Techniques to facilitate recommendations for non-member connections

Patent metadata

Field	Value
Publication number	US-10116756-B2
Application number	US-201414525824-A
Country	US
Kind code	B2
Filing date	Oct 28, 2014
Priority date	Mar 28, 2013
Publication date	Oct 30, 2018
Grant date	Oct 30, 2018

Abstract

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.

First claim

What is claimed is:

1. A method for providing recommended social networking connections, the 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:
determining a set of connection candidates based upon information gathered about a member of the social networking service, the connection candidates in the set of connection candidates are not already members of the social networking service, the information gathered about the member including at least one of: information from email accounts of the member, blog posts of the member, electronic calendar entries of the member, associated websites of the member, social networking profiles of the member on a second social networking service;
executing a machine learning algorithm to determine a relevance score for each particular connection candidate in the set of connection candidates based upon a plurality of signals gathered by the social networking service, the plurality of signals identifying with a subscore a likelihood that the member knows the particular connection candidate, wherein the subscore is based on points automatically assigned to similarities between the member and the particular connection candidate; and
presenting, on a display, to the member the set of connection candidates ordered based upon relevance scores.

2. The method of claim 1 , wherein presenting to the member the set of connection candidates includes presenting only those connection candidates having a relevance score that exceeds a predetermined threshold value.

3. The method of claim 1 , wherein the plurality of signals gathered by the social networking service includes at least one of: a communication from a connection candidate in the set of connection candidates to the member; a communication from the member to a connection candidate in the set of connection candidates; the presence of a connection candidate in the set of connection candidates in an address book of the member; a calculated geographical distance between an IP address associated with the member and a second IP address associated with a connection candidate in the set of connection candidates; an age similarity between the member and a connection candidate in the set of connection candidates.

4. The method of claim 1 , wherein determining the set of connection candidates based upon information gathered about a member of the social networking service comprises determining a set of connection candidates based upon contacts in an address book of an email account of the member, and wherein one of the plurality of signals gathered by the social networking service includes the presence of a connection candidate in the set of connection candidates in an address book of a connection of the member.

5. The method of claim 1 , wherein information from email accounts of the member includes contents of emails.

6. The method of claim 1 , wherein the machine learning algorithm is used to determine the relevance score, and wherein the machine learning algorithm is a Bayesian classifier.

7. The method of claim 1 , wherein the machine learning algorithm is used to determine the relevance score, and wherein the machine learning algorithm is a neural network.

8. A system for providing recommended social networking connections, the system comprising:
at least one processor;
a memory;
a set of instructions operable on the at least one processor to:
determine a set of connection candidates based upon information gathered about a member of the social networking service, the connection candidates in the set of connection candidates are not already members of the social networking service, the information gathered about the member including at least one of: information from email accounts of the member, blog posts of the member, electronic calendar entries of the member, associated websites of the member, social networking profiles of the member on a second social networking service;
execute a machine learning algorithm to determine a relevance score for each particular connection candidate in the set of connection candidates based upon a plurality of signals gathered by the social networking service, the plurality of signals identifying with a subscore a likelihood that the member knows the particular connection candidate, wherein the subscore is based on points automatically assigned to similarities between the member and the particular connection candidate; and
present, on a display, to the member the set of connection candidates ordered based upon relevance scores.

9. The system of claim 8 , wherein the set of instructions to present the set of connection candidates includes instructions to present only those connection candidates having a relevance score that exceeds a predetermined threshold value.

10. The system of claim 8 , wherein the plurality of signals gathered by the social networking service includes at least one of; a communication from a connection candidate in the set of connection candidates to the member; a communication from the member to a connection candidate in the set of connection candidates; the presence of a connection candidate in the set of connection candidates in an address book of the member; a calculated geographical distance between an IP address associated with the member and a second IP address associated with a connection candidate in the set of connection candidates; an age similarity between the member and a connection candidate in the set of connection candidates.

11. The system of claim 8 , wherein the set of instructions to determine the set of connection candidates based upon information gathered about a member of the social networking service includes instructions to at least determine a set of connection candidates based upon contacts in an address book of an email account of the member, and wherein one of the plurality of signals gathered by the social networking service includes the presence of a connection candidate in the set of connection candidates in an address book of a connection of the member.

12. The system of claim 8 , wherein information from email accounts of the member includes contents of emails.

13. The system of claim 8 , wherein the machine learning algorithm is used to determine the relevance score, and wherein the machine learning algorithm is a Bayesian classifier.

14. The system of claim 8 , wherein the machine learning algorithm is used to determine the relevance score, and wherein the machine learning algorithm is a neural network.

15. A non-transitory machine readable medium that stores instructions which when performed by a machine, cause the machine to perform operations comprising:
determining a set of connection candidates based upon information gathered about a member of the social networking service, the connection candidates in the set of connection candidates are not already members of the social networking service, the information gathered about the member including at least one of: information from email accounts of the member, blog posts of the member, electronic calendar entries of the member, associated websites of the member, social networking profiles of the member on a second social networking service;
executing a machine learning algorithm to determine a relevance score for each particular connection candidate in the set of connection candidates based upon a plurality of signals gathered by the social networking service, the plurality of signals identifying with a subscore a likelihood that the member knows the particular connection candidate, whe

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Shah Samir M
• Tiwari Mitul
• Sumbaly Roshan Rajesh
• Wang Curtis

Classifications

• G06Q10/40

  Business processes related to social networking or social networking services · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06Q50/01

  Physics · mapped topic

• G06Q10/107 Primary

  Computer-aided management of electronic mailing [e-mailing] · CPC title

• G06Q10/1053

  Employment or hiring · CPC title