Research Track -- Measuring Content Preservation in Textual Style Transfer -- A Temperature-Modified Dynamic Embedded Topic Model -- Measuring Difficulty of Learning using Ensembles Methods -- Graph Embeddings for Non-IID Data Feature Representation Learning -- Enhancing Understandability of Omics Data with SHAP, Embedding Projections and Interactive Visualisations -- WinDrift: Early Detction of Concept Drift through the use of Corresponding and Hierarchical Time Windows -- Investigation of Explainability Techniques for Multimodal Transformers -- Effective Imbalance Learning Utilizing Informative Data -- Interpretable Decision Tree via Human-In-The-Loop-Learning -- Application Track -- A Comparative Look at the Resilience of Discriminative and Generative Classifiers to Missing Data in Longitudinal Datasets -- Hierarchical Topic Model Inference by Community Discovery on Word Co-Occurrence Networks -- UMLS-Based Question-Answering Approach for Automatic Initial Frailty Assessment -- Natural Language Query For Technical Knowledge Graph Navigation -- Decomposition of Service Level Encoding for Anomaly Detcion -- Improving Ads-Profitability Using Traffic Fingerprints -- Attractiveness Analysis for Health Claims on Food Packages -- SchedmaDB: A Dataset for Structures in Relational Data.

This book constitutes the refereed proceedings of the 20th Australasian Conference on Data Mining, AusDM 2022, held in Western Sydney, Australia, during December 12-15, 2022. The 17 full papers included in this book were carefully reviewed and selected from 44 submissions. They were organized in topical sections as research track and application track.