Data Mining
19th Australasian Conference on Data Mining, AusDM 2021, Brisbane, QLD, Australia, December 14-15, 2021, Proceedings
Published on 8. December 2021
XII, 235 pages
978-981-16-8531-6 (ISBN)
Description
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.
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.
More details
Series
Edition
1st ed. 2021
Language
English
Place of publication
Singapore
Singapore
Publishing group
Springer Singapore
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XII, 235 p. 61 illus., 45 illus. in color.
ISBN-13
978-981-16-8531-6 (9789811685316)
DOI
10.1007/978-981-16-8531-6
Schweitzer Classification
Other editions
Additional editions
Yue Xu | Rosalind Wang | Anton Lord
Data Mining
19th Australasian Conference on Data Mining, AusDM 2021, Brisbane, QLD, Australia, December 14-15, 2021, Proceedings
Book
12/2021
Springer
€80.24
Shipment within 3-4 weeks
Content
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.
