# US 2020/0401848 A1 · Machine learning based system for identifying resonated connections in online connection networks > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401848 A1 - Document ID: US20200401848A1 - Status: Published application - Kind: A1 - Application number: 16/447,817 - Filed: 2019-06-20 - Published: 2020-12-24 - Earliest claimed: 2019-06-20 - Assignees: Microsoft Technology Licensing, LLC - Applicants: Microsoft Technology Licensing, LLC - Inventors: Yan Liu; Ajita Thomas; Alexander Shoykhet; Bing Wang; Ying Xi - Web page: https://patentgrep.com/patent/US20200401848A1 ## CPC - G06Q 10/1053: Employment or hiring - G06F 18/214: Generating training patterns; Bootstrap methods, e.g. bagging or boosting - G06N 20/00: Machine learning - G06Q 30/0202: Market predictions or forecasting for commercial activities - H04L 67/14: Session management (for real-time applications in data packet communications networks H04L65/1066) - H04L 67/306: User profiles - H04L 67/535: {Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34)} - 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 - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract The technical problem of identifying relevant social proof information with respect to a premium service for a given member profile in an online connection network system is addressed by, first, capturing the associated member's intent based on the member's activity on the web site provided by the online connection network system. The determined intent is used as input into a relevance machine learning model that is executed to identify the member's connection who is a subscriber to the premium service and who has been identified as the most convincing resonated connection of the member with respect to subscribing to the premium service. ## Claims ### Claim 1 A computer implemented method comprising: maintaining member profiles in an online connection network system, the member profiles including a subject profile representing a member in the online connection network system, the subject profile associated with connected profiles from the member profiles; monitoring interactions of the member with the online connection network system during a current login session of the member in the online connection network system; based on the monitored interactions of the member with the online connection network system during the current login session, identifying intent information for the subject profile; using the intent information, together with data derived from the subject profile, and with data derived from the connected profiles as input into a relevance machine learning model, executing the relevance machine learning model to produce a set of candidate profiles from the connected profiles, each profile from the set of candidate profiles having an associated relevance value indicating connection strength between the profile and the subject profile; selecting from the set of candidate profiles a resonated connection profile based on the monitored interaction of the member with the online connection network system during the current login session; and including into a user interface a reference to the selected resonated connection profile together with information about a premium service provided by the online connection network system. ### Claim 2 (depends on 1) The method of claim 1, wherein the identifying of the intent information for the subject profile comprises executing an intent machine learning model, using, as input, the monitored interactions of the member with the online connection network system during the current login session. ### Claim 3 (depends on 2) The method of claim 2, comprising: tracking and storing activity of members in the online connection network system to generate members' behavior data; and training the intent machine learning model using the members' behavior data. ### Claim 4 (depends on 1) The method of claim 1, comprising causing presentation of the user interface on a display device associated with the member represented by the subject profile. ### Claim 5 (depends on 1) The method of claim 1, wherein the selecting of the resonated connection profile comprises executing of the relevance machine learning model using as input, the monitored interaction of the member with the online connection network system during the current login session. ### Claim 6 (depends on 1) The method of claim 1, comprising tracking and storing information related to interactions between the member and the member's connections in the online connection network system, wherein the data derived from the subject profile and used as input into the relevance machine learning model comprises the tracked information related to interactions between the member and the member's connections. ### Claim 7 (depends on 1) The method of claim 1, comprising tracking and storing information related to the member's connections and their respective status as subscribers to the premium service, wherein the data derived from the connected profiles and used as input into a relevance machine learning model comprises the tracked information related to the member's connections and their respective status as subscribers to the premium service. ### Claim 8 (depends on 1) The method of claim 1, comprising: tracking and storing information related to interactions, in the online connection network system; between members of the online connection network system and their respective connections; tracking and storing information related to behavior, in the online connection network system, of members of the online connection network system that are subscribers to the premium service; and training the relevance machine learning model using the information related to interactions, in the online connection network system, between members of the online connection network system and their respective connections and the information related to behavior, in the online connection network system, of members of the online connection network system that are subscribers to the premium service. ### Claim 9 (depends on 1) The method of claim 1, wherein the intent information indicates job search in the online connection network system. ### Claim 10 (depends on 1) The method of claim 1, wherein the identifying of the intent information for the subject profile comprises identifying a