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  • 标题:Intelligent Data Analysis approaches for Knowledge Discovery: Survey and challenges
  • 本地全文:下载
  • 作者:Maher O Al-Khateeb ; Mohammad A.Hassan ; Ibrahim Al-Shourbaji
  • 期刊名称:Ilköğretim Online/Elementary Education Online
  • 印刷版ISSN:1305-3515
  • 电子版ISSN:1305-3515
  • 出版年度:2021
  • 卷号:20
  • 期号:5
  • 页码:1782-1792
  • DOI:10.17051/ilkonline.2021.05.196
  • 语种:English
  • 出版社:Öğretmen Eğitimi Akademisi
  • 摘要:With the enormous growth in information and data that are produced by various resources such as organization, companies’ phones, health records, social media, and the Internet of Tings (IoT), their analysis becomes a challenge and even more complex due to the increased volume of structured and unstructured data. Knowledge Discovery in Database (KDD) is the process of finding knowledge in data stored by various resources using Intelligent Data Analysis (IDA) techniques which have the ability to analyze and discover knowledge from these data. This paper investigates the main challenges in KDD. Also, it illustrates the IDAs approaches used to address KDD trends in short and finally presents open issues for research and progress in the field of KDD..
  • 关键词:Knowledge Discovery in Database;Intelligent Data Analysis;Missing values;Data scarcity;Black box;Mathematical mode
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