaluation Metrics -- 3.3 Multi-label Chinese Webpage Classification Results -- 4 Conclusion -- References -- MFF-Trans: Multi-level Feature Fusion Transformer for Fine-Grained Visual Classification -- 1 Introduction -- 2 Related Works -- 2.1 CNN-Based FGVC Methods -- 2.2 ViT-Based FGVC Methods -- 3 Proposed Method -- 3.1 Vision Transformer Encoder.
3.2 Important Token Election Module -- 3.3 Semantic Connection Enhancing Module -- 4 Experiments -- 4.1 DataSets and Implement Details -- 4.2 Comparisons with Advanced Methods -- 4.3 Ablation Studies -- 5 Conclusion -- References -- Summarizing Doctor's Diagnoses and Suggestions from Medical Dialogues -- 1 Introduction -- 2 Related Work -- 3 Model -- 3.1 Pointer Generator Network as Backbone -- 3.2 Input Token Enhancement by Speaker-level Embedding -- 3.3 Input Token Enhancement by Utterance-level Embedding -- 4 Experiment -- 4.1 Dataset -- 4.2 Baseline Models -- 4.3 Settings -- 4.4 Evaluation Metrics -- 4.5 Automatic Evaluation -- 4.6 Doctor Evaluation -- 4.7 Case Study -- 5 Conclusion -- References -- HSA: Hyperbolic Self-attention for Sequential Recommendation -- 1 Introduction -- 2 Preliminaries and Related Work -- 2.1 Empirical Analysis of Datasets -- 2.2 Lorentz Model of Hyperbolic Space -- 2.3 Self-attention Mechanism for Sequential Recommendation -- 3 Proposed Approach -- 3.1 Problem Formulation and Approach Overview -- 3.2 Item Embeddings in Hyperbolic Space -- 3.3 Sequence Learning with Self-attention Mechanism -- 3.4 Prediction Layer -- 3.5 Model Training -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Performance as a Plugin on Baselines -- 5 Conclusion -- References -- CFGCon: A Scheme for Accurately Generating Control Flow Graphs of Smart Contracts -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Proposed Scheme -- 4.1 Overview of the System Model -- 4.2 Transform Module -- 4.3 Division Module -- 4.4 Connection Module -- 5 Experiment and Performance Evaluation -- 5.1 Dataset -- 5.2 General Test for CFGCon -- 5.3 Performance Comparision with Existing Approaches -- 6 Conclusion -- References -- Hypergraph-Enhanced Self-supervised Heterogeneous Graph Representation Learning -- 1 Introduction.
2 Related Work.
Record Nr. UNISA-996594168203316
Song Xiangyu  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6-8, 2023, Proceedings, Part IV
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6-8, 2023, Proceedings, Part IV
Autore Song Xiangyu
Edizione [1st ed.]
Pubbl/distr/stampa Singapore : , : Springer Singapore Pte. Limited, , 2024
Descrizione fisica 1 online resource (539 pages)
Altri autori (Persone) FengRuyi
ChenYunliang
LiJianxin
MinGeyong
Collana Lecture Notes in Computer Science Series
ISBN 981-9724-21-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910857795603321
Song Xiangyu  
Singapore : , : Springer Singapore Pte. Limited, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6-8, 2023, Proceedings, Part I
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6-8, 2023, Proceedings, Part I
Autore Song Xiangyu
Edizione [1st ed.]
