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Big Data and Social Computing : 9th China National Conference, BDSC 2024, Harbin, China, August 8–10, 2024, Proceedings / / edited by Xiaofeng Meng, Zhidong Cao, Suran Wu, Yang Chen, Xiu-Xiu Zhan
| Big Data and Social Computing : 9th China National Conference, BDSC 2024, Harbin, China, August 8–10, 2024, Proceedings / / edited by Xiaofeng Meng, Zhidong Cao, Suran Wu, Yang Chen, Xiu-Xiu Zhan |
| Autore | Meng Xiaofeng |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (486 pages) |
| Disciplina | 004.6 |
| Altri autori (Persone) |
CaoZhidong
WuSuran ChenYang ZhanXiu-Xiu |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer networks
Image processing - Digital techniques Computer vision Application software Computer Communication Networks Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications |
| ISBN | 981-9758-03-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Digital Society and Public Security -- Early Warning Methods Based on a Real Time Series Dataset: a Comparative Study -- EG-ConMix: An Intrusion Detection Method based on Graph Contrastive Learning -- Network Analysis Reveals Regional Disparity in COVID-19 Policymaking -- Exploring Urban Spatio-temporal Patterns via Large-scale Vehicle Travel Data : The Role of Geographical Attributes and Traveler Characteristics -- Mapping Gridded Wealth Index Using Open Geospatial Data in Zambia -- Bidirectional Multi-grain Graph Convolution Network for Origin-Destination Demand Prediction -- Modelling and Simulation of Social Systems -- The Prospects of Multi-modal Pre-training Models in Epidemic Forecasting -- Deep Reinforcement Learning Based Dynamic Bus Timetable Scheduling with Bidirectional Constraints -- Modeling Knowledge Spillover Effects in High Speed Rail Development: A Discrete Simulation Approach Using Cellular Automata -- Educators' Networking Interacts with Digital Competence Heterogeneity to Enhance the Implementation of AIEd: A Mixed‐Methods Study -- Intelligent Fatigue Driving Detection Method Based on Fusion of Smartphone and Smartwatch Data -- SCPM-R+ER: A R+ER-based Algorithm for Mining Spatial Co-location Patterns -- Internet Intelligent Algorithm Governance -- Extracting Spatial High Utility Co-location Patterns Based on Fuzzy Feature Clusters -- Incremental Network Traffic Category Models Based on Hybrid Learning Strategies -- Modeling the BGP Prefix Hijack via Pollution and Recovery Processes -- A Weakly Supervised Method for Encrypted Traffic Classification in the Dark Web -- Rumor Detection Based on Conflict and Bot Features -- Social Network and Group Behavior -- A Study of Digital Nomad Culture and Local Social Practices -- Based on Fieldwork Research in a Certain Area of Southwest China -- Analysis of the Relationship Between Temperature and Insomnia Based on Social Media Text -- Do Gender Role Attitudes Affect Fertility Intentions ? — Evidence from International Data -- Dynamic Shifts: The Rise of Unicorns in the AI Ecosystem -- Measurement and Analysis of China's Fashion Events on Social Media: A Study of Shanghai Fashion Week -- Innovation, Risks, and Network Security of Large Language Models -- Enhanced Product Embedding with Sememe for Product Search -- FOKE: A Personalized and Explainable Education Framework Integrating Foundation Models, Knowledge Graphs, and Prompt Engineering -- Improving the Adversarial Transferability of Radio Signal with Denoising, Data Diversity, and Gradient Average.-Artificial Intelligence and Cognitive Science -- Temporal Knowledge Graph Reasoning: A Review -- The Impact of AI Trust Violation on Trustworthiness: An Empirical Study Based on AI Chatbots -- An Epileptic EEG Classification Approach with Spike Train Encoding Using Spiking Neural Networks. |
| Record Nr. | UNINA-9910878986203321 |
Meng Xiaofeng
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big Data and Social Computing [[electronic resource] ] : 8th China National Conference, BDSC 2023, Urumqi, China, July 15–17, 2023, Proceedings / / edited by Xiaofeng Meng, Yang Chen, Liming Suo, Qi Xuan, Zi-Ke Zhang
