Traditional Collaborative Filtering

Traditional collaborative filtering is a type of system used to generate user-specific recommendations based on common items between two similar users. Items most highly ranked by similar users come as the most recommended items. The major problem with this type of system is that, while recommendations are very targeted, they are also incredibly limited as far as what a user will find in his recommendations. This is due to the very limited number of similar users to which one is compared. Problems arise when users have a very narrow pool of items to draw from, and then recommendations that should ideally be similar in liking to a user do not fit that user's taste because recommendations are based on such a small amount of information. Basing recommendations solely on the taste of a small group of users with a common interest makes branching out in exposure to new things and things that are most likely to coincide with taste less and less likely.

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