Pubbl/distr/stampa Singapore : , : Springer Singapore Pte. Limited, , 2024
Descrizione fisica 1 online resource (533 pages)
Altri autori (Persone) FengRuyi
ChenYunliang
LiJianxin
MinGeyong
Collana Lecture Notes in Computer Science Series
ISBN 981-9723-03-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- A BERT-Based Semantic Enhanced Model for COVID-19 Fake News Detection -- 1 Introduction -- 2 Related Work -- 2.1 COVID-19 Fake News Collection -- 2.2 COVID-19 Fake News Detection -- 2.3 BERT Model -- 3 Methodology -- 3.1 Dataset -- 3.2 Problem Statement -- 3.3 Text Representation Learning -- 3.4 Topic Generation -- 3.5 Classifier Design -- 4 Experimental Results and Parameter Analysis -- 4.1 Experimental Results -- 4.2 Parameter Analysis -- 5 Conclusion -- References -- Mining Frequent Geo-Subgraphs in a Knowledge Graph -- 1 Introduction -- 2 Problem Definition -- 3 Frequent Geo-Subgraph Mining -- 4 Optimizations -- 4.1 Arc Consistency Based Candidate Generation -- 4.2 Image Vertex Reusage -- 4.3 Geo-Grid Based Vertex Ordering -- 5 Experimental Study -- 5.1 Setup -- 5.2 Performance Evaluations -- 6 Related Work -- 7 Conclusion -- References -- Locality Sensitive Hashing for Data Placement to Optimize Parallel Subgraph Query Evaluation -- 1 Introduction -- 2 Background -- 2.1 Preliminaries -- 2.2 Parallel Execution Model -- 3 Locality Sensitive Hashing for Data Placement -- 3.1 Vertex Similarity -- 3.2 Vertex MinHash -- 4 System Implementation -- 5 Experiments -- 5.1 Experimental Setting -- 5.2 Effect of Our Proposed Techniques -- 5.3 Comparison with Other Parallel Subgraph Query Systems -- 5.4 Data Placement Performance -- 6 Related Work -- 7 Conclusion -- References -- DUTD: A Deeper Understanding of Trajectory Data for User Identity Linkage -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 4 Proposed Model -- 4.1 Grid Feature Extractor -- 4.2 Tranformer-Based Encoder -- 4.3 Matcher -- 5 Experiment -- 5.1 Datasets -- 5.2 Baselines -- 5.3 Parameter Setting and Evaluation Metrics -- 5.4 Performance Comparison -- 5.5 Ablation Study -- 6 Conclusion -- References.
Large-Scale Rank Aggregation from Multiple Data Sources Based D3MOPSO Method -- 1 Introduction -- 2 Related Work -- 3 Definitions and Problem Formulation -- 4 Proposed Method -- 4.1 Strategy on Encoding Scheme and Multi-directional Search -- 4.2 Particle Swarm Initialization -- 4.3 Definition of Discrete Position and Velocity -- 4.4 Discrete Particle Statue Updating -- 4.5 Framework of the Proposed Algorithm -- 4.6 Complexity Analysis -- 5 Experimental Studies -- 5.1 Comparison Algorithms -- 5.2 Experimental Settings -- 5.3 Evaluation Metrics -- 5.4 The Results -- 6 Conclusion -- References -- Hierarchically Delegatable and Revocable Access Control for Large-Scale IoT Devices with Tradability Based on Blockchain -- 1 Introduction -- 2 Building Blocks -- 2.1 Blockchain and Ethereum -- 2.2 Digital Signature -- 2.3 BIP-32 Standard -- 3 System Assumption and Requirements -- 3.1 System Entities -- 3.2 System Assumption -- 3.3 System Requirements -- 4 The Proposed Framework -- 4.1 High-Level Overview -- 4.2 IoT Device Registration -- 4.3 Ownership Transfer/Trading of IoT Device -- 4.4 (Hierarchical) Delegation of Access Control -- 4.5 Access an IoT Device -- 4.6 Revocation -- 5 Experimental Results -- 6 Security Analysis -- 7 Conclusions -- References -- Distributed Deep Learning for Big Remote Sensing Data Processing on Apache Spark: Geological Remote Sensing Interpretation as a Case Study -- 1 Introduction -- 2 Related Works -- 2.1 Distributed Deep Learning's Development Status -- 2.2 DDL-Based Remote Sensing Data Processing -- 3 Distributed Deep Learning Frameworks -- 3.1 MLlib -- 3.2 SparkTorch and TensorflowOnSpark -- 3.3 DeepLearning4Java -- 3.4 BigDL -- 3.5 Horovod -- 4 D-AMSDFNet: Distributed Deep Learning-Based AMSDFNet for Geological Remote Sensing Interpretation -- 4.1 AMSDFNet -- 4.2 Design of Distributed AMSDFNet -- 5 Experiments.
