16. The set of computer-readable non-transitory storage media of claim 11 , wherein the operations further comprise: receiving an indication of the correct value of the unknown, incomplete, or inaccurate user attribute; and responsive to said receiving of the indication of the correct value, adjusting at least one weight of the plurality of weights to change the relative confidence of the corresponding probability algorithm.
11. A set of one or more computer-readable non-transitory storage media that provides instructions that, when executed by a set of one or more processing devices, will cause said set of processing devices to perform operations comprising: maintaining one or more data stores storing a social graph of a social networking system comprising a plurality of nodes and a plurality of edges between the nodes, wherein the plurality of nodes includes user nodes corresponding to users of the social networking system and concept nodes corresponding to concepts, and wherein user attributes are associated with each user node; identifying an unknown, incomplete, or inaccurate user attribute to be inferred for a user of the social networking system; generating a plurality of probability lists using a corresponding plurality of probability algorithms that utilize a set of known user attributes of the user and the social graph, wherein each probability list of the plurality of probability lists includes a set of one or more probability entries that each include a prediction value and a confidence score corresponding to the prediction value, wherein the prediction value is a possible value of the unknown, incomplete, or inaccurate user attribute, and wherein the confidence score is a value indicating a predicted likelihood that the prediction value is a correct value of the unknown, incomplete, or inaccurate user attribute; generating an inferred user attribute value based upon the plurality of probability lists and a plurality of weights corresponding to the plurality of probability algorithms, wherein each weight of the plurality of weights indicates a relative confidence that the corresponding probability algorithm will generate a probability list including a prediction value that is the correct value of the unknown, incomplete, or inaccurate user attribute; and storing the inferred user attribute value in the one or more data stores.