Discovery Science 27th International Conference, DS 2024, Pisa, Italy, October 14-16, 2024, Proceedings, Part I

The two-volume set LNAI 15243 + 15244 constitutes the proceedings of the 27th International Conference on Discovery Science, DS 2024, which took place in Pisa, Italy, during October 14-16, 2024.
The 53 full papers presented in the proceedings were carefully reviewed and selected from 121 submissions. They were organized in topical sections as follows: 
Part I: LLM, Text Analytics, and Ethical Aspects of AI; Natural Language Processing, Sequential Data and Science Discovery; Data-Driven Science Discovery Methodologies; Graph Neural Network, Graph Theory, Unsupervised Learning and Regression; 
Part II: Tree-Based Models and Causal Discovery; Security and Anomaly Detection; Computer Vision and Explainable AI; Classification Models; SoBigData++: City for Citizens and Explainable AI; SoBigData++: Societal Debates and Misinformation Analysis.
 

Dettagli sul prodotto

• Con la collaborazione di: Dino Pedreschi (Editore), Anna Monreale (Editore), Riccardo Guidotti (Editore), Roberto Pellungrini (Editore), Francesca Naretto (Editore), Riccardo Guidotti et al (Editore)
• Editore: Springer, Berlin
• Contenuto: Libro
• Forma del prodotto: Tascabile
• Data pubblicazione: 08.01.2025
• Categoria: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica
• EAN: 9783031789762
• ISBN: 978-3-0-3178976-2
• Numero di pagine: 419
• Illustrazioni: XXV, 419 p. 140 illus., 130 illus. in color.
• Dimensioni (della confezione): 15.5 x 2.4 x 23.5 cm
• Peso (della confezione): 675 g
• Serie: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Categorie: machine learning, Lehrmittel, Lerntechnologien, E-Learning, Data Mining, Artificial Intelligence, Bildverarbeitung, Wissensbasierte Systeme, Expertensysteme, Computer Vision, Computer Imaging, Vision, Pattern Recognition and Graphics, Natural Language Processing, Data Mining and Knowledge Discovery, Computers and Education, Computer Application in Social and Behavioral Sciences, machine learning algorithms, Computing methodologies, search methodologies, Machine learning approaches