Data mining, sometimes called knowledge discovery, is the process of sifting large volumes of data for correlations, patterns, and trends.

Data Quality Issues: The effectiveness of data mining heavily depends on the quality of the data being analyzed. Incomplete, inaccurate, or ambiguous data can lead to misleading results.

This module starts with an overview of data mining methods, then focuses on frequent pattern analysis, including the Apriori algorithm and FP-growth algorithm for frequent itemset mining, as well as ...

Ledolter will speak on "Data Mining and Business Analytics with Big and Small Data." He will review useful methods for data mining and business analytics, describe several applications and case ...

The Feynman trap—ransacking data for patterns without any preconceived idea of what one is looking for—is the Achilles heel of studies based on data mining.

Like Palantir, this Chinese start-up uses AI to help corporate clients and law enforcement convert huge volumes of data into actionable information.