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 | ||
|
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 | ||
|
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 | ||
|
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 | ||
|
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 | ||
|
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 | ||
|
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 | ||
|
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 | ||
|
Web and Big Data. APWeb-WAIM 2023 International Workshops : KGMA 2023 and SemiBDMA 2023, Wuhan, China, October 6-8, 2023, Proceedings |
Autore | Song Xiangyu |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
Descrizione fisica | 1 online resource (95 pages) |
Altri autori (Persone) |
FengRuyi
ChenYunliang LiJianxin MinGeyong |
Collana | Communications in Computer and Information Science Series |
ISBN | 981-9729-91-2 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910857794403321 |
Song Xiangyu | ||
Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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