Contextual Word Embeddings Clustering through Multiway Analysis: A Comparative Study -- Transferable Deep Metric Learning for Clustering -- Spatial Graph Convolution Neural Networks for Water Distribution Systems -- Data-Centric Perspective on Explainability versus Performance Trade-off -- Towards Data Science Design Patterns -- Diverse Paraphrasing with Insertion Models for Few-Shot Intent Detection -- LEMON: Alternative Sampling for More Faithful Explanation through Local Surrogate Models -- GASTeN: Generative Adversarial Stress Test Networks -- Learning Permutation-Invariant Embeddings for Description Logic Concepts -- Diffusion Transport Alignment -- Mind the Gap: Measuring Generalization Performance Across Multiple Objectives -- Effects of Locality and Rule Language on Explanations for Knowledge Graph Embeddings -- Shapley Values with Uncertain Value Functions. -Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors -- On the Change of Decision Boundary and Loss in Learning with Concept Drift -- AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, A Framework based on Active Learning and Transfer Learning -- Explanations for Itemset Mining by Constraint Programming: A Case Study using ChEMBL data -- Translated Texts Under the Lens: From Machine Translation Detection to Source Language Identification -- Geolet: An Interpretable Model for Trajectory Classification -- An investigation of structures responsible for gender bias in BERT and DistilBERT -- Discovering diverse top-k characteristic lists -- Online Influence Forest for Streaming Anomaly Detection -- APs: a proxemic framework for social media interactions modeling and analysis -- User Authentication via Multifaceted Mouse Movementsand Outlier Exposure -- Explaining Black Box Reinforcement Learning Agents Through Counterfactual Policies -- A GNN-based Architecture for Group Detection from spatio-temporal Trajectory Data -- Discovering Rule Lists with Preferred Variables -- Don't Start Your Data Labeling from Scratch: OpSaLa - Optimized Data Sampling Before Labeling -- The Other Side of Compression: Measuring Bias in Pruned Transformers -- Dropping incomplete records is (not so) straightforward -- Meta-Learning for Automated Selection of Anomaly Detectors for Semi-Supervised Datasets -- Should We Consider On-Demand Analysis in Scale-Free Networks? -- ROCKAD: Transferring ROCKET to whole time series anomaly detection -- Out-of-Distribution Generalisation with Symmetry-Based Disentangled Representations -- Forecasting Electricity Prices: an Optimize then Predict-based approach -- A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data -- QBERT: Generalist Model for Processing Questions -- On Compositionality in Data Embedding.

This book constitutes the proceedings of the 21st International Symposium on Intelligent Data Analysis, IDA 2022, which was held in Louvain-la-Neuve, Belgium, during April 12-14, 2023. The 38 papers included in this book were carefully reviewed and selected from 91 submissions. IDA is an international symposium presenting advances in the intelligent analysis of data. Distinguishing characteristics of IDA are its focus on novel, inspiring ideas, its focus on research, and its relatively small scale. .