Recommendations in a computing advice facility

A non-transitory machine-readable storage medium having embodied thereon instructions executable by one or more machines to perform operations comprising:

• generating a ratings matrix including matrix values, each row of the ratings matrix identifying one of a plurality of users, each column of the ratings matrix identifying one of a plurality of items, and each of the matrix values corresponding to a known affinity rating describing a degree of affinity associated with one of the users and one of the items, wherein the ratings matrix includes a missing entry representing an unknown affinity rating;
• generating, using one or more processors, a revised ratings matrix by factoring the ratings matrix into a user matrix and an item matrix, the revised ratings matrix being the product of the user matrix and the item matrix and including at least one entry representing a predicted affinity rating in place of the missing entry;
• estimating a confidence value associated with at least a portion of the known affinity ratings in the ratings matrix;
• generating a confidence matrix that includes the confidence values;
• estimating a probability that a specific user had an opportunity to rate a specific item, the specific user and the specific item being associated with a missing affinity rating in the ratings matrix;
• replacing the missing affinity rating in the ratings matrix with a low affinity rating;
• and
• inserting a confidence value associated with the specific user and the specific item in the confidence matrix, the confidence value having a value equal to the probability.

An apparatus comprising:

• a matrix generation module configured to generate a ratings matrix including matrix values, each row of the ratings matrix identifying one of a plurality of users, each column of the ratings matrix identifying one of a plurality of items, and each of the matrix values corresponding to a known affinity rating describing a degree of affinity associated with one of the users and one of the items, wherein the ratings matrix includes a missing entry representing an unknown affinity rating;
• and
• a prediction module, implemented by one or more processors, configured to:
• generate a revised ratings matrix by factoring the ratings matrix into a user matrix and an item matrix, the revised ratings matrix being the product of the user matrix and the item matrix and including at least one entry representing a predicted affinity rating in place of the missing entry;
• estimate a confidence value associated with at least a portion of the known affinity ratings in the ratings matrix;
• generate a confidence matrix that includes the confidence values;
• estimate a probability that a specific user had an opportunity to rate a specific item, the specific user and the specific item being associated with a missing affinity rating in the ratings matrix;
• replace the missing affinity rating in the ratings matrix with a low affinity rating;
• and
• insert a confidence value associated with the specific user and the specific item in the confidence matrix, the confidence value having a value equal to the probability.