| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910855375403321 |
|
|
Autore |
Song Xiangyu |
|
|
Titolo |
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 |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2024.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (536 pages) |
|
|
|
|
|
|
Collana |
|
Lecture Notes in Computer Science, , 1611-3349 ; ; 14332 |
|
|
|
|
|
|
Altri autori (Persone) |
|
FengRuyi |
ChenYunliang |
LiJianxin |
MinGeyong |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
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 |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
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. |
|
|
|
|
|
|
Sommario/riassunto |
|
The 4-volume set LNCS 14331, 14332, 14333, and 14334 constitutes the refereed proceedings of the 7th International Joint Conference, APWeb-WAIM 2023, which took place in Wuhan, China, in October 2023. The total of 138 papers included in the proceedings were carefully reviewed and selected from 434 submissions. They focus on innovative ideas, original research findings, case study results, and experienced insights in the areas of the World Wide Web and big data, covering Web technologies, database systems, information management, software engineering, knowledge graph, recommend system and big data. |
|
|
|
|
|
|
|
| |