Disclosed in some examples are methods, systems, and machine-readable mediums which provide a relevance engine for determining a relevance of an individual (either a non-member or another member) to another individual (either a non-member or another member). This relevance engine may use signals in the form of data that the social networking service may learn about the individuals to determine how relevant the individuals are to each other. Example applications may include ordering of connection invitations in a social networking service.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: on a social networking service: receiving a first connection invitation from a first member of the social networking service; receiving a second connection invitation from a second member of the social networking service, the first and second connection invitations expressing a desire by the first and second members, respectively, to connect to a subject member of the social networking service; determining a first relevance score for the first member, using one or more computer processors, based upon a first plurality of observed signals, the relevance score indicating a likelihood that the subject member knows the first member; determining a second relevance score for the second member, using the one or more computer processors, based upon a second plurality of observed signals, the second relevance score indicating a likelihood that the subject member knows the second member; and sending a notification to the subject member of the first and second connection invitations, the notification ordered based upon the first and second respective relevance scores of the first and second members. 2. The method of claim 1, further comprising: receiving a third connection invitation from a third member of the social networking service; determining a third relevance score for the third member, using the one or more computer processors, based upon a third plurality of observed signals, the third relevance score indicating a likelihood that the subject member knows the third member; comparing the third relevance score to a predetermined relevance threshold; determining that the third relevance score is less relevant than the predetermined relevance threshold; responsive to determining that the third relevance score is less relevant than the predetermined relevance threshold, not including the third connection invitation in the notification. 3. The method of claim 1, wherein the first plurality of observed signals includes at least one of: any communication from the first member to the subject member; any communication from the subject member to the first member; a profile view of the first member by the subject member; common skills shared by the subject member and the first member; an age similarity between the subject member and the first member; employment histories of the subject member and the first member; and education histories of the subject member and the first member. 4. The method of claim 1, wherein determining the first relevance score based upon a plurality of first signals comprises determining the first relevance score using the first plurality of signals as inputs to a Bayesian classifier. 5. The method of claim 1, wherein determining the first relevance score based upon a plurality of first signals comprises at least determining a weighted score for each of the plurality of first observed signals and determining the first relevance score by at least summing the weighted scores for the plurality of observed signals. 6. The method of claim 1, wherein determining the first relevance score based upon a plurality of first signals comprises determining a relevance score using at least a neural network. 7. The method of claim 1, wherein the notification is an email. 8. A system for providing recommended social networking connections, the system comprising: a data collection module configured to: receive a first connection invitation from a first member of the social networking service; receive a second connection invitation from a second member of the social networking service, the first and second connection invitations expressing a desire by the first and second members, respectively, to connect to a subject member of the social networking service; a relevance module configured to: determine a first relevance score for the first member, using one or more computer processors, based upon a first plurality of observed signals, the first relevance score indicating a likelihood that the subject member knows the first member; determine a second relevance score for the second member, using the one or more computer processors, based upon a second plurality of observed signals, the second relevance score indicating a likelihood that the subject member knows the second member; and an application module configured to: send a notification to the subject member of the first and second connection invitations, the notification ordered based upon the first and second respective relevance scores of the first and second members. 9. The system of claim 8, wherein the data collection module is configured to: receive a third connection invitation from a third member of the social networking service; wherein the relevance module is configured to: determine a third relevance score for the third member, using the one or more computer processors, based upon a third plurality of observed signals, the relevance score indicating a likelihood that the subject member knows the third member; compare the third relevance score to a predetermined relevance threshold; determine that the third relevance score is less relevant than the predetermined relevance threshold; and responsive to determining that the third relevance score is less relevant than the predetermined relevance threshold, the application module configured to not include the third connection invitation in the notification. 10. The system of claim 8, wherein the first plurality of observed signals includes at least one of: any communication from the first member to the subject member; any communication from the subject member to the first member; a profile view of the first member by the subject member; common skills shared by the subject member and the first member; an age similarity between the subject member and the first member; employment histories of the subject member and the first member; and education histories of the subject member and the first member. 11. The system of claim 8, wherein the relevance module is configured to determine the first relevance score based upon a plurality of first signals at least by determining the first relevance score using the first plurality of signals as inputs to a Bayesian classifier. 12. The system of claim 8, wherein the relevance module is configured to determine the first relevance score based upon a plurality of first signals at least by determining a weighted score for each of the plurality of first observed signals and determining the first relevance score by at least summing the weighted scores for the plurality of observed signals. 13. The system of claim 8, wherein the relevance module is configured to determine the first relevance score based upon a plurality of first signals at least by determining a relevance score using at least a neural network. 14. The system of claim 8, wherein the notification is an email. 15. A machine readable medium that is not a transitory propagating signal, that stores instructions which when performed by a machine, cause the machine to perform operations comprising: receiving a first connection invitation from a first member of the social networking service; receiving a second connection invitation from a second member of the social networking service, the first and second connection invitations expressing a desire by the first and second members, respectively, to connect to a subject member of the social networking service; determining a first relevance score for the first member, based upon a first plurality of observed signals, the first relevance score indicating a likelihood that the subject member knows the first member; determining a second relevance score for the second member, based upon a second plurality of observed signals, the second relevance score indicating a likelihood that the subject member knows the second member; and sending a notification to the subject member of the first and second connection invitations, the notification ordered based upon the first and second respective relevance scores of the first and second members. 16. The machine readable medium of claim 15, wherein the instructions include instructions, which when performed by the machine, cause the machine to perform the operations comprising: receiving a third connection invitation from a third member of the social networking service; determining a third relevance score for the third member, using the one or more computer processors, based upon a third plurality of observed signals, the third relevance score indicating a likelihood that the subject member knows the third member; comparing the third relevance score to a predetermined relevance threshold; determining that the third relevance score is less relevant than the predetermined relevance threshold; responsive to determining that the third relevance score is less relevant than the predetermined relevance threshold, not including the third connection invitation in the notification. 17. The machine readable medium of claim 15, wherein the first plurality of observed signals includes at least one of: any communication from the first member to the subject member; any communication from the subject member to the first member; a profile view of the first member by the subject member; common skills shared by the subject member and the first member; an age similarity between the subject member and the first member; employment histories of the subject member and the first member; and education histories of the subject member and the first member. 18. The machine readable medium of claim 15, wherein the instructions for determining the first relevance score based upon a plurality of first signals comprises instructions, which when performed by the machine, cause the machine to perform operations comprising: determining the first relevance score using the first plurality of signals as inputs to a Bayesian classifier. 19. The machine readable medium of claim 15, wherein the instructions for determining the first relevance score based upon a plurality of first signals comprises instructions, which when performed by the machine, cause the machine to perform operations comprising: determining a weighted score for each of the plurality of first observed signals and determining the first relevance score by at least summing the weighted scores for the plurality of observed signals. 20. The machine readable medium of claim 15, wherein the instructions for determining the first relevance score based upon a plurality of first signals comprises instructions, which when performed by the machine, cause the machine to perform operations comprising: determining a relevance score using at least a neural network.