04969nam a22006135i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001600172072001600188072001700204072002300221072001500244072001600259245026800275250001800543264007200561300006500633336002600698337002600724338003600750347002400786490007500810505177400885520047102659650002303130650003603153650004903189650002103238650003203259650004203291650004103333650003603374650007103410650002903481650003703510700009203547700008303639700009403722700015003816700008303966710003404049773002604083776003604109776003604145830008204181856004604263912001404309912001504323999001704338978-981-99-8696-5DE-He21320251030110848.0cr nn 008mamaa231204s2024    si |    s    |||| 0|eng d  a97898199869659978-981-99-8696-57 a10.1007/978-981-99-8696-52doi 4aQA76.9.D343 7aUNF2bicssc 7aUYQE2bicssc 7aCOM0210302bisacsh 7aUNF2thema 7aUYQE2thema10aData Science and Machine Learningh[electronic resource] :b21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11–13, 2023, Proceedings /cedited by Diana Benavides-Prado, Sarah Erfani, Philippe Fournier-Viger, Yee Ling Boo, Yun Sing Koh.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXII, 300 p. 94 illus., 83 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aCommunications in Computer and Information Science,x1865-0937 ;v19430 aResearch 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.  aThis 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. . 0aData mining.96941 0aArtificial intelligence.958441 0aImage processingxDigital techniques.964228 0aComputer vision. 0aEducationxData processing. 0aComputer sciencexMathematics.96404114aData Mining and Knowledge Discovery.24aArtificial Intelligence.95844124aComputer Imaging, Vision, Pattern Recognition and Graphics.96555024aComputers and Education.24aMathematics of Computing.9665011 aBenavides-Prado, Diana.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9679671 aErfani, Sarah.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9679681 aFournier-Viger, Philippe.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9679691 aBoo, Yee Ling.eeditor.0(orcid)0000-0001-7188-95971https://orcid.org/0000-0001-7188-95974edt4http://id.loc.gov/vocabulary/relators/edt9679701 aKoh, Yun Sing.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9679712 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981998695808iPrinted edition:z9789819986972 0aCommunications in Computer and Information Science,x1865-0937 ;v194396650840uhttps://doi.org/10.1007/978-981-99-8696-5  aZDB-2-SCS  aZDB-2-SXCS  c56744d56744