Advanced Data Mining and Applications

Time Series.- An Adaptive Data-Driven Imputation Model for Incomplete Event Series.- From Time Series to Multi-Modality: Classifying Multivariate Time Series via Both 1D and 2D Representations.- Exploring the Effectiveness of Positional Embedding on Transformer-based Architectures for Multivariate Time Series Classification.- Modeling of Repeated Measures for Time-to-Event Prediction.- A Method for Identifying the Timeliness of Manufacturing Data Based on Weighted Timeliness Graph.- STAD: Multivariate Time Series Anomaly Detection Based on Spatio-temporal Relationship.- Recommendation I.- Refined Node Type Graph Convolutional Network for Recommendation.- Multi-level Noise Filtering and Preference Propagation Enhanced Knowledge Graph Recommendation.- Enhancing Knowledge-aware Recommendation with Contrastive Learning.- Knowledge-Rich Influence Propagation Recommendation Algorithm Based on Graph Attention Networks.- A Novel Variational Autoencoder with Multi-Position Latent Self-Attention and Actor-Critic for Recommendation.- Fair Re-ranking Recommendation Based on Debiased Multi-Graph Representations.- Information Extraction.- FastNER: Speeding Up Inferences for Named Entity Recognition Tasks.- CPMFA: A Character Pair-Based Method for Chinese Nested Named Entity Recognition.- STMC-GCN: A Span Tagging Multi-Channel Graph Convolutional Network for Aspect Sentiment Triplet Extraction.- Exploring the Design Space of Unsupervised Blocking with Pre-trained Language Models in Entity Resolution.- Joint Modeling of Local and Global Semantics for Contrastive Entity Disambiguation.- Fine-grained Review Analysis using BERT with Attention: A Categorical and Rating-based Approach.- Emotional Analysis.- Discovery of Emotion Implicit Causes in Products based on Commonsense Reasoning.- Multi-modal Multi-emotion Emotional Support Conversation.- Exploiting Pseudo Future Contexts for Emotion Recognition in Conversations.- Generating Enlightened Suggestions based on Mental State Evolution for Emotional Support Conversation.- Deep One-Class Fine-Tuning for Imbalanced Short Text Classification in Transfer Learning.- EmoKnow: Emotion- and Knowledge-oriented Model for COVID-19 Fake News Detection.- Popular Songs: The Sentiment Surrounding the Conversation.- Market Sentiment Analysis based on Social Media and Trading Volume for Asset Price Movement Prediction.- Data Mining.- Efficient mining of high utility co-location patterns based on a query strategy.- Point-level Label-free Segmentation Framework for 3D Point Cloud Semantic Mining.- CD-BNN: Causal Discovery with Bayesian Neural Network.- A Preference-based Indicator Selection Hyper-heuristic for Optimization Problems.- An Elastic Scalable Grouping for Stateful Operators in Stream Computing Systems.- Incremental natural gradient boosting for probabilistic regression.- Discovering Skyline Periodic Itemset Patterns in Transaction Sequences.- Double-optimized CS-BP Anomaly Prediction for Control Operation Data.- Bridging the Interpretability Gap in Coupled Neural Dynamical Models.- Multidimensional Adaptative kNN Over Tracking Outliers (Makoto).- Traffic.- MANet: An End-to-End Multiple Attention Network for Extracting Roads around EHV Transmission Lines from High-Resolution Remote Sensing Images.- Deep Reinforcement Learning for Solving the Trip Planning Query.- MDCN: Multi-Scale Dilated Convolutional Enhanced Residual Network for Traffic Sign Detection.- Identifying Critical Congested Roads based on Traffic Flow-Aware Road Network Embedding.- A Cross-Region-based Framework for Supporting Car-Sharing.- Attention-based Spatial-Temporal Graph Convolutional Recurrent Networks for Traffic Forecasting.- Transformer Based Driving Behavior Safety Prediction For New Energy Vehicles.- Graph Convolution Recurrent Denoising Diffusion Model for Multivariate Probabilistic Temporal Forecasting.- A Bottom-Up Sampling Strategy for Reconstructing Geospatial Data from Ultra Sparse Inputs.- Recommendation II.- Feature Representation Enhancing by Context Sensitive Information in CTR Prediction.- ProtoMix: Learnable Data Augmentation on Few-shot Features with Vector Quantization in CTR Prediction.- When Alignment Makes a Difference: A Content-Based Variational Model for Cold-Start CTR Prediction.- Dual-Ganularity Contrastive Learning for Session-based Recommendation.- Efficient Graph Collaborative Filtering with Multi-layer Output-enhanced Contrastive Learning.- Influence Maximization with Tag Revisited: Exploiting the Bi-Submodularity of the Tag-Based Influence Function.- Multi-Interest Aware Graph Convolution Network for Social Recommendation.- Enhancing MultimediaRecommendation through Item-Item Semantic Denoising and Global Preference Awareness.- Resident-based Store Recommendation Model for Community Commercial Planning.c