subdomain of the intent information and wherein the resonated connection profile is characterized by the subdomain of the intent information. ### Claim 11 A system comprising: one or more processors; and a non-transitory computer readable storage medium comprising instructions that when executed by the one or processors cause the one or more processors to perform operations comprising: maintaining member profiles in an online connection network system; the member profiles including a subject profile representing a member in the online connection network system; the subject profile associated with connected profiles from the member profiles; monitoring interactions of the member with the online connection network system during a current login session of the member in the online connection network system; based on the monitored interactions of the member with the online connection network system during the current login session, identifying intent information for the subject profile; using the intent information, together with data derived from the subject profile, and with data derived from the connected profiles as input into a relevance machine learning model, executing the relevance machine learning model to produce a set of candidate profiles from the connected profiles, each profile from the set of candidate profiles having an associated relevance value indicating connection strength between the profile and the subject profile; selecting from the set of candidate profiles a resonated connection profile based on the monitored interaction of the member with the online connection network system during the current login session; and including into a user interface a reference to the selected resonated connection profile together with information about a premium service provided by the online connection network system. ### Claim 12 (depends on 11) The system of claim 11, wherein the identifying of the intent information for the subject profile comprises executing an intent machine learning model, using, as input, the monitored interactions of the member with the online connection network system during the current login session. ### Claim 13 (depends on 12) The system of claim 12, comprising: tracking and storing activity of members in the online connection network system to generate members' behavior data; and training the intent machine learning model using the members' behavior data. ### Claim 14 (depends on 11) The system of claim 11, comprising causing presentation of the user interface on a display device associated with the member represented by the subject profile. ### Claim 15 (depends on 11) The system of claim 11, wherein the selecting of the resonated connection profile comprises executing of the relevance machine learning model using as input, the monitored interaction of the member with the online connection network system during the current login session. ### Claim 16 (depends on 11) The system of claim 11, comprising tracking and storing information related to interactions between the member and the member's connections in the online connection network system, wherein the data derived from the subject profile and used as input into the relevance machine learning model comprises the tracked information related to interactions between the member and the member's connections. ### Claim 17 (depends on 11) The system of claim 11, comprising tracking and storing information related to the member's connections and their respective status as subscribers to the premium service, wherein the data derived from the connected profiles and used as input into a relevance machine learning model comprises the tracked information related to the member's connections and their respective status as subscribers to the premium service. ### Claim 18 (depends on 11) The system of claim 11, comprising: tracking and storing information related to interactions, in the online connection network system; between members of the online connection network system and their respective connections; tracking and storing information related to behavior, in the online connection network system, of members of the online connection network system that are subscribers to the premium service; and training the relevance machine learning model using the information related to interactions, in the online connection network system, between members of the online connection network system and their respective connections and the information related to behavior, in the online connection network system, of members of the online connection network system that are subscribers to the premium service. ### Claim 19 (depends on 11) The system of claim 11, wherein the intent information indicates job sears in the online connection network system. ### Claim 20 A machine-readable non-transitory storage medium having instruction data executable by a machine to cause the machine to perform operations comprising: maintaining member profiles in an online connection network system; the member profiles including a subject profile representing a member in the online connection network system, the subject profile associated with connected profiles from the member profiles; monitoring interactions of the member with the online connection network system during a current login session of the member in the online connection network system; based on the monitored interactions of the member with the online connection network system during the current login session, identifying intent information for the subject profile; using the intent information, together with data derived from the subject profile, and with data derived from the connected profiles as input into a relevance machine learning model, executing the relevance machine learning model to produce a set of candidate profiles from the connected profiles, each profile from the set of candidate profiles having an associated relevance value indicating connection strength between the profile and the subject profile; selecting from the set of candidate profiles a resonated connection profile based on the monitored interaction of the member with the online connection network system during the current login session; and including into a user interface a reference to the selected resonated connection profile together with information about a premium service provided by the online connection network system.