4. A collaborative filtering system for predicting a user's rating for an item, wherein the user and a plurality of other users are members of a social network, comprising: a memory storing: a similarity measure w″ a,u for each pair of users in said recommendation system; ratings for items rated by other users in said recommendation system; a processor for calculating a weighted average of all the ratings for the item, wherein the weighted average is the sum of the product of a rating and its respective correlation coefficient similarity measure divided by the sum of the correlation coefficients similarity measures to provide a predicted user rating; wherein the similarity measure comprises a measure of similarity in ratings between pairs of users; wherein the similarity measure comprises a relationship distance in the said social network between pairs of users; wherein the processor calculates an initial version of the correlation coefficient w a,u for user a and other user u in the system in accordance with the relationship w a , u = ∑ i ⁢ r a , i ⁢ r u , i ∑ j ∈ I a ⁢ r a , j 2 ⁢ ∑ j ∈ I u ⁢ r u , j 2 where r u,i is the rating of other user u who has rated item I, r a,i is the rating of user a who has rated item I, where I a and I u are the set of items user a and user u have rated, respectively, wherein the processor enhances the initial version of coefficient w a,u by calculating the second version of the correlation coefficient, w′ a,u for user a and other user u in the system in accordance with the relationship: w′ a,u =w a,u , if there are more than N co-rated items w a , u ′ = w a , u ⁢  I a ⋂ I u  N , otherwise where I u is the set of items that other user u has rated, I a is the set of items that active user a has rated, wherein the processor calculates the similarity measure w″ a,u by enhancing a second version w′ a,u of the similarity measure in accordance with the relationship 
 w″ a,u =η d a,u +(1−η d a,u ) w″ a,u where η is a tunable parameter and d a,u is a measure of relationship distance between user a and other user u in the social network.
4. A collaborative filtering system for predicting a user's rating for an item, wherein the user and a plurality of other users are members of a social network, comprising: a memory storing: a similarity measure w″ a,u for each pair of users in said recommendation system; ratings for items rated by other users in said recommendation system; a processor for calculating a weighted average of all the ratings for the item, wherein the weighted average is the sum of the product of a rating and its respective correlation coefficient similarity measure divided by the sum of the correlation coefficients similarity measures to provide a predicted user rating; wherein the similarity measure comprises a measure of similarity in ratings between pairs of users; wherein the similarity measure comprises a relationship distance in the said social network between pairs of users; wherein the processor calculates an initial version of the correlation coefficient w a,u for user a and other user u in the system in accordance with the relationship w a , u = ∑ i ⁢ r a , i ⁢ r u , i ∑ j ∈ I a ⁢ r a , j 2 ⁢ ∑ j ∈ I u ⁢ r u , j 2 where r u,i is the rating of other user u who has rated item I, r a,i is the rating of user a who has rated item I, where I a and I u are the set of items user a and user u have rated, respectively, wherein the processor enhances the initial version of coefficient w a,u by calculating the second version of the correlation coefficient, w′ a,u for user a and other user u in the system in accordance with the relationship: w′ a,u =w a,u , if there are more than N co-rated items w a , u ′ = w a , u ⁢  I a ⋂ I u  N , otherwise where I u is the set of items that other user u has rated, I a is the set of items that active user a has rated, wherein the processor calculates the similarity measure w″ a,u by enhancing a second version w′ a,u of the similarity measure in accordance with the relationship 
 w″ a,u =η d a,u +(1−η d a,u ) w″ a,u where η is a tunable parameter and d a,u is a measure of relationship distance between user a and other user u in the social network. 6. The system of claim 4 , wherein the processor calculates the predicted user rating of an item i for a user a in accordance with the relationship: r _ a + ∑ u ⁢ ⁢ w a , u ″ ⁡ ( r u , i - r _ u ) ∑ u ⁢ ⁢  w a , u ″  , where the summation u is over a subset of other users that are most similar to user a according to w′ a,u and who have rated i, where r u,i is the rating of other user u who has rated item i, w′ a,u is the similarity measure between user a and the other user u, and r a is an average rating for active user a.