LEADER 01163nam a2200253 i 4500 001 991004277336307536 005 20230518095626.0 008 230518s2010 it e 001 0 ita 022 $a1593-0947 040 $aBibl. Dip.le Aggr. Storia Società Studi sull'Uomo - Sez. Studi Storici 082 04$a271.56 245 02$aL'Ordine dei Chierici Regolari Minori (Caracciolini) :$breligione e cultura in età postridentina : atti del Convegno (Chieti, 11-12 aprile 2008) /$ca cura di Irene Fosi e Giovanni Pizzoru 260 $a[Napoli] :$bLoffredo,$c2010 300 $a364 p. :$bill.,$c25 cm 490 1 $aStudi medievali e moderni : arte, letteratura, storia ;$v27 500 $aDati della cop. 500 $aIn testa alla cop.: Dipartimento di Studi medievali e moderni - Università degli studi G. D'Annunzio 500 $aNum. monografico di: Studi medievali e moderni : arte, letteratura, storia, A. 14 (2010), n. 27, fasc. 1 650 7$aChierici regolari minori$xStoria 700 1 $aFosi, Irene 700 1 $aPizzorusso, Giovanni 912 $a991004277336307536 996 $aOrdine dei Chierici Regolari Minori (Caracciolini)$93378127 997 $aUNISALENTO LEADER 05066nam 22007575 450 001 9910768164603321 005 20240912151817.0 010 $a981-9986-96-6 024 7 $a10.1007/978-981-99-8696-5 035 $a(MiAaPQ)EBC30997895 035 $a(Au-PeEL)EBL30997895 035 $a(DE-He213)978-981-99-8696-5 035 $a(CKB)29267763000041 035 $a(EXLCZ)9929267763000041 100 $a20231204d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Science and Machine Learning $e21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11?13, 2023, Proceedings /$fedited by Diana Benavides-Prado, Sarah Erfani, Philippe Fournier-Viger, Yee Ling Boo, Yun Sing Koh 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (310 pages) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v1943 311 08$aPrint version: Benavides-Prado, Diana Data Science and Machine Learning Singapore : Springer,c2024 9789819986958 320 $aIncludes bibliographical references and index. 327 $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. 330 $aThis book constitutes the proceedings of the 21st Australasian Conference on Data Science and Machine Learning, AusDM 2023, held in Auckland, New Zealand, during December 11?13, 2023. The 20 full papers presented in this book were carefully reviewed and selected from 50 submissions. The papers are organized in the following topical sections: research track and application track. They deal with topics around data science and machine learning in everyday life. . 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v1943 606 $aData mining 606 $aArtificial intelligence 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aEducation$xData processing 606 $aComputer science$xMathematics 606 $aData Mining and Knowledge Discovery 606 $aArtificial Intelligence 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aComputers and Education 606 $aMathematics of Computing 615 0$aData mining. 615 0$aArtificial intelligence. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aEducation$xData processing. 615 0$aComputer science$xMathematics. 615 14$aData Mining and Knowledge Discovery. 615 24$aArtificial Intelligence. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aComputers and Education. 615 24$aMathematics of Computing. 676 $a006.3 701 $aXue$b Bing$c(Senior lecturer in computer science)$01369249 702 $aBenavides-Prado$b Diana 702 $aErfani$b Sarah. M 702 $aFournier-Viger$b Philippe 702 $aBoo$b Yee Ling 702 $aKoh$b Yun Sing$f1978- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910768164603321 996 $aData Science and Machine Learning$94234239 997 $aUNINA