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.-20. (canceled) 21. A method comprising: on a computer-based social networking service, executing computer program instructions which cause one or more computer processors to perform the operations of: receiving a plurality of connection invitation requests from a plurality of members, the plurality of connection invitation requests directed to a subject member of the social networking service; determining a plurality of relevance scores for the plurality of members based upon a plurality of signals; and generating a notification to the subject member, the notification including a connection invitation corresponding to a connection invitation request of the plurality of connection invitation requests, the connection invitation selected based on the plurality of relevance scores. 22. The method of claim 21, wherein a relevance score of the plurality of relevance scores indicates a predicted likelihood that the subject member knows a member of the plurality of members, the member corresponding to the relevance score. 23. The method of claim 22, wherein a second connection invitation request of the plurality of connection invitation requests is not included in the notification based on a second relevance score corresponding to the second connection invitation request, wherein the second relevance score is below a threshold. 24. The method of claim 21, wherein the notification includes a plurality of connection invitations ordered according to the plurality of relevance scores. 25. The method of claim 21, wherein the plurality of signals includes at least one of: a communication from a first member of the plurality of members to the subject member; a 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. 26. The method of claim 21, wherein determining the plurality of relevance scores based upon the plurality of signals comprises determining the plurality of relevance scores using the plurality of signals as inputs to a Bayesian classifier. 27. The method of claim 21, wherein determining the plurality of relevance scores based upon the plurality of signals comprises at least determining a weighted score for each of the plurality of signals and determining the plurality of relevance scores by at least summing the weighted scores for the plurality of signals. 28. The method of claim 21, wherein determining the plurality of relevance scores based upon the plurality of signals comprises determining the plurality of relevance scores using at least a neural network. 29. A system for providing recommended social networking connections, the system comprising: a machine readable medium stored thereon including instructions, which, when executed by a processor, cause the system to: receive a plurality of connection invitation requests from a plurality of members, the plurality of connection invitation requests directed to a subject member of a social networking service; determine a plurality of relevance scores for the plurality of members based upon a plurality of signals, wherein a relevance score of the plurality of relevance scores indicates a predicted likelihood that the subject member knows a member of the plurality of members, the member corresponding to the relevance score; and generate a notification to the subject member, the notification including a connection invitation corresponding to a connection invitation request of the plurality of connection invitation requests, the connection invitation selected based on the plurality of relevance scores. 30. The system of claim 29, wherein a relevance score of the plurality of relevance scores indicates a predicted likelihood that the subject member knows a member of the plurality of members, the member corresponding to the relevance score. 31. The system of claim 30, wherein a second connection invitation request of the plurality of connection invitation requests is not included in the notification based on a second relevance score corresponding to the second connection invitation request, wherein the second relevance score is below a threshold. 32. The system of claim 29, wherein the notification includes a plurality of connection invitations ordered according to the plurality of relevance scores. 33. 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 plurality of connection invitation requests from a plurality of members, the plurality of connection invitation requests directed to a subject member of a social networking service; determining a plurality of relevance scores for the plurality of members based upon a plurality of signals, wherein a relevance score of the plurality of relevance scores indicates a predicted likelihood that the subject member knows a member of the plurality of members, the member corresponding to the relevance score; and generating a notification to the subject member, the notification including a connection invitation corresponding to a connection invitation request of the plurality of connection invitation requests, the connection invitation selected based on the plurality of relevance scores. 34. The machine readable medium of claim 33, wherein a relevance score of the plurality of relevance scores indicates a predicted likelihood that the subject member knows a member of the plurality of members, the member corresponding to the relevance score. 35. The machine readable medium of claim 34, wherein a second connection invitation request of the plurality of connection invitation requests is not included in the notification based on a second relevance score corresponding to the second connection invitation request, wherein the second relevance score is below a threshold. 36. The machine readable medium of claim 33, wherein the notification includes a plurality of connection invitations ordered according to the plurality of relevance scores. 37. The machine readable medium of claim 33, wherein the plurality of signals includes at least one of: a communication from a first member of the plurality of members to the subject member; a 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. 38. The machine readable medium of claim 33, wherein determining the plurality of relevance scores based upon the plurality of signals comprises determining the plurality of relevance scores using the plurality of signals as inputs to a Bayesian classifier. 39. The machine readable medium of claim 33, wherein determining the plurality of relevance scores based upon the plurality of signals comprises at least determining a weighted score for each of the plurality of signals and determining the plurality of relevance scores by at least summing the weighted scores for the plurality of signals. 40. The machine readable medium of claim 33, wherein determining the plurality of relevance scores based upon the plurality of signals comprises determining the plurality of relevance scores using at least a neural network.