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 . Profiling is being used in fraud prevention, ambient intelligence, and consumer analytics. Statistical methods of profiling include Knowledge Discovery in Databases (KDD). The profiling process The technical process of profiling can be separated in several steps: Preliminary grounding: The profiling process starts with a specification of the applicable problem domain and the identification of the goals of analysis. Data collection: The target dataset or database for analysis is formed by selecting the relevant data in the light of existing domain knowledge and data understanding. Data preparation: The data are preprocessed for removing noise and reducing complexity by eliminating attributes. Data mining: The data are analysed with the algorithm or heuristics developed to suit the data, model and goals. Interpretation: The mined patterns are evaluated on their relevance and validity by specialists and/or professionals in the application domain (e.g. excluding spurious correlations). Application: The constructed profiles are applied, e.g. to categories of persons, to test and fine-tune the algorithms. Institutional decision: The institution decides what actions or policies to apply to groups or individuals whose data match a relevant profile. Data collection, preparation and mining all belong to the phase in which the profile is under construction. However, profiling also refers to the application of profiles, meaning the usage of profiles for the identification or categorization of groups or individual persons. As can be seen in step six (application), the process is circular. There is a feedback loop between the construction and the application of profiles. The interpretation of profiles can lead to the reiterant – possibly real-time – fine-tuning of specific previous steps in the profiling process. The application of profiles to people whose data were not used to construct the profile is based on data