5.1 Settings -- 5.2 Analysis of Experimental Results -- 6 Conclusions -- References -- Graph-Enforced Neural Network for Attributed Graph Clustering -- 1 Introduction -- 2 Related Works -- 3 Notations and Problem Formulation -- 4 Degradation Analysis -- 4.1 Intra-cluster Estrangement -- 4.2 Attribute Similarity Neglection -- 4.3 Blurred Cluster Boundaries -- 5 The Proposed Method -- 5.1 Multi-task Learning Framework -- 5.2 High-Order Structural Proximity Enforcement -- 5.3 Attribute Similarity Enforcement -- 5.4 Cluster Boundary Enforcement -- 5.5 Joint Objective Optimization -- 6 Experiments -- 6.1 Experiment Settings -- 6.2 Performance Comparison -- 6.3 Efficiency Comparison -- 6.4 Ablation Study -- 6.5 Hyperparameter Sensitivity Analysis -- 7 Conclusion -- References -- MacGAN: A Moment-Actor-Critic Reinforcement Learning-Based Generative Adversarial Network for Molecular Generation -- 1 Introduction -- 2 Related Work -- 3 MacGAN Overview -- 3.1 GAN -- 3.2 Autoregressive GAN for SMILES Strings -- 3.3 Moment Reward -- 4 Experiment -- 4.1 Dataset -- 4.2 Evaluation Measures -- 4.3 Desired Chemical Properties -- 4.4 Model Setup -- 4.5 Experimental Results -- 5 Conclusion -- References -- Multi-modal Graph Convolutional Network for Knowledge Graph Entity Alignment -- 1 Introduction -- 2 Related Work -- 2.1 Entity Alignment -- 2.2 Multi-modal Knowledge Graph -- 3 Methodology -- 3.1 Definition and Model Overview -- 3.2 Multi-modal Pre-trained Embedding -- 3.3 Multi-modal Enhancement Embedding Mechanism -- 3.4 Objective -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Settings -- 4.3 Baselines -- 4.4 Main Results -- 4.5 Ablation Study -- 4.6 Parameter Analysis -- 5 Conclusion and Future Work -- References -- Subgraph Federated Learning with Global Graph Reconstruction -- 1 Introduction -- 2 Related Work -- 2.1 Subgraph Federated Learning (SFL).
2.2 Graph Structure Learning (GSL) -- 2.3 Split Learning -- 3 Problem Setting -- 4 Methodology -- 4.1 Framework Overview -- 4.2 Local Pre-training -- 4.3 The Local Graph Learning Module -- 4.4 The Global Graph Structure Learning Module -- 4.5 Objective and Training Procedure -- 5 Experiment -- 5.1 Experimental Setups -- 5.2 Comparison with State-of-the-art Methods (RQ1) -- 5.3 Ablation Study (RQ2) -- 5.4 Sensitivity Analysis (RQ3) -- 6 Conclusion -- References -- SEGCN: Structural Enhancement Graph Clustering Network -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Notations -- 3.2 Topology Enhancement Module -- 3.3 Improved Attention-Driven Graph Clustering Network with Global Structure Dynamic Fusion Module -- 3.4 Optimization Objective Function -- 4 Experiment -- 4.1 Benchmark Datasets -- 4.2 Experimental Setup and Evaluation -- 4.3 Clustering Results -- 4.4 Ablation Studies -- 4.5 Visualization Results -- 5 Conclusion -- References -- Designing a Knowledge Graph System for Digital Twin to Assess Urban Flood Risk -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 4 The Proposed UrbanFloodKG System -- 4.1 System Overview -- 4.2 Data Layer -- 4.3 Graph Layer -- 4.4 Algorithm Layer -- 4.5 Digital Twin Layer -- 5 Experiment and Discussion -- 5.1 Dataset and Environment -- 5.2 Link Prediction Analysis -- 5.3 Node Classification Analysis -- 6 Conclusion -- References -- TASML: Two-Stage Adaptive Semi-supervised Meta-learning for Few-Shot Learning -- 1 Introduction -- 2 Related Work -- 2.1 Brain-Inspired Model for Visual Object Recognition -- 2.2 Meta-learning for Few-Shot Learning -- 3 Methodology -- 3.1 Preliminary -- 3.2 The Two-Stage Semi-supervised Meta-learning Framework -- 3.3 Unsupervised Visual Representation Learning -- 3.4 Gradient-Based Meta-learning for Few-Shot Learning -- 3.5 Global Context-Aware Module -- 4 Experiments.
