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Advances in Knowledge Discovery and Data Mining 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part IV /

The 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720...

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Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Yang, De-Nian (Επιμελητής έκδοσης), Xie, Xing (Επιμελητής έκδοσης), Tseng, Vincent S. (Επιμελητής έκδοσης), Pei, Jian (Επιμελητής έκδοσης), Huang, Jen-Wei (Επιμελητής έκδοσης), Lin, Jerry Chun-Wei (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:Αγγλικά
Έκδοση: Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Έκδοση:1st ed. 2024.
Σειρά:Lecture Notes in Artificial Intelligence, 14648
Θέματα:
Artificial intelligence.
Algorithms.
Education > Data processing.
Computer science > Mathematics.
Signal processing.
Computer networks .
Artificial Intelligence.
Design and Analysis of Algorithms.
Computers and Education.
Mathematics of Computing.
Signal, Speech and Image Processing.
Computer Communication Networks.
Διαθέσιμο Online:https://doi.org/10.1007/978-981-97-2238-9
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Περιγραφή
Περίληψη:The 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 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.
Φυσική περιγραφή:XXXIII, 352 p. 106 illus., 91 illus. in color. online resource.
ISBN:9789819722389
ISSN:2945-9141 ;
DOI:10.1007/978-981-97-2238-9

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