.- Recommender System. .- Hierarchical Review-based Recommendation with Contrastive Collaboration. .- Adaptive Augmentation and Neighbor Contrastive Learning for Multi-Behavior Recommendation. .- Automated Modeling of Influence Diversity with Graph Convolutional Network for Social Recommendation. .- Contrastive Generator Generative Adversarial Networks for Sequential Recommendation. .- Distribution-aware Diversification for Personalized Re-ranking in Recommendation. .- KMIC: A Knowledge-aware Recommendation with Multivariate Intentions Contrastive Learning. .- Logic Preference Fusion Reasoning on Recommendation. .- MHGNN: Hybrid Graph Neural Network with Mixers for Multi-interest Session-aware Recommendation. .- Mixed Augmentation Contrastive Learning for Graph Recommendation System. .- Noise-Resistant Graph Neural Networks for Session-based Recommendation. .- S2DNMF: A Self-supervised Deep Nonnegative Matrix Factorization Recommendation Model Incorporating Deep Latent Features of Network Structure. .- Self-Filtering Residual Attention Network based on Multipair Information Fusion for Session-Based Recommendations. .- TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback. .- VM-Rec: A Variational Mapping Approach for Cold-start User Recommendation. .- Knowledge Graph. .- Matching Tabular Data to Knowledge Graph based on Multi-level Scoring Filters for Table Entity Disambiguation. .- Complex Knowledge Base Question Answering via Structure and Content Dual-driven Method. .- EvoREG: Evolutional Modeling with Relation-Entity Dual-Guidance for Temporal Knowledge Graph Reasoning. .- Federated Knowledge Graph Embedding Unlearning via Diffusion Model. .- Functional Knowledge Graph Towards Knowledge Application and Data Management for General Users. .- Hospital Outpatient Guidance System Based On Knowledge Graph. .- TOP: Taxi Destination Prediction Based on Trajectory Knowledge Graph. .- Type-based Neighborhood Aggregation for Knowledge Graph Alignment. .- An Aggregation Procedure Enhanced Mechanism for GCN-based Knowledge Graph Completion Model by Leveraging Condensed Sampling and Attention Optimization. .- Spatial and Temporal Data. .- Capturing Fine and Coarse Grained User Preferences with Dual-Transformer for Next POI Recommendation. .- Enhancing Spatio-Temporal Semantics with Contrastive Learning for Next POI Recommendation. .- Distinguish the Indistinguishable: Spatial Personalized Transformer for Traffic Flow Forecast. .- Meeting Pattern Detection from Trajectories in Road Network. .- Speed Prediction of Multiple Traffic Scenarios with Local Fluctuation. .- ST-TPFL: Towards Spatio-Temporal Traffic Flow Prediction Based on Topology Protected Federated Learning. .- A Context-aware Distance Analysis Approach for Time Series. .- Dual-view Stack State Learning Network for Attribute-based Container Location Assignment. .- Efficient Coverage Query over Transition Trajectories.