4.1 Few-Shot Image Classification -- 4.2 Ablation Study -- 4.3 Visualization -- 5 Conclusion -- References -- An Empirical Study of Attention Networks for Semantic Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Enrich Contextual Information Based Methods -- 2.2 Reduce Computation Complexity Based Methods -- 3 Experiment -- 3.1 Datasets -- 3.2 Implementation Details -- 4 Analysis -- 5 Conclusions and Future Works -- References -- Epidemic Source Identification Based on Infection Graph Learning -- 1 Introduction -- 2 Preliminaries -- 2.1 Problem Description -- 2.2 Propagation Model -- 3 Related Work -- 4 Our Model -- 4.1 Architecture -- 4.2 Input Generation -- 4.3 GCN Layer -- 4.4 Graph Embedding Layer -- 4.5 Output Layer -- 4.6 Loss Function -- 4.7 Model Complexity -- 5 Experiment -- 5.1 Datasets and Baselines -- 5.2 Evaluation Metrics -- 5.3 Experimental Setting -- 5.4 Source Identification Performance -- 5.5 Ablation Study -- 5.6 Impact of Parameters -- 5.7 Model Efficiency -- 6 Conclusion and Future Work -- References -- Joint Training Graph Neural Network for the Bidding Project Title Short Text Classification -- 1 Introduction -- 2 Related Work -- 2.1 Text Classification -- 2.2 Short Text Classification -- 3 Method -- 3.1 Extracting Contextual Information -- 3.2 Graph Structure Construction -- 3.3 Feature Caching and Replacement -- 3.4 Graph Convolution Operation -- 3.5 Classification -- 4 Experiment -- 4.1 Datasets -- 4.2 Data Processing -- 4.3 Baseline Models -- 4.4 Experimental Settings -- 4.5 Results -- 4.6 Parameter Analysis -- 5 Conclusion -- References -- Hierarchical Retrieval of Ancient Chinese Character Images Based on Region Saliency and Skeleton Matching -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Visual Feature Extraction -- 3.2 Regional Channel Screening -- 3.3 Saliency Joint Weighting Method.
3.4 Shape Fine Matching Based on Skeleton Context.
Record Nr. UNISA-996601561103316
Song Xiangyu  
Singapore : , : Springer Singapore Pte. Limited, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6-8, 2023, Proceedings, Part IV
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6-8, 2023, Proceedings, Part IV
Autore Song Xiangyu
Edizione [1st ed.]
Pubbl/distr/stampa Singapore : , : Springer Singapore Pte. Limited, , 2024
Descrizione fisica 1 online resource (539 pages)
Altri autori (Persone) FengRuyi
ChenYunliang
LiJianxin
MinGeyong
Collana Lecture Notes in Computer Science Series
ISBN 981-9724-21-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996601562003316
Song Xiangyu  
Singapore : , : Springer Singapore Pte. Limited, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6-8, 2023, Proceedings, Part I
Web and Big Data : 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6-8, 2023, Proceedings, Part I
Autore Song Xiangyu
Edizione [1st ed.]
