Computer Supported Cooperative Work and Social Computing : 20th CCF Conference, ChineseCSCW 2025, Guangzhou, China, November 7-9, 2025, Revised Selected Papers, Part II (Communications in Computer and Information Science)

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Computer Supported Cooperative Work and Social Computing : 20th CCF Conference, ChineseCSCW 2025, Guangzhou, China, November 7-9, 2025, Revised Selected Papers, Part II (Communications in Computer and Information Science)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 384 p.
  • 言語 ENG
  • 商品コード 9789819202874

Full Description

The two-volume set CCIS 2910 + 2911 constitutes the refereed proceedings of the 20th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2025, held in Guangzhou, China, in November 2025.

The 50 full papers and 13 short papers presented in the proceedings were carefully reviewed and selected from 196 submissions.These papers were organized in topical sections as follows:

Part I: CSCW and Social Computing and Human-Machine-Things Fusion and Human-AI Collaborative Computing.

Part II: Crowd Cooperative Computing and Evolutionary Computation and Collaborative Data, Software and Services.

Contents

.- Topic C: Crowd Cooperative Computing and Evolutionary Computation
.- Intelligent Collaborative Vessel Scheduling for Inland Waterway Intersections Based on Improved Multi-Agent Deep Reinforcement Learning.
.- Multi-Agent Task Allocation and Path Planning for Sustainable Synchronous Collaboration.
.- Collaborative Learning Group Formation Considering Cognition-Emotion Coevolution.
.- E-Motorcycle Multi-Task Assignment Method Based on E-CARGO and Deep Learning-Driven Bearing Health Assessment.
.- Dual Graph Representation Learning.
.- A Joint Resource Security Allocation Scheme with Collaborative Interference and UAV AssistanceA Joint Resource Security Allocation Scheme with Collaborative Interference and UAV Assistance.
.- An Angular Quantization-Guided Evolutionary Framework for Feature Selection in High-Dimensional Imbalanced Classification.
.- Optimizing Task Allocation Under Cold-Start Conditions: A Reputation-Based Approach for Complex Crowdsourcing.
.- ACRO-NEEP: A Hierarchical Cooperative Optimization Framework for Symbolic Regression.
.- NoiseMap: Visual Analytics for Interpreting Noise Scheduling Strategies in Diffusion Models for Multivariate Time Series Forecasting.
.- Topic D: Collaborative Data, Software and Services
.- SHindex: A Two-Tier Distributed Index for Road-Network Trajectory Data.
.- Adaptive Cognitive Evolution for Dynamic Knowledge Tracing with Time-Aware Temporal Representation.
.- Beamforming for Reconfigurable Intelligence Surface Assisted Collaborative System of Communication and Sensing.
.- Short Video Rumor Detection Method Integrating Multimodal Information.
.- Semantic Planning Meets Structural Retrieval: Knowledge Graph Subgraph Retrieval Collaboration for Robust LLM Reasoning.
.- CGSDP: Attention-Based Defect Prediction Combining Source Code Semantic and Directed Class Dependency Network.
.- An Emoticon-aware Autoencoder Method for Face Replacement in Images from Videos.
.- Trajectory Similarity Detection Based on Graph Contrastive Learning.
.- LLM-driven Multi-Agent Simulation for Teaching Dynamics and Peer Effects.
.- Automatic Feature Interaction Learning via Attention-free Neural Networks.
.- Identifying Collaborative Enterprise Communities in Multi-Chain Industrial Networks via Incomplete Multi-View Clustering.
.- Family-Aware Graph Neural Networks with Loss Function Optimization for Android Malware Classification.
.- Automatic Construction of Multi-Layer Knowledge Graphs with Large Language Models.
.- Data Poisoning Attack with Diffusion Model for QoS-aware Cloud API Recommender System.
.- Frequency-Enhanced and Query-Aware for Temporal Knowledge Graph Reasoning.
.- Chorus: Mitigating GPU Fragmentation in LLM Serving by Unifying Prefill-Decode Disaggregation and Aggregation.
.- Deadline- and Reliability-Constrained Workflow Scheduling in GDCs.
.- MLIF: Multi-Aspect Label Information Fusion for Effective ICD Coding in Long-Tail Scenarios.

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