Big data
Toward Explainable Recommendation Via Counterfactual Reasoning
Online Volume Optimization for Notifications via Long Short-Term Value Modeling
Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases
Financial data
Joint Latent Topic Discovery and Expectation Modeling for Financial Markets
Let the model make financial senses: a Text2Text generative approach for financial complaint identification
Information retrieval and search
Web-scale Semantic Product Search With Large Language Models
Multi-task learning based Keywords weighted Siamese Model for semantic retrieval
Relation-Aware Network with Attention-Based Loss for Few-Shot Knowledge Graph Completion
MFBE: Leveraging Multi-Field Information of FAQs for Efficient Dense Retrieval
Isotropic Representation Can Improve Dense Retrieval
Knowledge-Enhanced Prototypical Network with Structural Semantics for Few-Shot Relation Classification
Internet of Things
MIDFA : Memory-Based Instance Division and Feature Aggregation Network for Video Object Detection
Medical and biological data
Vision Transformers for Small Histological Datasets learned through Knowledge Distillation
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis
DKFM: Dual Knowledge-guided Fusion Model for Drug Recommendation
Hierarchical Graph Neural Network for Patient Treatment Preference Prediction with External Knowledge
Multimedia and multimodal data
An Extended Variational Mode Decomposition Algorithm Developed Speech Emotion Recognition Performance
Dynamically-Scaled Deep Canonical Correlation Analysis
TCR: Short Video Title Generation and Cover Selection with Attention Refinement
ItrievalKD: An Iterative Retrieval Framework Assisted with Knowledge Distillation for Noisy Text-to-Image Retrieval
Recommender systems
Semantic Relation Transfer for Non-overlapped Cross-domain Recommendations
Interest Driven Graph Structure Learning for Session-Based Recommendation
Multi-behavior Guided Temporal Graph Attention Network for Recommendation
Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation
Meta-learning Enhanced Next POI Recommendation by Leveraging Check-ins from Auxiliary Cities
Global-Aware External Attention Deep Model for Sequential Recommendation
Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-aware Reranking
Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation
kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval
Staying or Leaving: A Knowledge-Enhanced User Simulator for Reinforcement Learning Based Short Video Recommendation
RLMixer: A Reinforcement Learning Approach For Integrated Ranking With Contrastive User Preference Modeling.