Pubbl/distr/stampa Singapore : , : Springer Singapore Pte. Limited, , 2024
Descrizione fisica 1 online resource (533 pages)
Altri autori (Persone) FengRuyi
ChenYunliang
LiJianxin
MinGeyong
Collana Lecture Notes in Computer Science Series
ISBN 981-9723-03-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- A BERT-Based Semantic Enhanced Model for COVID-19 Fake News Detection -- 1 Introduction -- 2 Related Work -- 2.1 COVID-19 Fake News Collection -- 2.2 COVID-19 Fake News Detection -- 2.3 BERT Model -- 3 Methodology -- 3.1 Dataset -- 3.2 Problem Statement -- 3.3 Text Representation Learning -- 3.4 Topic Generation -- 3.5 Classifier Design -- 4 Experimental Results and Parameter Analysis -- 4.1 Experimental Results -- 4.2 Parameter Analysis -- 5 Conclusion -- References -- Mining Frequent Geo-Subgraphs in a Knowledge Graph -- 1 Introduction -- 2 Problem Definition -- 3 Frequent Geo-Subgraph Mining -- 4 Optimizations -- 4.1 Arc Consistency Based Candidate Generation -- 4.2 Image Vertex Reusage -- 4.3 Geo-Grid Based Vertex Ordering -- 5 Experimental Study -- 5.1 Setup -- 5.2 Performance Evaluations -- 6 Related Work -- 7 Conclusion -- References -- Locality Sensitive Hashing for Data Placement to Optimize Parallel Subgraph Query Evaluation -- 1 Introduction -- 2 Background -- 2.1 Preliminaries -- 2.2 Parallel Execution Model -- 3 Locality Sensitive Hashing for Data Placement -- 3.1 Vertex Similarity -- 3.2 Vertex MinHash -- 4 System Implementation -- 5 Experiments -- 5.1 Experimental Setting -- 5.2 Effect of Our Proposed Techniques -- 5.3 Comparison with Other Parallel Subgraph Query Systems -- 5.4 Data Placement Performance -- 6 Related Work -- 7 Conclusion -- References -- DUTD: A Deeper Understanding of Trajectory Data for User Identity Linkage -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 4 Proposed Model -- 4.1 Grid Feature Extractor -- 4.2 Tranformer-Based Encoder -- 4.3 Matcher -- 5 Experiment -- 5.1 Datasets -- 5.2 Baselines -- 5.3 Parameter Setting and Evaluation Metrics -- 5.4 Performance Comparison -- 5.5 Ablation Study -- 6 Conclusion -- References.
Large-Scale Rank Aggregation from Multiple Data Sources Based D3MOPSO Method -- 1 Introduction -- 2 Related Work -- 3 Definitions and Problem Formulation -- 4 Proposed Method -- 4.1 Strategy on Encoding Scheme and Multi-directional Search -- 4.2 Particle Swarm Initialization -- 4.3 Definition of Discrete Position and Velocity -- 4.4 Discrete Particle Statue Updating -- 4.5 Framework of the Proposed Algorithm -- 4.6 Complexity Analysis -- 5 Experimental Studies -- 5.1 Comparison Algorithms -- 5.2 Experimental Settings -- 5.3 Evaluation Metrics -- 5.4 The Results -- 6 Conclusion -- References -- Hierarchically Delegatable and Revocable Access Control for Large-Scale IoT Devices with Tradability Based on Blockchain -- 1 Introduction -- 2 Building Blocks -- 2.1 Blockchain and Ethereum -- 2.2 Digital Signature -- 2.3 BIP-32 Standard -- 3 System Assumption and Requirements -- 3.1 System Entities -- 3.2 System Assumption -- 3.3 System Requirements -- 4 The Proposed Framework -- 4.1 High-Level Overview -- 4.2 IoT Device Registration -- 4.3 Ownership Transfer/Trading of IoT Device -- 4.4 (Hierarchical) Delegation of Access Control -- 4.5 Access an IoT Device -- 4.6 Revocation -- 5 Experimental Results -- 6 Security Analysis -- 7 Conclusions -- References -- Distributed Deep Learning for Big Remote Sensing Data Processing on Apache Spark: Geological Remote Sensing Interpretation as a Case Study -- 1 Introduction -- 2 Related Works -- 2.1 Distributed Deep Learning's Development Status -- 2.2 DDL-Based Remote Sensing Data Processing -- 3 Distributed Deep Learning Frameworks -- 3.1 MLlib -- 3.2 SparkTorch and TensorflowOnSpark -- 3.3 DeepLearning4Java -- 3.4 BigDL -- 3.5 Horovod -- 4 D-AMSDFNet: Distributed Deep Learning-Based AMSDFNet for Geological Remote Sensing Interpretation -- 4.1 AMSDFNet -- 4.2 Design of Distributed AMSDFNet -- 5 Experiments.
