METHOD AND APPARATUS FOR PROGRAMMATICALLY ADJUSTING THE RELATIVE IMPORTANCE OF CONTENT DATA AS BEHAVIORAL DATA CHANGES

摘要

Methods, apparatuses, and computer program products are described herein that are configured for creating a hybrid recommendation algorithm that programmatically decreases the importance of the content-based data as the basis of affinity data supporting collaborative filtering grows over time. One example embodiment may include a method for computing a content based similarity metric between a first item and a second item, accessing each of one or more instances of affinity data; and calculating an overall similarity metric between the first item and the second item, the overall similarity metric being a function of the content based similarity metric between the first item and the second item and a number of instances of empirical data for the items, the function defined such that as the number of instances of empirical data increases, the overall similarity metric increases a relative contribution in favor of the empirical data.