Advances in Knowledge Discovery and Data Mining

Chapter 1 FR $$^3$$ 3 LS: A Forecasting Model with Robust and Reduced Redundancy Latent Series

Chapter 2 Knowledge-Infused Optimization for Parameter Selection in Numerical Simulations

Chapter 4 A Weighted Cross-Modal Feature Aggregation Network for Rumor Detection

Chapter 5 Quantifying Opinion Rejection: A Method to Detect Social Media Echo Chambers

Chapter 6 KiProL: A Knowledge-Injected Prompt Learning Framework for Language Generation

Chapter 7 GViG: Generative Visual Grounding Using Prompt-Based Language Modeling for Visual Question Answering

Chapter 8 Aspect-Based Fake News Detection

Chapter 9 DQAC: Detoxifying Query Auto-completion with Adapters

Chapter 10 Graph Neural Network Approach to Semantic Type Detection in Tables

Chapter 11 TCGNN: Text-Clustering Graph Neural Networks for Fake News Detection on Social Media

Chapter 12 Exploiting Adaptive Contextual Masking for Aspect-Based Sentiment Analysis

Chapter 13 An Automated Approach for Generating Conceptual Riddles

Chapter 14 DiffFind : Discovering Differential Equations from Time Series

Chapter 15 DEAL: Data-Efficient Active Learning for Regression Under Drift

Chapter 16 Evolving Super Graph Neural Networks for Large-Scale Time-Series Forecasting

Chapter 17 Unlearnable Examples for Time Series

Chapter 18 Learning Disentangled Task-Related Representation for Time Series

Chapter 19 A Multi-view Feature Construction and Multi-Encoder-Decoder Transformer Architecture for Time Series Classification

Chapter 20 Kernel Representation Learning with Dynamic Regime Discovery for Time Series Forecasting

Chapter 21 Hyperparameter Tuning MLP’s for Probabilistic Time Series Forecasting

Chapter 22 Efficient and Accurate Similarity-Aware Graph Neural Network for Semi-supervised Time Series Classification

Chapter 23 STLGRU: Spatio-Temporal Lightweight Graph GRU for Traffic Flow Prediction