Knowledge Science, Engineering and Management

16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part II

AvZhi Jin,Yuncheng Jiang

Häftad, Engelska, 2023

Del 14118 i serien Lecture Notes in Computer Science

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Beskrivning

This volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16–18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management.

Produktinformation

Utgivningsdatum:2023-08-10
Mått:155 x 235 x 27 mm
Vikt:733 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:461
Förlag:Springer International Publishing AG
ISBN:9783031402852

Utforska kategorier

Innehållsförteckning

Knowledge Engineering Research and Applications.- Knowing before Seeing: Incorporating Post-Retrieval Information into Pre-Retrieval Query Intention Classification.- LSRN: Live-Streaming Identification Based on Reasoning Network with Core Traffic Set.- Implicit Offensive Speech Detection Based on Multi-feature Fusion.- SIE-YOLOv5: Improved YOLOv5 for Small Object Detection in Drone-Captured-Scenarios.- Learning-based Dichotomy Graph Sketch for Summarizing Graph Streams with High Accuracy.- SNAFA-Net: Squared Normalization Attention and Feature Alignment for Visible-Infrared Person Re-identification.- A comparative study of chatbot response generation: traditional approaches versus large language models.- Investigating the Impact of Product Contours on User Perception of Product Attributes.- Conf-UNet: A model for speculation on unknown Oracle Bone Characters.- An Efficient One-Shot Network and Robust Data Associations in Multi-Pedestrian Tracking.- Sampling Spatial-Temporal Attention Network for Traffic Forecasting.- ST-MAN: Spatio-Temporal Multimodal Attention Network for Traffic Prediction.- Sparse-view CT Reconstruction via Implicit Neural Intensity Functions.- Tennis action recognition based on multi-branch mixed attention.- Cascade Sampling via Dual Uncertainty for Active Entity Alignment.- Template Shift and Background Suppression for Visual Object Tracking.- Reversible Data Hiding in Encrypted Images Based on A Multi-Granularity Adaptive Classification Mechanism.- Enhanced Entity Interaction Modeling for Multi-modal Entity Alignment.- Monte Carlo Medical Volume Rendering Denoising via Auxiliary Feature Guided Self-Attention and Convolution Integrated.- View Distribution Alignment with Progressive Adversarial Learning for UAV Visual Geo-Localization.- HBay: Predicting Human Mobility via Hyperspherical Bayesian Learning.- Spatial-Temporal Diffusion Probabilistic Learning for Crime Prediction.- DBA: An Efficient Approach to Boost Transfer-based Adversarial Attack Performance through Information Deletion.- A Graph Partitioning Algorithm Based on Graph Structure and Label Propagation for Citation Network Prediction.- Hybrid Heterogeneous Graph Neural Networks for Fund Performance Prediction.- WGCN: A Novel Wavelet Graph Neural Network for Metro Ridership Prediction.- GMiRec: A Multi-image Visual Recommendation Model based on a Gated Neural Network.- Semi-supervised entity alignment via noisy student-based self training.- Modeling Chinese Ancient Book Catalog.- JOINT EXTRACTION OF NESTED ENTITIES AND RELATIONS BASED ON MULTI-TASK LEARNING.- A Grasping System with Structured Light 3D Machine Vision Guided Strategy Optimization.- A Cognitive Knowledge Enriched Joint Framework for Social Emotion and Cause Mining.- TKSP: Long-term Stance Prediction for Social Media Users by Fusing Time Series Features and Event Dynamic Evolution Knowledge.- A Cross-Document Coreference Resolution Approach to Low-Resource Languages.- Network Flow Based IoT Anomaly Detection Using Graph Neural Network.- Disentangled Multi-factor Graph Neural Network for Non-coding RNA-drug Resistance Association Prediction.