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[null,"1.","Record Nr.",null,"UNINA9910983393603321"]
[null,null,"Autore",null,"Pedreschi Dino"]
[null,null,"Titolo",null,"Discovery Science : 27th International Conference, DS 2024, Pisa, Italy, October 14–16, 2024, Proceedings, Part II / / edited by Dino Pedreschi, Anna Monreale, Riccardo Guidotti, Roberto Pellungrini, Francesca Naretto"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"9783031789809"]
[{"$nulls":4},"3031789806"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (686 pages)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 15244"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Education - Data processing"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Social sciences - Data processing"]
[{"$nulls":4},"Image processing - Digital techniques"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computers and Education"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Computer Application in Social and Behavioral Sciences"]
[{"$nulls":4},"Computer Imaging, Vision, Pattern Recognition and Graphics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Tree-Based Models and Causal Discovery -- Security and Anomaly Detection -- Computer Vision and Explainable AI -- Classification Models; SoBigData++: City for Citizens and Explainable AI -- SoBigData++: Societal Debates and Misinformation Analysis."]
[null,null,null,"Sommario/riassunto","The two-volume set LNAI 15243 + 15244 constitutes the proceedings of the 27th International Conference on Discovery Science, DS 2024, which took place in Pisa, Italy, during October 14-16, 2024. The 53 full papers presented in the proceedings were carefully reviewed and selected from 121 submissions. They were organized in topical sections as follows: Part I: LLM, Text Analytics, and Ethical Aspects of AI; Natural Language Processing, Sequential Data and Science Discovery; Data-Driven Science Discovery Methodologies; Graph Neural "]
[{"$nulls":4},"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. ."]