1. 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 article, the method comprising: producing a model using a plurality of documents generated for the plurality of items, each document representing an item and comprising item information describing the item, the item information being encoded as metadata into the document, the metadata comprising at least one attribute/value pair and taxonomy information describing the item, the model comprising a plurality of similarity measurements, each similarity measurement reflecting a level of similarity between two items in the plurality of items, wherein the level of similarity between two items is determined using the two documents representing the two items and is not based on user ratings of the two 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.