05166nam a22006615i 4500 978-981-99-8696-5 DE-He213 20251030110848.0 cr nn 008mamaa 231204s2024 si | s |||| 0|eng d 9789819986965 978-981-99-8696-5 10.1007/978-981-99-8696-5 doi QA76.9.D343 UNF bicssc UYQE bicssc COM021030 bisacsh UNF thema UYQE thema Data Science and Machine Learning [electronic resource] : 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11–13, 2023, Proceedings / edited by Diana Benavides-Prado, Sarah Erfani, Philippe Fournier-Viger, Yee Ling Boo, Yun Sing Koh. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XII, 300 p. 94 illus., 83 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Communications in Computer and Information Science, 1865-0937 ; 1943 Research Track: Random Padding Data Augmentation -- Unsupervised Fraud Detection on Sparse Rating Networks -- Semi-Supervised Model-Based Clustering for Ordinal Data -- Damage GAN: A Generative Model for Imbalanced Data -- Text-Conditioned Graph Generation Using Discrete Graph Variational Autoencoders -- Boosting QA Performance through SA-Net and AA-Net with the Read+Verify Framework -- Anomaly Detection Algorithms: Comparative Analysis and Explainability Perspectives -- Towards Fairness and Privacy: A Novel Data Pre-processing Optimization Framework for Non-binary Protected Attributes -- MStoCast: Multimodal Deep Network for Stock Market Forecast. -- Few Shot and Transfer Learning with Manifold Distributed Datasets -- Mitigating The Adverse Effects of Long-tailed Data on Deep Learning Models -- Shapley Value Based Feature Selection to Improve Generalization of Genetic Programming for High-Dimensional Symbolic Regression -- Hybrid Models for Predicting Cryptocurrency Price Using Financial and Non-Financial Indicators -- Application Track: Multi-Dimensional Data Visualization for Analyzing Materials -- Law in Order: An Open Legal Citation Network for New Zealand -- Enhancing Resource Allocation in IT Projects: The Potentials of Deep Learning-Based Recommendation Systems and Data-Driven Approaches -- A Comparison of One-Class versus Two-Class Machine Learning Models for Wildfire Prediction in California -- Skin Cancer Detection with Multimodal Data: A Feature Selection Approach Using Genetic Programming -- Comparison of Interpolation Techniques for Prolonged Exposure Estimation: A Case Study on Seven years of Daily Nitrogen Oxide in Greater Sydney -- Detecting Asthma Presentations from Emergency Department Notes: An Active Learning Approach. This book constitutes the proceedings of the 21st Australasian Conference on Data Science and Machine Learning, AusDM 2023, held in Auckland, New Zealand, during December 11–13, 2023. The 20 full papers presented in this book were carefully reviewed and selected from 50 submissions. The papers are organized in the following topical sections: research track and application track. They deal with topics around data science and machine learning in everyday life. . Data mining. 6941 Artificial intelligence. 58441 Image processing Digital techniques. 64228 Computer vision. Education Data processing. Computer science Mathematics. 64041 Data Mining and Knowledge Discovery. Artificial Intelligence. 58441 Computer Imaging, Vision, Pattern Recognition and Graphics. 65550 Computers and Education. Mathematics of Computing. 66501 Benavides-Prado, Diana. editor. edt http://id.loc.gov/vocabulary/relators/edt 67967 Erfani, Sarah. editor. edt http://id.loc.gov/vocabulary/relators/edt 67968 Fournier-Viger, Philippe. editor. edt http://id.loc.gov/vocabulary/relators/edt 67969 Boo, Yee Ling. editor. (orcid)0000-0001-7188-9597 https://orcid.org/0000-0001-7188-9597 edt http://id.loc.gov/vocabulary/relators/edt 67970 Koh, Yun Sing. editor. edt http://id.loc.gov/vocabulary/relators/edt 67971 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819986958 Printed edition: 9789819986972 Communications in Computer and Information Science, 1865-0937 ; 1943 66508 https://doi.org/10.1007/978-981-99-8696-5 ZDB-2-SCS ZDB-2-SXCS 56744 56744