Abstract: A system and method for applying a first filter and a second filter, such as a recommendation and a constraint filter, to a plurality of items, including determining a cost of applying the first filter and the second filter to the plurality of items, and determining an order of applying the first and second filters based on the cost of applying the first and second filters.

Abstract: The present invention relates to a method and system for generating client preference recommendations in a high performance computing regime. Accordingly, one embodiment of the present invention comprises: providing a sparse ratings matrix, forming a plurality of data structures representing the sparse ratings matrix, forming a runtime recommendation model from the plurality of data structures, determining a recommendation from the runtime recommendation model in response to a request from a user, and providing the recommendation to the user.

Abstract: A system and method for applying a first filter and a second filter, such as a recommendation and a constraint filter, to a plurality of items, including determining a cost of applying the first filter and the second filter to the plurality of items, and determining an order of applying the first and second filters based on the cost of applying the first and second filters.

Abstract: Methods, systems, and articles of manufacture consistent with the present invention provide a recommendation server that receives a recommendation request from a user of a client computer. The recommendation server contains software to provide recommendations to the user. To provide the recommendations, the recommendation server applies a constraint filter and a recommendation filter on a set of items.