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Herausgeber: 
  • Qiang Yang
  • Zhi-Hua Zhou
  • Zhiguo Gong
  • Min-Ling Zhang
  • Sheng-Jun Huang
  • Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part I 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  März 2019  
    Genre:  EDV / Informatik 
     
    Application software / Artificial Intelligence / C / Computer and Information Systems Applications / Computer Appl. in Social and Behavioral Sciences / Computer Application in Social and Behavioral Sciences / Computer applications in the social & behavioural sciences / computer science / Computer security / Computer Vision / Data and Information Security / Data Mining / Data Mining and Knowledge Discovery / Expert systems / knowledge-based systems / Image processing / Image Processing and Computer Vision / Information Retrieval / Information Systems Applications (incl. Internet) / Internet searching / Network Security / Optical data processing / Systems and Data Security
    ISBN:  9783030161477 
    EAN-Code: 
    9783030161477 
    Verlag:  Springer Nature EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Lecture Notes in Artificial Intelligence
    #11439 - Lecture Notes in Computer Science  
    Dimensionen:  H 235 mm / B 155 mm / D 35 mm 
    Gewicht:  1009 gr 
    Seiten:  627 
    Illustration:  XL, 627 p. 310 illus., 146 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 submissions. The papers present 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, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: classification and supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and related topics; clustering and anomaly detection; deep learning models and applications; sequential pattern mining; weakly supervised learning; recommender system; social network and graph mining; data pre-processing and feature selection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.

      
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