| Big Data and Social Computing [[electronic resource] ] : 8th China National Conference, BDSC 2023, Urumqi, China, July 15–17, 2023, Proceedings / / edited by Xiaofeng Meng, Yang Chen, Liming Suo, Qi Xuan, Zi-Ke Zhang |
| Autore | Meng Xiaofeng |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (412 pages) |
| Disciplina |
621.39
004.6 |
| Altri autori (Persone) |
ChenYang
SuoLiming XuanQi ZhangZi-Ke |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer engineering
Computer networks Computer systems Image processing—Digital techniques Computer vision Application software Computer Engineering and Networks Computer System Implementation Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications |
| ISBN | 981-9939-25-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Digital Technology and Sustainable Development -- A Power Consumption Forecasting Method Based on Knowledge Embedding Under the Influence of the COVID-19 Pandemic -- An efficient regional co-location pattern mining algorithm over extended objects based on neighborhood distribution relation computation -- Research on Multi-objective Optimization Algorithm for Coal Blending -- Social Network and Group Behavior -- Research on the Public Value of Government Social Media Content and Communication Strategies under “Infodemic” -- Location Recommendations Based on Multi-view Learning and Attention-enhanced Graph Networks -- Driving Style Classification and Dynamic Recognition Considering Traffic State -- Who Connects Wikipedia? A Deep Analysis of Node Roles and Connection Patterns in Wikilink Network -- Digital infrastructure and the Intelligent Society -- Social Behavior-Aware Driving Intention Detection using Spatio-Temporal Attention Network -- Intelligent Government Decision-Making: A Multidimensional Policy Text Visualization Analysis System -- Heuristic Approach to Curate Disease Taxonomy Beyond Nosology-based Standards -- Root Cause Localization Method of Base Station Cells with Poor Quality using AI+SHAP -- Digital Society and Public Security Does Internet Use Promote the Garbage Classification Behavior of Farmers? -- Empirical Evidence from Rural China -- Traffic State Propagation Prediction based on SAE-LSTM-SAD under the SCATS -- Citation Prediction via Influence Representation using Temporal Graphs -- Enhancing Time Series Anomaly Detection with Graph Learning Techniques -- Image Dehazing based on CycleGAN with an Enhanced Generator and a Multiscale Discriminator -- Artificial Intelligence and Cognitive Science -- Accurate and Rapid Localization of Tea Bud Leaf Picking Point based on YOLOv8 -- Compressor Fault Diagnosis Based on Graph Attention Network -- Conductance-Threshold Dual Adaptive Spiking Neural Networks for Speech Recognition -- Mitigating Backdoor Attacks Using Prediction of Model Update Trends -- The Motor Fault Diagnosis Based On Current Signal With Graph Attention Network -- Internet Intelligent Algorithm Governance -- NILSIC-BERT4Rec: Sequential Recommendation with Non-Invasive and Interest Capturing Self-Attention Mechanism -- Rethinking the Robustness of Graph Neural Networks -- MDC: An Interpretable GNNs Method Based on Node Motif Degree and Graph Diffusion Convolution -- Missing data imputation for traffic flow data using SAE-GAN-SAD -- Scaffold Data Augmentation for Molecular Property Prediction. . |
| Record Nr. | UNISA-996546837703316 |
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Meng Xiaofeng
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Big Data and Social Computing : 8th China National Conference, BDSC 2023, Urumqi, China, July 15–17, 2023, Proceedings / / edited by Xiaofeng Meng, Yang Chen, Liming Suo, Qi Xuan, Zi-Ke Zhang
| Big Data and Social Computing : 8th China National Conference, BDSC 2023, Urumqi, China, July 15–17, 2023, Proceedings / / edited by Xiaofeng Meng, Yang Chen, Liming Suo, Qi Xuan, Zi-Ke Zhang |
| Autore | Meng Xiaofeng |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (412 pages) |
| Disciplina |
621.39
004.6 |
| Altri autori (Persone) |
ChenYang
SuoLiming XuanQi ZhangZi-Ke |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer engineering
