In information science, profiling refers to the process of construction and application of user profiles generated by computerized data analysis.

This is the use of algorithms or other mathematical techniques that allow the discovery of patterns or correlations in large quantities of data, aggregated in databases. When these patterns or correlations are used to identify or represent people, they can be called profiles. Other than a discussion of profiling technologies or population profiling, the notion of profiling in this sense is not just about the construction of profiles, but also concerns the application of group profiles to individuals, e. g., in the cases of credit scoring, price discrimination, or identification of security risks (Hildebrandt & Gutwirth 2008) (Elmer 2004).

Profiling is being used in fraud prevention, ambient intelligence, and consumer analytics. Statistical methods of profiling include Knowledge Discovery in Databases (KDD).

 

Note:   The above text is excerpted from the Wikipedia article Profiling (information science), which has been released under the GNU Free Documentation License.