Abstract: A diversified, self-organizing map (SOM) system and method creates a number of special-purpose SOMs by filtering and training from a SOM Database which contains user preference data entries that include a wide range of fields or attributes of user preferences. Each special-purpose SOM is trained with a filtered subset of user preference data for fields and attributes related to its special purpose. Two or more special-purpose SOMs are harnessed inter-cooperatively together to provide recommendations of preferred items in response to queries. Multiple SOMs can be maintained at different websites and harnessed together through a global SOM interface. The system can function more efficiently than a single large SOM using a monolithic database with single-type data entries of large dimensionality.