Building adaptive user profiles by a genetic fuzzy classifier with feature selection

A genetic algorithm is used to build user profiles from a collection of documents previously retrieved by the user. A fuzzy classification and a genetic term selection process provide a better utilization of valuable knowledge for genetic algorithms in order to get an improvement of the quality of the current and near future information needs in the areas of interest to the user. A gene in the chromosome of the genetic algorithm is defined by a term and a fuzzy number of occurrences of the term in documents belonging to the class of documents that satisfy the user´s information need. In this way, the terms that allow the system to discern between good and bad documents are selected and stored as a part of the user´s profile to be used in future queries to the system. The fuzzy classifier implements an inductive derivation of the current, experience based, interest profile in terms of an importance weighted conjunction of genes