International conference proceedings.

Includes author index.

Research Track
Parallel Nonlinear Dimensionality Reduction Using GPU Acceleration
Taking the Confusion out of Multinomial Confusion Matrices and Imbalanced Classes
Sharpshooting Most Beneficial Part of AUC for Detecting Malicious Logs
A Drift Aware Hierarchical Test based Approach for Combating Spammers in Online Social Networks
Hospital Readmission Prediction Using Semantic Relations Between Medical Codes
HFM++: An Enhanced Holographic Factorization Machine for Recommendation
Deep Learning for Bias Detection: From Inception to Deployment
Exploring Fusion Strategies in Deep Learning Models for Multi-modal Classification
Application Track
Chameleon: A Python Workflow Toolkit for Feature Selection
PostMatch: A Framework for Efficient Address Matching
Detection of Classical Cipher Types with Feature-Learning Approach
SOMPS-Net: Attention based Social Graph Framework for Early Detection of Fake Health News
How to Read the News: A Study of How Sentiment Effects Financial Markets
Investigation of Topic Modelling Methods for Understanding the Reports of the Mining Projects in Queensland
A Semi-Automatic Data Extraction System for Heterogeneous Data Sources: A Case Study from Cotton Industry
Nonnegative Matrix Factorization to Understand Spatio-Temporal Traffic Pattern Variations during COVID-19: A Case Study

This book constitutes the refereed proceedings of the 19th Australasian Conference on Data Mining, AusDM 2021, held in Brisbane, Queensland, Australia, in December 2021.* The 16 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in sections on research track and application track. *Due to the COVID-19 pandemic the conference was held online