Techniques for inferring the identity (e.g., member profile attributes) of members of an online social network service are described. According to various embodiments, a member profile attribute missing from a member profile page associated with a particular member of an online social network service is identified. Member profile data and behavioral log data associated with a plurality of members of the online social network service is then accessed. Thereafter, a prediction modeling process is performed, based on a prediction model and feature data including the member profile data and the behavioral log data, to generate a confidence score associated with the particular member and the missing member profile attribute, the confidence score indicating a likelihood that the missing member profile attribute corresponds to a candidate value.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: identifying a member profile attribute missing from a member profile page associated with a particular member of an online social network service; accessing member profile data associated with a plurality of members of the online social network service; accessing behavioral log data associated with the members, the behavioral log data indicating interactions by the members with one or more products of the online social network service; performing prediction modeling, using one or more processors, based on a prediction model and feature data including the member profile data and the behavioral log data, to generate a confidence score associated with the particular member and the missing member profile attribute, the confidence score indicating a likelihood that the missing member profile attribute corresponds to a candidate value; determining that the confidence score is greater than a predetermined threshold; receiving a search request for members having a member profile attribute corresponding to the candidate value; modifying search results associated with the search request to identify the particular member based on the determination; and prompting the particular member to update the missing member profile attribute to correspond to the candidate value based on the determination. 2. The method of claim 1, wherein the missing member profile attribute corresponds to at least one of a geographic location, an educational attribute, an employer attribute, a title, and a skill. 3. (canceled) 4. The method of claim 1, wherein the missing member profile attribute corresponds to an employer attribute and the candidate value corresponds to a candidate employer. 5. The method of claim 4, wherein the feature data in the model includes member connection information identifying member connections of the members of the online social network. 6. The method of claim 4, wherein the feature data in the model includes IP address information identifying IP addresses associated with login requests by the members of the online social network. 7. The method of claim 4, wherein the feature data in the model includes profile view information identifying profile views by the members of the online social network. 8. The method of claim 4, wherein the feature data in the model includes email domain information identifying email domains associated with the members of the online social network. 9. The method of claim 4, wherein the feature data in the model includes invitation information identifying invitations transmitted by the members of the online social network. 10. The method of claim 1, wherein the missing member profile attribute corresponds to an educational attribute and the candidate value corresponds to a candidate university. 11. The method of claim 10, wherein the feature data in the model includes at least one of alumni group membership information, geographic location information, gender distribution information, and industry information associated with the members of the online social network. 12. The method of claim 1, wherein the missing member profile attribute corresponds to a geographic location and the candidate value corresponds to a candidate location. 13. The method of claim 12, wherein the feature data in the model includes at least one of IP address information, member connection information, and profile view information associated with the members of the online social network. 14. The method of claim 1, wherein the prediction model is any one of a logistic regression model, a gradient-boosted machine (GBM) model, a Naïve Bayes model, a support vector machines (SVM) model, a decision trees model, and a neural network model. 15. The method of claim 1, further comprising: determining that the missing member profile attribute of the particular member corresponds to the candidate value, based on the confidence score; and wherein the particular member is included in the modified search results. 16. The method of claim 1, further comprising: identifying an existing member profile attribute included in the member profile page of the particular member; generating a second confidence score associated with the particular member and the existing member profile attribute, the second confidence score indicating a likelihood that a new value distinct from a current value of the existing member profile attribute is accurate; and prompting the particular member to update the existing member profile attribute to correspond to the new value, based on the second confidence score. 17. The method of claim 16, further comprising: revising a current count of employees at an employer associated with the current value and an employer associated with the new value, based on the second confidence score. 18. The method of claim 16, further comprising: receiving a search request for members having a member profile attribute corresponding to the current value; determining that the existing member profile attribute of the particular member corresponds to the new value, based on the confidence score; and modifying search results associated with the search request to exclude the particular member. 19. A system comprising: a machine including a memory and at least one processor; an identification module, executable by the machine, configured to identify a member profile attribute missing from a member profile page associated with a particular member of an online social network service; and a prediction module, executable by the machine, configured to: access member profile data associated with a plurality of members of the online social network service; access behavioral log data associated with the members, the behavioral log data indicating interactions by the members with one or more products of the online social network service; perform prediction modeling, using one or more processors, based on a prediction model and feature data including the member profile data and the behavioral log data, to generate a confidence score associated with the particular member and the missing member profile attribute, the confidence score indicating a likelihood that the missing member profile attribute corresponds to a candidate value; determine that the confidence score is greater than a predetermined threshold; receive a search request for members having a member profile attribute corresponding to the candidate value; modify search results associated with the search request to identify the particular member based on the determination; and prompt the particular member to update the missing member profile attribute to correspond to the candidate value based on the determination. 20. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising: identifying a member profile attribute missing from a member profile page associated with a particular member of an online social network service; accessing member profile data associated with a plurality of members of the online social network service; accessing behavioral log data associated with the members, the behavioral log data indicating interactions by the members with one or more products of the online social network service; performing prediction modeling, using one or more processors, based on a prediction model and feature data including the member profile data and the behavioral log data, to generate a confidence score associated with the particular member and the missing member profile attribute, the confidence score indicating a likelihood that the missing member profile attribute corresponds to a candidate value; determining that the confidence score is greater than a predetermined threshold; receiving a search request for members having a member profile attribute corresponding to the candidate value; modifying search results associated with the search request to identify the particular member based on the determination; and prompting the particular member to update the missing member profile attribute to correspond to the candidate value based on the determination. 21. A method comprising: identifying an existing member profile attribute included in a member profile page of a particular member; generating a confidence score associated with the existing member profile attribute; determining that the existing member profile attribute is inaccurate based on the generated confidence score; receiving a search request for members having a member profile attribute corresponding to the existing member profile attribute; and modifying search results associated with the search request to exclude the particular member based on the determination.