Computer networks Computer systems Image processing—Digital techniques Computer vision Application software Computer Engineering and Networks Computer System Implementation Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications |
| ISBN | 981-9939-25-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Digital Technology and Sustainable Development -- A Power Consumption Forecasting Method Based on Knowledge Embedding Under the Influence of the COVID-19 Pandemic -- An efficient regional co-location pattern mining algorithm over extended objects based on neighborhood distribution relation computation -- Research on Multi-objective Optimization Algorithm for Coal Blending -- Social Network and Group Behavior -- Research on the Public Value of Government Social Media Content and Communication Strategies under “Infodemic” -- Location Recommendations Based on Multi-view Learning and Attention-enhanced Graph Networks -- Driving Style Classification and Dynamic Recognition Considering Traffic State -- Who Connects Wikipedia? A Deep Analysis of Node Roles and Connection Patterns in Wikilink Network -- Digital infrastructure and the Intelligent Society -- Social Behavior-Aware Driving Intention Detection using Spatio-Temporal Attention Network -- Intelligent Government Decision-Making: A Multidimensional Policy Text Visualization Analysis System -- Heuristic Approach to Curate Disease Taxonomy Beyond Nosology-based Standards -- Root Cause Localization Method of Base Station Cells with Poor Quality using AI+SHAP -- Digital Society and Public Security Does Internet Use Promote the Garbage Classification Behavior of Farmers? -- Empirical Evidence from Rural China -- Traffic State Propagation Prediction based on SAE-LSTM-SAD under the SCATS -- Citation Prediction via Influence Representation using Temporal Graphs -- Enhancing Time Series Anomaly Detection with Graph Learning Techniques -- Image Dehazing based on CycleGAN with an Enhanced Generator and a Multiscale Discriminator -- Artificial Intelligence and Cognitive Science -- Accurate and Rapid Localization of Tea Bud Leaf Picking Point based on YOLOv8 -- Compressor Fault Diagnosis Based on Graph Attention Network -- Conductance-Threshold Dual Adaptive Spiking Neural Networks for Speech Recognition -- Mitigating Backdoor Attacks Using Prediction of Model Update Trends -- The Motor Fault Diagnosis Based On Current Signal With Graph Attention Network -- Internet Intelligent Algorithm Governance -- NILSIC-BERT4Rec: Sequential Recommendation with Non-Invasive and Interest Capturing Self-Attention Mechanism -- Rethinking the Robustness of Graph Neural Networks -- MDC: An Interpretable GNNs Method Based on Node Motif Degree and Graph Diffusion Convolution -- Missing data imputation for traffic flow data using SAE-GAN-SAD -- Scaffold Data Augmentation for Molecular Property Prediction. . |
| Record Nr. | UNINA-9910744506003321 |
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Meng Xiaofeng
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Moving Objects Management : Models, Techniques and Applications / / by Xiaofeng Meng, Zhiming Ding, Jiajie Xu
| Moving Objects Management : Models, Techniques and Applications / / by Xiaofeng Meng, Zhiming Ding, Jiajie Xu |
| Autore | Meng Xiaofeng |
| Edizione | [2nd ed. 2014.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 V. ; ; 26 cm |
| Disciplina | 621.3845/6 |
| Soggetto topico |
Database management
Transportation Geographical information systems Regional planning Urban planning Electrical engineering Database Management Geographical Information Systems/Cartography Landscape/Regional and Urban Planning Communications Engineering, Networks |
| ISBN | 3-642-38276-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Moving Objects Modeling -- Moving Objects Tracking -- Moving Objects Indexing -- Moving Objects Basic Querying -- Moving Objects Advanced Querying -- Trajectory Prediction of Moving Objects -- Uncertainty Management in Moving Objects Database -- Statistical Analysis on Moving Object Trajectories -- Clustering Analysis of Moving Objects -- Dynamic Transportation Navigation -- Location Privacy. |
| Record Nr. | UNINA-9910298571003321 |
