Collaborative Computing: Networking, Applications and Worksharing

Recommendation System.- A Negative Sampling-based Service Recommendation Method.- Knowledge Graph Enhanced Web API Recommendation via Neighbor Information Propagation for Multi service Application Development.- Expertise-oriented Explainable Question Routing.- An API Recommendation Method based on Beneficial Interaction.- A flow prediction model of bike-sharing based on cycling context.- Federated Learning and application.- FedFR: Evaluation and Selection of Loss Functions for Federated Face Recognition.- FedCL: An Efficient Federated Unsupervised Learning for Model Sharing in IoT.- Edge Federated Learning for Social Profit Optimality: A Cooperative Game Approach.- MetaEM: Meta Embedding Mapping for Federated Cross-Domain Recommendation to Cold-Start Users.- A Reliable Service Function Chain Orchestration Method Based on Federated Reinforcement Learning.- EdgeComputing and Collaborative working.- A Context-aware Approach to Scheduling of Multi-Data- Source Tasks in Mobile Edge Computing.- Secure and Private Coding for Edge Computing against Cooperative Attack with Low Communication Cost and Computational Load.- Availability-Constrained Application Deployment in Hybrid Cloud-Edge Collaborative Environment.- EBA: An Adaptive Large Neighborhood Search-based Approach for Edge Bandwidth Allocation.- System Completion Time Minimization with Edge Server Onboard Unmanned Vehicle.- An approach to the synchronization of dynamic complex network combining degree distribution and eigenvector criteria.- An Energy-Saving Strategy for 5G Base Stations in Vehicular Edge Computing.- An efficient scheduling strategy for containers based on Kubernetes.- NOMA-Based Task Offloading and Allocation in Vehicular Edge Computing Networks.- A Collaborative Graph