Patent ID: 7590616

Claim:
A method for implementing a collaborative-filtering based recommendation system for recommending one or more items among a plurality of items to a current user of a network, an item representing a product, service, webpage, audio, or document, the method comprising: producing a model based on explicit ratings of the plurality of items from a plurality of previous network users and implicit ratings of the plurality of items based on user events of the plurality of previous network users, wherein the implicit ratings comprise recency, intensity, and frequency ratings of user events for the plurality of items, a recency rating of a user event for an item indicating how recent the user event occurred for the item, a more recent user event for the item having a higher recency rating value than a less recent user event for the item, an intensity rating of a user event for an item reflecting a number of times the user event occurred regarding the item, and a frequency rating of a user event for an item reflecting a number of times the user event occurred regarding the item over a predetermined period of time, the model comprising a plurality of similarity measurements, each similarity measurement reflecting a level of similarity between two items in the plurality of items; receiving a first rating of a first item from the current user; and determining the one or more recommended items by producing a predicated rating for each item in the plurality of items, the predicated rating of an item being produced using the received first rating and a similarity measurement, retrieved from the model, that reflects a level of similarity between the item and the first item.