Systems and methods for optimizing decision graph collaborative filtering

摘要

The present invention provides collaborative filtering systems and methods employing default scores of decision graphs/trees to quickly create a top-n prediction list that can efficiently determine a user's interest in items. In one instance of the present invention, the list is refined by utilizing a variable maximum score algorithm and/or an invalidation list algorithm to insert items that score above an inclusion threshold set by a last item in the top-n prediction list. In another instance of the present invention, an invalidation list for a decision graph and/or decision tree is utilized to create a top-n prediction list. An algorithm employing default scores is then utilized to refine the top-n prediction list to insert items with default scores above an inclusion threshold set by a last item in the top-n prediction list.