Explains the KDD process to extract knowledge from datasets, highlighting its applications and challenges.
Knowledge Discovery in Databases (KDD) is a systematic process used to extract meaningful patterns and useful knowledge from large datasets. It combines techniques from statistics, machine learning, database systems, and artificial intelligence. The KDD process involves several stages including data selection, cleaning, transformation, data mining, and interpretation. This paper explains the complete KDD process, its steps, applications, advantages, and challenges in detail.
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Mr.Khedekar Nagesh Haridas (2025) studied this question.
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