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Meng Xiaofeng
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| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Spatial Data and Intelligence : 5th China Conference, SpatialDI 2024, Nanjing, China, April 25-27, 2024, Proceedings
| Spatial Data and Intelligence : 5th China Conference, SpatialDI 2024, Nanjing, China, April 25-27, 2024, Proceedings |
| Autore | Meng Xiaofeng |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (364 pages) |
| Altri autori (Persone) |
ZhangXueying
GuoDanhuai HuDi ZhengBolong ZhangChunju |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 981-9729-66-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Spatiotemporal Data Analysis -- Multi-view Contrastive Clustering with Clustering Guidance and Adaptive Auto-encoders -- 1 Introduction -- 2 Related Work -- 2.1 Multi-view Clustering -- 2.2 Contrastive Learning -- 3 The Framework of MAAC Network -- 3.1 Adaptive Graph Auto-encoder -- 3.2 Contrastive Fusion -- 3.3 Graph Clustering -- 3.4 Clustering Guidance Strategy -- 4 Experiments -- 4.1 Datasets and Evaluation Measure -- 4.2 Implementation Details -- 4.3 Baselines -- 4.4 Results -- 4.5 Ablation Experiment -- 4.6 Cluster Visualization -- 5 Conclusion -- References -- Cloud-Edge Collaborative Continual Adaptation for ITS Object Detection -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 Definition -- 3.2 Problem Statement -- 4 The Framework for Continual Adaptation in Traffic Object Detection Based on Cloud-Edge Collaboration -- 4.1 Cloud Component: Dynamic Domain Adaptation -- 4.2 Edge Component: Efficient Model Synchronization -- 5 Experiments -- 5.1 Datasets -- 5.2 Experimental Settings -- 5.3 Methods for Comparison -- 5.4 Experimental Results -- 6 Conclusion -- References -- Understanding Spatial Dependency Among Spatial Interactions -- 1 Introduction -- 2 Methodological Framework -- 2.1 Spatial Dependency Metrics for Spatial Interactions -- 2.2 Factors Influencing Second-Order Spatial Autocorrelation -- 2.3 Spatial Econometric Interaction Modeling -- 3 Experiments and Results -- 3.1 Research Area and Data -- 3.2 Measuring Spatial Dependency Among Spatial Interactions -- 3.3 Exploring Factors Influencing Second-Order Spatial Autocorrelation -- 3.4 Modeling Spatial Interactions Incorporating Spatial Dependency -- 4 Conclusions -- References -- An Improved DBSCAN Clustering Method for AIS Trajectories Incorporating DP Compression and Discrete Fréchet Distance -- 1 Introduction.
2 Related Works -- 3 Methodology -- 3.1 Framework of the Research -- 3.2 Trajectory Data Pre-processing -- 3.3 Computation of Distance Matrix -- 3.4 Unsupervised KNN + Kneed -- 4 Experiments -- 4.1 Dataset and Experimental Environment -- 4.2 Data Pre-processing -- 4.3 Comparison of Similarity Measures -- 4.4 Description of Clusters -- 5 Conclusions -- References -- Structure and Semantic Contrastive Learning for Nodes Clustering in Heterogeneous Information Networks -- 1 Introduction -- 2 Related Work -- 3 The Proposed Method -- 3.1 Adjacency Matrix Reconstruction -- 3.2 Cleaning Feature -- 3.3 Contrastive Learning -- 3.4 Objective Function -- 4 Experiments -- 4.1 Datasets and Baselines -- 4.2 Comparison Methods -- 4.3 Ablation Experiments -- 4.4 Parameter Analysis -- 5 Conclusion -- References -- An Accuracy Evaluation Method for Multi-source Data Based on Hexagonal Global Discrete Grids -- 1 Introductory -- 2 Multi-source Data Grids -- 2.1 Selection of Grid Levels -- 2.2 Gridded Representation of Vector Data -- 2.3 Gridded Representation of Remotely Sensed Data -- 3 Accuracy Evaluation System for Gridded Data -- 3.1 Accuracy Evaluation Index System for Vector Data Gridding -- 3.2 Accuracy Evaluation Index System of Remote Sensing Data Gridding -- 4 Experimental Results and Analysis -- 4.1 Conversion Results and Uncertainty Assessment of Remotely Sensed Data -- 4.2 Transformation and Uncertainty Assessment of Vector Data -- 5 Summarize -- References -- Applying Segment Anything Model to Ground-Based Video Surveillance for Identifying Aquatic Plant -- 1 Introduction -- 2 Methodology -- 2.1 Overview -- 2.2 Detection and Segmentation -- 2.3 Area Estimation -- 3 Study Area and Data -- 4 Experiment -- 4.1 Computational Environment -- 4.2 Detection and Segmentation -- 4.3 Area Estimation -- 5 Conclusion -- References -- Spatiotemporal Data Mining. Mining Regional High Utility Co-location Pattern -- 1 Introduction -- 2 Related Work -- 3 Related Concepts and Problem Statement -- 4 Algorithm -- 5 Experiments -- 5.1 Analysis of Mining Results -- 5.2 Efficiency Analysis -- 6 Conclusion -- References -- Local Co-location Pattern Mining Based on Regional Embedding -- 1 Introduction -- 2 Related Works -- 3 Basic Concepts -- 4 Mining Framework -- 4.1 Regional Embedding -- 4.2 Region Functional Annotation -- 4.3 Mining Semantic LCPs -- 4.4 Algorithm Analysis -- 5 Experimental Evaluation -- 5.1 Description of Datasets -- 5.2 Region Partitioning and Function Annotation Based on Regional Embedding -- 5.3 Case Study of Semantic LCP Mining -- 6 Conclusion -- References -- RCPMRLM: A Regional Co-location Pattern Mining Method Based on Representation Learning Model -- 1 Introduction -- 2 Related Concepts -- 2.1 Regional Co-location Patterns Mining -- 2.2 Word Embeddings Representation Model -- 2.3 Similarity Measurement -- 2.4 Clustering Method -- 3 Study Area and Data -- 4 Regional Co-location Pattern Mining Method Based on Representation Learning Model (RCPMRLM) -- 5 Algorithm Complexity Analysis -- 6 Results -- 6.1 Clustering Results -- 6.2 RCPMRLM Mining Results -- 7 Summary -- References -- Construction of a Large-Scale Maritime Elements Semantic Schema Based on Heterogeneous Graph Models -- 1 Introduction -- 2 Related Work -- 2.1 Overview of Related Work on Knowledge Graphs -- 2.2 Overview of Related Work on Ship Behavior Mining -- 3 Technical Framework and Dataset -- 3.1 Technical Framework -- 3.2 Dataset -- 3.3 Introduction to Application Scenarios of the Framework -- 4 Experimental Results and Analysis -- 4.1 Ship Type Prediction -- 4.2 Similar Berth Recommendation -- 5 Conclusion and Future Work -- References. OCGATL: One-Class Graph Attention Networks with Transformation Learning for Anomaly Detection for Argo Data -- 1 Introduction -- 2 Related Work -- 2.1 Graph Anomaly Detection -- 2.2 One-Class Classification -- 2.3 Contrastive Learning -- 3 Preliminaries -- 4 Methodology -- 4.1 Graph Construction -- 4.2 OCGATL Model -- 5 Experiments -- 5.1 Simulation -- 5.2 Argo Real Data Experiment -- 6 Conclusion -- References -- RGCNdist2vec: Using Graph Convolutional Networks and Distance2Vector to Estimate Shortest Path Distance Along Road Networks -- 1 Introduction -- 2 Related Work -- 2.1 Shortest Path Distance Calculation -- 2.2 Graph Neural Network -- 3 Definitions and Solutions -- 3.1 Definition -- 3.2 Solution -- 4 Road Network Shortest Path Estimation Method -- 4.1 RGCNdist2vec -- 4.2 RGCNdist2vec-Encoder -- 4.3 RGCNdist2vec-Decoder -- 5 Sampling Method -- 5.1 Subgraph Sampling Method -- 5.2 Sampling Method Between Subgraphs -- 5.3 Whole Graph Sampling Method -- 6 Experiment -- 6.1 Experimental Introduction -- 6.2 Ablation Experiment -- 6.3 Effect Experiment -- 6.4 Efficiency Experiment -- 7 Conclusion -- References -- Self-supervised Graph Neural Network Based Community Search over Heterogeneous Information Networks -- 1 Introduction -- 2 Related Work -- 3 Community Search Model and Algorithm over HIN -- 3.1 Node Attribute Score Calculation -- 3.2 Community Search -- 4 Experiments -- 4.1 Experiment Settings -- 4.2 Effectiveness Evaluation -- 4.3 Ablation Study -- 4.4 Community Sensitivity Analysis -- 5 Conclusion -- References -- Measurement and Research on the Conflict Between Residential Space and Tourism Space in Pianyan Ancient Township -- 1 Introduction -- 2 Overview of the Study Area and Data Sources -- 2.1 Overview of the Study Area -- 2.2 Data Sources -- 3 Multi-intelligence Body Simulation -- 3.1 Environmental Information Module. 