Abstract: Profiling based advertising and commerce systems are provided herein. The system statistically analyzes user activity data of social network users and normalizes the statistical data with respect to specified user populations. Then the system profiles each user with respect to user archetypes using empirical study data that correlates the user archetypes with respective normalized statistical activity data relating to the user. The correspondence analysis is carried out by applying a heuristic genetic algorithm on an artificial neural network that represents the relation between the normalized user study data and the user archetypes. Profiles and segmentations produced are used for designing advertising campaigns and electronic commerce.

Abstract: A profiling unit is provided herein. The profiling unit comprises a statistical module that characterizes user activity data statistically; a normalization module that normalizes the statistical data related to each user with respect to user populations; and an analysis unit that analyzes a correspondence between normalized user study data and user archetypes, and also associates, for each user, the normalized statistical data with one of the user archetypes according to the analyzed correspondence. The correspondence analysis is carried out by applying a heuristic genetic algorithm on an artificial neural network that represents the relation between the normalized user study data and the user archetypes.