Social Media and Recommendation
Granular Emotion Detection in Social Media Using Multi-Discipline Ensembles
Sentiment Polarity and Emotion Detection from Tweets Using Distant Supervision and Deep Learning Models
Disruptive Event Identification in Online Social Network
Modeling Polarization on Social Media Posts: A Heuristic Approach Using Media Bias
Sarcasm detection in Tunisian social media comments: Case of COVID-19
Multimodal Deep Learning and Fast Retrieval for Recommendation
Natural Language Processing
Mining news articles dealing with Food Security
Identification of Paragraph Regularities in Legal Judgements through Clustering and Textual Embedding
Aspect term extraction improvement based on a hybrid method
Exploring the Impact of Gender Bias Mitigation Approaches on a Downstream Classification Task
A semi-automatic data generator for Query Answering
Explainability,
XAI to explore robustness of features in adversarial training for cybersecurity
Impact of Feedback Type on Explanatory Interactive Learning
Learning and Explanation of Extreme Multi-Label Deep Classification Models for Media Content
An Interpretable Machine Learning Approach to Prioritizing Factors Contributing to Clinician Burnout
A general-purpose method for applying Explainable AI for Anomaly Detection
More Sanity Checks for Saliency Maps
Intelligent Systems
Deep Reinforcement Learning for Automated Stock Trading: Inclusion of Short Selling
Scaling Posterior Distributions over Differently-Curated Datasets: A Bayesian-Neural-Networks Methodology
Ensembling Sparse Autoencoders for Network Covert Channel Detection in IoT Ecosystems
Towards Automation of Pollen Monitoring: Image-Based Tree Pollen Recognition
Rough Sets for Intelligence on Embedded Systems
Context as a Distance Function in ConSQL
Classification and Clustering
Detecting Anomalies with LatentOut: Novel Scores, Architectures, and Settings
Richness Fallacy
Adapting loss functions to learning progress improves accuracy of classification in neural networks
Multiscale and multivariate time series clustering: A new approach
Improve Calibration Robustness of Temperature Scaling by Penalizing Output Entropy
Understanding Negative Calibration from Entropy Perspective
A New Clustering Preserving Transformation for $k$-Means Algorithm Output
Complex Data
A Transformer-Based Framework for Geomagnetic Activity Prediction
AS-SIM: an approach to Action-State Process Model Discovery
Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery
Temporal Graph-based CNNs (TG-CNNs) for Online Course Dropout Prediction
Graph Convolutional Networks Using Node Addition and Edge Reweighting
Audio Super-Resolution via Vision Transformer
Similarity embedded temporal Transformers: Enhancing stock predictions with historically similar trends
Investigating noise interference on speech towards applying the Lombard effect automatically
Medical Applications
Towards Polynomial Adaptive Local Explanations for Healthcare Classifiers
Towards Tailored Intervention in Medicine Using Patients' Segmentation
Application of association rules to classify IBD patients
Unsupervised Learning Based Rule Generating System with Temporal Features Extractions Tuned for Tinnitus Retraining Therapy
Industrial Applications
TrueDetective 4.0: a Big data architetture for real time anomaly detection
Optimising the Machine Translation Workflow: Analysis, Development, Benchmarking, Testing and Maintenance
Classification vs Recommendation methods for Therapeutics Recommendation
Document Layout Analysis with Variational Autoencoders : an Industrial Application.