3.2 Implementation Module -- 3.3 Information Storage Module -- 3.4 Module for Analyzing Simulation Results -- 4 System Implementation and Simulation Experiments -- 4.1 Spatial Form of the Ancient Town of Pianyan -- 4.2 Spatial Conflict Identification -- 4.3 Optimization Strategies -- 5 Conclusion -- References -- Spatiotemporal Data Prediction -- Spatio-Temporal Sequence Prediction of Diversion Tunnel Based on Machine Learning Multivariate Data Fusion -- 1 Introduction -- 2 Methodology -- 2.1 ARIMA Model -- 2.2 Order of ARIMA Model -- 2.3 The LSSVM Model -- 2.4 The DLSSVM Model -- 2.5 DLSSVM Kernel Function -- 2.6 ARIMA-Bi-DLSSVM Modeling -- 3 Real Experiment for Monitoring Data -- 3.1 Monitoring Data -- 3.2 Data Processing -- 4 Results and Analysis -- 4.1 Prediction Effect of ARIMA-b-DLSSVM -- 4.2 Comparison of Prediction Effect of Several Models -- 5 Conclusion -- References -- DyAdapTransformer: Dynamic Adaptive Spatial-Temporal Graph Transformer for Traffic Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Transformer-Based Traffic Forecasting -- 2.2 Adaptive GNN-Based Traffic Forecasting -- 3 Preliminaries -- 3.1 Definitions -- 3.2 Problem Formulation -- 4 The Proposed Model -- 5 S-TPE: Spatial-Temporal Position Embedding -- 5.1 Temporal Position Embedding (TPE) -- 5.2 Spatial Position Embedding (SPE) Based on Random Walk -- 6 DASCL: Dynamic Adaptive Spatial-Temporal Correlations Learning -- 6.1 Encoder -- 6.2 Decoder -- 7 Experimental Analysis -- 7.1 Datasets -- 7.2 Baseline Methods -- 7.3 Experimental Settings -- 7.4 Experimental Results and Analysis -- 7.5 Interpretability Analysis -- 8 Conclusion -- References -- Predicting Future Spatio-Temporal States Using a Robust Causal Graph Attention Model -- 1 Introduction -- 2 Preliminaries -- 3 Methodology -- 3.1 Forward Propagation of the CGATM -- 3.2 Optimization of the CGATM. 4 Experimental Results and Analysis. |
| Record Nr. | UNINA-9910855382803321 |
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Meng Xiaofeng
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| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Spatial Data and Intelligence : 5th China Conference, SpatialDI 2024, Nanjing, China, April 25-27, 2024, Proceedings
| Spatial Data and Intelligence : 5th China Conference, SpatialDI 2024, Nanjing, China, April 25-27, 2024, Proceedings |
| Autore | Meng Xiaofeng |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (364 pages) |
| Altri autori (Persone) |
ZhangXueying
GuoDanhuai HuDi ZhengBolong ZhangChunju |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 981-9729-66-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Spatiotemporal Data Analysis -- Multi-view Contrastive Clustering with Clustering Guidance and Adaptive Auto-encoders -- 1 Introduction -- 2 Related Work -- 2.1 Multi-view Clustering -- 2.2 Contrastive Learning -- 3 The Framework of MAAC Network -- 3.1 Adaptive Graph Auto-encoder -- 3.2 Contrastive Fusion -- 3.3 Graph Clustering -- 3.4 Clustering Guidance Strategy -- 4 Experiments -- 4.1 Datasets and Evaluation Measure -- 4.2 Implementation Details -- 4.3 Baselines -- 4.4 Results -- 4.5 Ablation Experiment -- 4.6 Cluster Visualization -- 5 Conclusion -- References -- Cloud-Edge Collaborative Continual Adaptation for ITS Object Detection -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 Definition -- 3.2 Problem Statement -- 4 The Framework for Continual Adaptation in Traffic Object Detection Based on Cloud-Edge Collaboration -- 4.1 Cloud Component: Dynamic Domain Adaptation -- 4.2 Edge Component: Efficient Model Synchronization -- 5 Experiments -- 5.1 Datasets -- 5.2 Experimental Settings -- 5.3 Methods for Comparison -- 5.4 Experimental Results -- 6 Conclusion -- References -- Understanding Spatial Dependency Among Spatial Interactions -- 1 Introduction -- 2 Methodological Framework -- 2.1 Spatial Dependency Metrics for Spatial Interactions -- 2.2 Factors Influencing Second-Order Spatial Autocorrelation -- 2.3 Spatial Econometric Interaction Modeling -- 3 Experiments and Results -- 3.1 Research Area and Data -- 3.2 Measuring Spatial Dependency Among Spatial Interactions -- 3.3 Exploring Factors Influencing Second-Order Spatial Autocorrelation -- 3.4 Modeling Spatial Interactions Incorporating Spatial Dependency -- 4 Conclusions -- References -- An Improved DBSCAN Clustering Method for AIS Trajectories Incorporating DP Compression and Discrete Fréchet Distance -- 1 Introduction.
2 Related Works -- 3 Methodology -- 3.1 Framework of the Research -- 3.2 Trajectory Data Pre-processing -- 3.3 Computation of Distance Matrix -- 3.4 Unsupervised KNN + Kneed -- 4 Experiments -- 4.1 Dataset and Experimental Environment -- 4.2 Data Pre-processing -- 4.3 Comparison of Similarity Measures -- 4.4 Description of Clusters -- 5 Conclusions -- References -- Structure and Semantic Contrastive Learning for Nodes Clustering in Heterogeneous Information Networks -- 1 Introduction -- 2 Related Work -- 3 The Proposed Method -- 3.1 Adjacency Matrix Reconstruction -- 3.2 Cleaning Feature -- 3.3 Contrastive Learning -- 3.4 Objective Function -- 4 Experiments -- 4.1 Datasets and Baselines -- 4.2 Comparison Methods -- 4.3 Ablation Experiments -- 4.4 Parameter Analysis -- 5 Conclusion -- References -- An Accuracy Evaluation Method for Multi-source Data Based on Hexagonal Global Discrete Grids -- 1 Introductory -- 2 Multi-source Data Grids -- 2.1 Selection of Grid Levels -- 2.2 Gridded Representation of Vector Data -- 2.3 Gridded Representation of Remotely Sensed Data -- 3 Accuracy Evaluation System for Gridded Data -- 3.1 Accuracy Evaluation Index System for Vector Data Gridding -- 3.2 Accuracy Evaluation Index System of Remote Sensing Data Gridding -- 4 Experimental Results and Analysis -- 4.1 Conversion Results and Uncertainty Assessment of Remotely Sensed Data -- 4.2 Transformation and Uncertainty Assessment of Vector Data -- 5 Summarize -- References -- Applying Segment Anything Model to Ground-Based Video Surveillance for Identifying Aquatic Plant -- 1 Introduction -- 2 Methodology -- 2.1 Overview -- 2.2 Detection and Segmentation -- 2.3 Area Estimation -- 3 Study Area and Data -- 4 Experiment -- 4.1 Computational Environment -- 4.2 Detection and Segmentation -- 4.3 Area Estimation -- 5 Conclusion -- References -- Spatiotemporal Data Mining. Mining Regional High Utility Co-location Pattern -- 1 Introduction -- 2 Related Work -- 3 Related Concepts and Problem Statement -- 4 Algorithm -- 5 Experiments -- 5.1 Analysis of Mining Results -- 5.2 Efficiency Analysis -- 6 Conclusion -- References -- Local Co-location Pattern Mining Based on Regional Embedding -- 1 Introduction -- 2 Related Works -- 3 Basic Concepts -- 4 Mining Framework -- 4.1 Regional Embedding -- 4.2 Region Functional Annotation -- 4.3 Mining Semantic LCPs -- 4.4 Algorithm Analysis -- 5 Experimental Evaluation -- 5.1 Description of Datasets -- 5.2 Region Partitioning and Function Annotation Based on Regional Embedding -- 5.3 Case Study of Semantic LCP Mining -- 6 Conclusion -- References -- RCPMRLM: A Regional Co-location Pattern Mining Method Based on Representation Learning Model -- 1 Introduction -- 2 Related Concepts -- 2.1 Regional Co-location Patterns Mining -- 2.2 Word Embeddings Representation Model -- 2.3 Similarity Measurement -- 2.4 Clustering Method -- 3 Study Area and Data -- 4 Regional Co-location Pattern Mining Method Based on Representation Learning Model (RCPMRLM) -- 5 Algorithm Complexity Analysis -- 6 Results -- 6.1 Clustering Results -- 6.2 RCPMRLM Mining Results -- 7 Summary -- References -- Construction of a Large-Scale Maritime Elements Semantic Schema Based on Heterogeneous Graph Models -- 1 Introduction -- 2 Related Work -- 2.1 Overview of Related Work on Knowledge Graphs -- 2.2 Overview of Related Work on Ship Behavior Mining -- 3 Technical Framework and Dataset -- 3.1 Technical Framework -- 3.2 Dataset -- 3.3 Introduction to Application Scenarios of the Framework -- 4 Experimental Results and Analysis -- 4.1 Ship Type Prediction -- 4.2 Similar Berth Recommendation -- 5 Conclusion and Future Work -- References. OCGATL: One-Class Graph Attention Networks with Transformation Learning for Anomaly Detection for Argo Data -- 1 Introduction -- 2 Related Work -- 2.1 Graph Anomaly Detection -- 2.2 