5.1 Settings -- 5.2 Analysis of Experimental Results -- 6 Conclusions -- References -- Graph-Enforced Neural Network for Attributed Graph Clustering -- 1 Introduction -- 2 Related Works -- 3 Notations and Problem Formulation -- 4 Degradation Analysis -- 4.1 Intra-cluster Estrangement -- 4.2 Attribute Similarity Neglection -- 4.3 Blurred Cluster Boundaries -- 5 The Proposed Method -- 5.1 Multi-task Learning Framework -- 5.2 High-Order Structural Proximity Enforcement -- 5.3 Attribute Similarity Enforcement -- 5.4 Cluster Boundary Enforcement -- 5.5 Joint Objective Optimization -- 6 Experiments -- 6.1 Experiment Settings -- 6.2 Performance Comparison -- 6.3 Efficiency Comparison -- 6.4 Ablation Study -- 6.5 Hyperparameter Sensitivity Analysis -- 7 Conclusion -- References -- MacGAN: A Moment-Actor-Critic Reinforcement Learning-Based Generative Adversarial Network for Molecular Generation -- 1 Introduction -- 2 Related Work -- 3 MacGAN Overview -- 3.1 GAN -- 3.2 Autoregressive GAN for SMILES Strings -- 3.3 Moment Reward -- 4 Experiment -- 4.1 Dataset -- 4.2 Evaluation Measures -- 4.3 Desired Chemical Properties -- 4.4 Model Setup -- 4.5 Experimental Results -- 5 Conclusion -- References -- Multi-modal Graph Convolutional Network for Knowledge Graph Entity Alignment -- 1 Introduction -- 2 Related Work -- 2.1 Entity Alignment -- 2.2 Multi-modal Knowledge Graph -- 3 Methodology -- 3.1 Definition and Model Overview -- 3.2 Multi-modal Pre-trained Embedding -- 3.3 Multi-modal Enhancement Embedding Mechanism -- 3.4 Objective -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Settings -- 4.3 Baselines -- 4.4 Main Results -- 4.5 Ablation Study -- 4.6 Parameter Analysis -- 5 Conclusion and Future Work -- References -- Subgraph Federated Learning with Global Graph Reconstruction -- 1 Introduction -- 2 Related Work -- 2.1 Subgraph Federated Learning (SFL).
2.2 Graph Structure Learning (GSL) -- 2.3 Split Learning -- 3 Problem Setting -- 4 Methodology -- 4.1 Framework Overview -- 4.2 Local Pre-training -- 4.3 The Local Graph Learning Module -- 4.4 The Global Graph Structure Learning Module -- 4.5 Objective and Training Procedure -- 5 Experiment -- 5.1 Experimental Setups -- 5.2 Comparison with State-of-the-art Methods (RQ1) -- 5.3 Ablation Study (RQ2) -- 5.4 Sensitivity Analysis (RQ3) -- 6 Conclusion -- References -- SEGCN: Structural Enhancement Graph Clustering Network -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Notations -- 3.2 Topology Enhancement Module -- 3.3 Improved Attention-Driven Graph Clustering Network with Global Structure Dynamic Fusion Module -- 3.4 Optimization Objective Function -- 4 Experiment -- 4.1 Benchmark Datasets -- 4.2 Experimental Setup and Evaluation -- 4.3 Clustering Results -- 4.4 Ablation Studies -- 4.5 Visualization Results -- 5 Conclusion -- References -- Designing a Knowledge Graph System for Digital Twin to Assess Urban Flood Risk -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 4 The Proposed UrbanFloodKG System -- 4.1 System Overview -- 4.2 Data Layer -- 4.3 Graph Layer -- 4.4 Algorithm Layer -- 4.5 Digital Twin Layer -- 5 Experiment and Discussion -- 5.1 Dataset and Environment -- 5.2 Link Prediction Analysis -- 5.3 Node Classification Analysis -- 6 Conclusion -- References -- TASML: Two-Stage Adaptive Semi-supervised Meta-learning for Few-Shot Learning -- 1 Introduction -- 2 Related Work -- 2.1 Brain-Inspired Model for Visual Object Recognition -- 2.2 Meta-learning for Few-Shot Learning -- 3 Methodology -- 3.1 Preliminary -- 3.2 The Two-Stage Semi-supervised Meta-learning Framework -- 3.3 Unsupervised Visual Representation Learning -- 3.4 Gradient-Based Meta-learning for Few-Shot Learning -- 3.5 Global Context-Aware Module -- 4 Experiments.
