kdd
Knowledge Discovery in Databases (KDD) is the nontrivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data. It refers to the overall cycle of steps used to turn raw data into meaningful knowledge, typically involving data selection, cleaning, integration, transformation, data mining, evaluation, and presentation. In this view, data mining is the core analytical step that employs algorithms to extract patterns, while the surrounding steps ensure data quality and the interpretability of results.
The concept emerged from research in databases and machine learning during the 1980s and 1990s. A widely
Typical activities within KDD include selecting relevant data sources, preprocessing to address missing values and inconsistencies,
The field is associated with a professional community and venues such as the ACM SIGKDD Conference on