Intelligent Data Analysis approaches for Knowledge Discovery: Survey and challenges
Maher O Al-Khateeb, Mohammad A. Hassan, Ibrahim Al-Shourbaji*, Muhammad Saidu Aliero.
Abstract
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.
Key words: Knowledge Discovery in Database; Intelligent Data Analysis; Missing values; Data scarcity, Black box; Mathematical model
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