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Big Data Analytics and Knowledge Discovery [electronic resource] : 25th International Conference, DaWaK 2023, Penang, Malaysia, August 28-30, 2023, Proceedings / edited by Robert Wrembel, Johann Gamper, Gabriele Kotsis, A Min Tjoa, Ismail Khalil.

Contributor(s): Wrembel, Robert [editor.] | Gamper, Johann [editor.] | Kotsis, Gabriele [editor.] | Tjoa, A Min [editor.] | Khalil, Ismail [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 14148Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 1st ed. 2023.Description: XVI, 400 p. 147 illus., 107 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031398315.Subject(s): Quantitative research | Data mining | Application software | Artificial intelligence | Data Analysis and Big Data | Data Mining and Knowledge Discovery | Computer and Information Systems Applications | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 001.422 | 005.7 Online resources: Click here to access online In: Springer Nature eBookSummary: This book constitutes the proceedings of the 25th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2023, which took place in Penang, Malaysia, during August 29-30, 2023. The 18 full papers presented together with 19 short papers were carefully reviewed and selected from a total of 83 submissions. They were organized in topical sections as follows: Data quality; advanced analytics and pattern discovery; machine learning; deep learning; and data management.
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This book constitutes the proceedings of the 25th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2023, which took place in Penang, Malaysia, during August 29-30, 2023. The 18 full papers presented together with 19 short papers were carefully reviewed and selected from a total of 83 submissions. They were organized in topical sections as follows: Data quality; advanced analytics and pattern discovery; machine learning; deep learning; and data management.

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