# US 2013/0159096 A1 · Ranked user graph for social advertisement targeting > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2013/0159096 A1 - Document ID: US20130159096A1 - Status: Published application - Kind: A1 - Application number: 13/329,070 - Filed: 2011-12-16 - Published: 2013-06-20 - Earliest claimed: 2011-12-16 - Inventors: Ram Santhanagopal; Arvind Thirunarayanan; Katrina Illari; Bret Thaeler - Web page: https://patentgrep.com/patent/US20130159096A1 ## CPC - G06Q 30/0269: {based on user profile or attribute} - G06Q 10/48: using social graphs - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract A method, advertising network, and computer program product for constructing a ranked user graph for advertisement targeting. The method commences by selecting a user from a set of candidate users from a first internet site, then identifying membership of the user in at least one second internet site. Having the intersecting membership, then assembling a set of one or more relationship associations between the user and a set of the user's associates (e.g. as retrieved from the second internet site). The relationship associations have various aspects that relate the user to a particular associate, and scoring or ranking of those various aspects are used in applying weights the relationship associations. Privacy settings are applied in order to filter out certain associations and/or to restrict propagation of information that the user or other authority deems as private information. The ranked user graph is used in delivering advertising to the user's associates. ## Claims ### Claim 1 A computer implemented method for implementing a ranked user graph for social advertisement targeting, the method comprising: selecting a subject user from a set of candidate users, the set of candidate users comprising a plurality of user records retrieved from at least a first internet site; identifying an aspect of membership of the subject user in at least one second internet site; assembling a set of one or more relationship associations between the subject user and a set of associates retrieved from the second internet site, each of the one or more relationship associations having at least one aspect to relate the subject user to a particular associate from among the set of associates; and applying a weight to at least some of the relationship associations. ### Claim 2 (depends on 1) The method of claim 1, further comprising ranking the set of associates using at least the weight applied to one or more relationship associations. ### Claim 3 (depends on 1) The method of claim 1, further comprising filtering the set of associates to form a subset of the set of associates using at least the one or more relationship associations. ### Claim 4 (depends on 3) The method of claim 3, wherein filtering the set of associates comprises removing associates using at least some privacy actions. ### Claim 5 (depends on 3) The method of claim 3, wherein forming the subset of the set of associates comprises applying at least some user filters. ### Claim 6 (depends on 1) The method of claim 1, wherein identifying an aspect of membership uses a source ranking ### Claim 7 (depends on 1) The method of claim 1, further comprising forming a suggestion list based on the weight applied to at least some of the relationship associations. ### Claim 8 An advertising network implementing a ranked user graph for social advertisement targeting, comprising: a computer processor to execute a set of program code instructions; and a memory to hold the program code instructions, in which the program code instructions comprises program code to perform, selecting a subject user from a set of candidate users, the set of candidate users comprising a plurality of user records retrieved from at least a first internet site; identifying an aspect of membership of the subject user in at least one second internet site; assembling a set of one or more relationship associations between the subject user and a set of associates retrieved from the second internet site, each of the one or more relationship associations having at least one aspect to relate the subject user to a particular associate from among the set of associates; and applying a weight to at least some of the relationship associations. ### Claim 9 (depends on 8) The advertising network of claim 8, further comprising ranking the set of associates using at least the weight applied to one or more relationship associations. ### Claim 10 (depends on 8) The advertising network of claim 8, further comprising filtering the set of associates to form a subset of the set of associates using at least the one or more relationship associations. ### Claim 11 (depends on 10) The advertising network of claim 10, wherein filtering the set of associates comprises removing associates using at least some privacy actions. ### Claim 12 (depends on 10) The advertising network of claim 10, wherein forming the subset of the set of associates comprises applying at least some user filters. ### Claim 13 (depends on 8) The advertising network of claim 8, wherein identifying an aspect of membership uses a source ranking. ### Claim 14 (depends on 8) The advertising network of claim 8, further comprising forming a suggestion list based on the weight applied to at least some of the relationship associations. ### Claim 15 A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method to implement a ranked user graph for social advertisement targeting, the method comprising: selecting a subject user from a set of candidate users, the set of candidate users comprising a plurality of user records retrieved from at least a first internet site; identifying an aspect of membership of the subject user in at least one second internet site; assembling a set of one or more relationship associations between the subject user and a set of associates retrieved from the second internet site, each of the one or more relationship associations having at least one aspect to relate the subject user to a particular associate from among the set of associates; and applying a weight to at least some of the relationship associations. ### Claim 16 (depends on 15) The computer readable medium of claim 15, further comprising ranking the set of associates using at least the weight applied to one or more relationship associations. ### Claim 17 (depends on 15) The computer readable medium of claim 15, further comprising filtering the set of associates to form a subset of the set of associates using at least the one or more relationship associations. ### Claim 18 (depends on 17) The computer readable medium of claim 17, wherein filtering the set of associates comprises removing associates using at least some privacy actions. ### Claim 19 (depends on 17) The computer readable medium of claim 17, wherein forming the subset of the set of associates comprises applying at least some user filters. ### Claim 20 (depends on 15) The computer readable medium of claim 15, further comprising forming a suggestion list based on the weight applied to at least some of the relationship associations.