Ulteriori informazioni
This two-volume set, CCIS 1744 and CCIS 1745 book constitutes the 7th International Conference, on Data Mining and Big Data, DMBD 2022, held in Beijing, China, in November 21-24, 2022.
The 62 full papers presented in this two-volume set included in this book were carefully reviewed and selected from 135 submissions. The papers present the latest research on advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, etc.
Sommario
Deep Reinforcement Learning Approach.- Heterogeneous Multi-unit Control with Curriculum Learning for Multi-agent Reinforcement Learning.- A Deep Reinforcement Learning Approach for Cooperative Target Defense.- Particle Swarm Based Reinforcement Learning.- User's Permission Reasoning Method Based on Knowledge Graph Reward Guidance Reinforcement Learning in Data Center. - SMPG: Adaptive Soft Update for Masked MADDPG.- Attentive Relational State Representation for Intelligent Joint Operation Simulation.- Graph Neural Networks.- Flow Prediction via Multi-view Spatial-temporal Graph Neural Network.- RotatSAGE: A Scalable Knowledge Graph Embedding Model based on Translation Assumptions and Graph Neural Networks.- Denoise Network Structure for User Alignment across Networks via Graph Structure Learning.- OLPGP: An optimized label propagation-based distributed graph partitioning algorithm.- Deep Neural Networks.- DRGS: Low-Precision Full Quantization of Deep Neural Network with Dynamic Rounding and Gradient Scaling for Object Detection.- Emotion Recognition Based on Multi-scale Convolutional Neural Network.- Pose Sequence Model Using the Encoder-decoder Structure for 3d Pose Estimation.- Research and Analysis of Video-Based Human Pose Estimation.- Action Recognition for Solo-militant Based on ResNet and Rule Matching.- Multiple Residual Quantization of Pruning.- Clustering Methods.- Deep Structured Graph Clustering Network.- Improved Clustering Strategies for Learning Style Identification in Massive Open Online Courses.- CSHEM - A Compressed Sensing Based Secure Data Processing Method for Electrical Data.- Prediction Methods.- An Improved Multi-Source Spatiotemporal Data Fusion Model based on the Nearest Neighbor Grids for PM2.5 Concentration Interpolation and Prediction.- Study on the Prediction of Rice Noodle Raw Material Index Content by Deep Feature Fusion.- GAP: Goal-Aware Prediction with Hierarchical Interactive Representation for Vehicle Trajectory.- Multi-Cause Learning for Diagnosis Prediction.- Prediction of Postoperative Survival Level of Esophageal Cancer Patients Based on Kaplan-Meier(K-M) Survival Analysis and Gray Wolf Optimization (GWO)-BP Model.- Classification Methods.- Possibilistic Reject-Classification based on Contrastive Learning in Vector Quantization Networks.- A Classification Method for Imbalanced Data Based on Ant Lion Optimizer.- Learnable Relation With Triplet Formulation For Semi-supervised Medical Image Classification.- Multi-view Classification via Twin Projection Vector Machine with Application to EEG-based Driving Fatigue Detection.- An Interpretable Conditional Augmentation Classification Approach for Imbalanced EHRs MortalityPrediction.- Combining Statistical and Semantic Features For Trajectory Point Classification.- Identification and Recognition Methods.- Complementary Convolutional Restricted Boltzmann Machine and Its Applications in Image Recognition.- Text-independent Speaker Identification Using a Single-scale SincNet-DCGAN Model.- Genome-wide Feature Selection of Robust mRNA Biomarkers for Body Fluid Identification.- HOS-YOLOv5: An Improved High-precision Remote Sensing Image Target Detection Algorithm Based on YOLOv5.- A Multi-Module 3D U-Net Learning Architecture for Brain Tumor Segmentation.- Problems with Regression-line in Data-mining Applications and A Better Alternate Linear-model.- Research on Hot Spot Mining Technology for Network Public Opinion.- Research Hotspots, Emerging Trend and Front of Fraud Detection Rearch: A Scientometric Analysis (1984 - 2021).- Optimization Metho
