Abstract: A browser-based personalized recommendation system and method for lifestyle items comprising style dimension mapping, inputs, outputs, and a computer-algorithm is described. The system gathers information about a user's unique lifestyle preferences, which is then correlated to clothing and lifestyle items. The recommendation system uniquely and directly matches users to discrete items without the need for historic user data.

Abstract: A user-centric computer-implemented method and system for managing inputs and creating, modifying, importing, and sharing one or more user lifestyle preference profiles as input into a relevance assessment engine to determine a user's product or service preferences comprises a personalized recommendation software for assessing and aggregating lifestyle items via style dimension mapping of one or more computer-implemented algorithms to process image-associated metadata to create unique vector inputs, individualized lifestyle preference indices, and lifestyle preference outputs, associated with a plurality of correlated products, services and experiences. The recommendation system then directly matches each user to discrete relevant items without the need for management of historical data from other users.