4.1 Few-Shot Image Classification -- 4.2 Ablation Study -- 4.3 Visualization -- 5 Conclusion -- References -- An Empirical Study of Attention Networks for Semantic Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Enrich Contextual Information Based Methods -- 2.2 Reduce Computation Complexity Based Methods -- 3 Experiment -- 3.1 Datasets -- 3.2 Implementation Details -- 4 Analysis -- 5 Conclusions and Future Works -- References -- Epidemic Source Identification Based on Infection Graph Learning -- 1 Introduction -- 2 Preliminaries -- 2.1 Problem Description -- 2.2 Propagation Model -- 3 Related Work -- 4 Our Model -- 4.1 Architecture -- 4.2 Input Generation -- 4.3 GCN Layer -- 4.4 Graph Embedding Layer -- 4.5 Output Layer -- 4.6 Loss Function -- 4.7 Model Complexity -- 5 Experiment -- 5.1 Datasets and Baselines -- 5.2 Evaluation Metrics -- 5.3 Experimental Setting -- 5.4 Source Identification Performance -- 5.5 Ablation Study -- 5.6 Impact of Parameters -- 5.7 Model Efficiency -- 6 Conclusion and Future Work -- References -- Joint Training Graph Neural Network for the Bidding Project Title Short Text Classification -- 1 Introduction -- 2 Related Work -- 2.1 Text Classification -- 2.2 Short Text Classification -- 3 Method -- 3.1 Extracting Contextual Information -- 3.2 Graph Structure Construction -- 3.3 Feature Caching and Replacement -- 3.4 Graph Convolution Operation -- 3.5 Classification -- 4 Experiment -- 4.1 Datasets -- 4.2 Data Processing -- 4.3 Baseline Models -- 4.4 Experimental Settings -- 4.5 Results -- 4.6 Parameter Analysis -- 5 Conclusion -- References -- Hierarchical Retrieval of Ancient Chinese Character Images Based on Region Saliency and Skeleton Matching -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Visual Feature Extraction -- 3.2 Regional Channel Screening -- 3.3 Saliency Joint Weighting Method.
3.4 Shape Fine Matching Based on Skeleton Context.
Record Nr. UNINA-9910864179303321
Song Xiangyu  
Singapore : , : Springer Singapore Pte. Limited, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Web and big data, APWeb-WAIM 2020 international workshops : KGMA 2020, SemiBDMA 2020, DeepLUDA 2020, Tianjin, China, September 18-20, 2020, revised selected papers / / Qun Chen and Jianxin Li (eds)
Web and big data, APWeb-WAIM 2020 international workshops : KGMA 2020, SemiBDMA 2020, DeepLUDA 2020, Tianjin, China, September 18-20, 2020, revised selected papers / / Qun Chen and Jianxin Li (eds)
Pubbl/distr/stampa Gateway East, Singapore : , : Springer, , [2021]
Descrizione fisica 1 online resource (173 pages) : illustrations
Disciplina 004.22
Collana Communications in Computer and Information Science
Soggetto topico Application software
System design - Data processing
Artificial intelligence
ISBN 981-16-0479-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996464419003316
Gateway East, Singapore : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Web and big data, APWeb-WAIM 2020 international workshops : KGMA 2020, SemiBDMA 2020, DeepLUDA 2020, Tianjin, China, September 18-20, 2020, revised selected papers / / Qun Chen and Jianxin Li (eds)
Web and big data, APWeb-WAIM 2020 international workshops : KGMA 2020, SemiBDMA 2020, DeepLUDA 2020, Tianjin, China, September 18-20, 2020, revised selected papers / / Qun Chen and Jianxin Li (eds)
Pubbl/distr/stampa Gateway East, Singapore : , : Springer, , [2021]
Descrizione fisica 1 online resource (173 pages) : illustrations
Disciplina 004.22
Collana Communications in Computer and Information Science
Soggetto topico Application software
System design - Data processing
Artificial intelligence
ISBN 981-16-0479-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910484402003321
Gateway East, Singapore : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui