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Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part I / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng



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Autore: Kashima Hisashi Visualizza persona
Titolo: Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part I / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng Visualizza cluster
Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Edizione: 1st ed. 2023.
Descrizione fisica: 1 online resource (563 pages)
Disciplina: 006.312
Soggetto topico: Artificial intelligence
Algorithms
Education—Data processing
Computer science—Mathematics
Computer vision
Computer engineering
Computer networks
Artificial Intelligence
Design and Analysis of Algorithms
Computers and Education
Mathematics of Computing
Computer Vision
Computer Engineering and Networks
Soggetto non controllato: Mathematics
Altri autori: IdeTsuyoshi  
PengWen-Chih  
Sommario/riassunto: The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023. The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Titolo autorizzato: Advances in Knowledge Discovery and Data Mining  Visualizza cluster
ISBN: 3-031-33374-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910728396003321
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Serie: Lecture Notes in Artificial Intelligence, . 2945-9141 ; ; 13935