One-Class Classification -- 2.3 Contrastive Learning -- 3 Preliminaries -- 4 Methodology -- 4.1 Graph Construction -- 4.2 OCGATL Model -- 5 Experiments -- 5.1 Simulation -- 5.2 Argo Real Data Experiment -- 6 Conclusion -- References -- RGCNdist2vec: Using Graph Convolutional Networks and Distance2Vector to Estimate Shortest Path Distance Along Road Networks -- 1 Introduction -- 2 Related Work -- 2.1 Shortest Path Distance Calculation -- 2.2 Graph Neural Network -- 3 Definitions and Solutions -- 3.1 Definition -- 3.2 Solution -- 4 Road Network Shortest Path Estimation Method -- 4.1 RGCNdist2vec -- 4.2 RGCNdist2vec-Encoder -- 4.3 RGCNdist2vec-Decoder -- 5 Sampling Method -- 5.1 Subgraph Sampling Method -- 5.2 Sampling Method Between Subgraphs -- 5.3 Whole Graph Sampling Method -- 6 Experiment -- 6.1 Experimental Introduction -- 6.2 Ablation Experiment -- 6.3 Effect Experiment -- 6.4 Efficiency Experiment -- 7 Conclusion -- References -- Self-supervised Graph Neural Network Based Community Search over Heterogeneous Information Networks -- 1 Introduction -- 2 Related Work -- 3 Community Search Model and Algorithm over HIN -- 3.1 Node Attribute Score Calculation -- 3.2 Community Search -- 4 Experiments -- 4.1 Experiment Settings -- 4.2 Effectiveness Evaluation -- 4.3 Ablation Study -- 4.4 Community Sensitivity Analysis -- 5 Conclusion -- References -- Measurement and Research on the Conflict Between Residential Space and Tourism Space in Pianyan Ancient Township -- 1 Introduction -- 2 Overview of the Study Area and Data Sources -- 2.1 Overview of the Study Area -- 2.2 Data Sources -- 3 Multi-intelligence Body Simulation -- 3.1 Environmental Information Module. 3.2 Implementation Module -- 3.3 Information Storage Module -- 3.4 Module for Analyzing Simulation Results -- 4 System Implementation and Simulation Experiments -- 4.1 Spatial Form of the Ancient Town of Pianyan -- 4.2 Spatial Conflict Identification -- 4.3 Optimization Strategies -- 5 Conclusion -- References -- Spatiotemporal Data Prediction -- Spatio-Temporal Sequence Prediction of Diversion Tunnel Based on Machine Learning Multivariate Data Fusion -- 1 Introduction -- 2 Methodology -- 2.1 ARIMA Model -- 2.2 Order of ARIMA Model -- 2.3 The LSSVM Model -- 2.4 The DLSSVM Model -- 2.5 DLSSVM Kernel Function -- 2.6 ARIMA-Bi-DLSSVM Modeling -- 3 Real Experiment for Monitoring Data -- 3.1 Monitoring Data -- 3.2 Data Processing -- 4 Results and Analysis -- 4.1 Prediction Effect of ARIMA-b-DLSSVM -- 4.2 Comparison of Prediction Effect of Several Models -- 5 Conclusion -- References -- DyAdapTransformer: Dynamic Adaptive Spatial-Temporal Graph Transformer for Traffic Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Transformer-Based Traffic Forecasting -- 2.2 Adaptive GNN-Based Traffic Forecasting -- 3 Preliminaries -- 3.1 Definitions -- 3.2 Problem Formulation -- 4 The Proposed Model -- 5 S-TPE: Spatial-Temporal Position Embedding -- 5.1 Temporal Position Embedding (TPE) -- 5.2 Spatial Position Embedding (SPE) Based on Random Walk -- 6 DASCL: Dynamic Adaptive Spatial-Temporal Correlations Learning -- 6.1 Encoder -- 6.2 Decoder -- 7 Experimental Analysis -- 7.1 Datasets -- 7.2 Baseline Methods -- 7.3 Experimental Settings -- 7.4 Experimental Results and Analysis -- 7.5 Interpretability Analysis -- 8 Conclusion -- References -- Predicting Future Spatio-Temporal States Using a Robust Causal Graph Attention Model -- 1 Introduction -- 2 Preliminaries -- 3 Methodology -- 3.1 Forward Propagation of the CGATM -- 3.2 Optimization of the CGATM. 4 Experimental Results and Analysis. |
| Record Nr. | UNISA-996594168003316 |
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Meng Xiaofeng
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| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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