18. The system of claim 17 , wherein the mapper is further configured to: iteratively choose an item as the third item until a distance in the trained joint embedding space from the first item to the third item is less than the distance between the first and second items; and estimate a rank of the third item in relation to the second item based upon a number of iterations required to choose the third item; and move at least one of the first, second, or third items in the joint embedding space such that a distance in the trained joint embedding space between the first and second items is less than a distance between the first and third items, wherein the move is based on a stochastic gradient technique weighted based upon the estimated rank.
17. The system of claim 15 , wherein the mapper is further configured to learn the mapping for one or more item types using a stochastic gradient technique.