# US 10,372,740 B2 · Viewpoint data logging for improved feed relevance > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,372,740 B2 - Document ID: US10372740B2 - Status: Granted - Kind: B2 - Application number: 15/454,136 - Filed: 2017-03-09 - Published: 2017-09-14 - Granted: 2019-08-06 - Earliest claimed: 2016-03-09 - Assignees: Microsoft Technology Licensing, LLC - Applicants: Microsoft Technology Licensing, LLC - Inventors: Kevin Chang; Lin Yang - Web page: https://patentgrep.com/patent/US10372740B2 ## CPC - G06Q 10/1053: Employment or hiring - G06F 16/334: Query execution (filtering based on additional data G06F16/335) - G06F 16/335: Filtering based on additional data, e.g. user or group profiles (filtering in web context G06F16/9535, G06F16/9536) - G06F 16/9537: Spatial or temporal dependent retrieval, e.g. spatiotemporal queries - G06Q 10/40: Business processes related to social networking or social networking services - G06Q 10/42: Determination of affinities or common interests between users - H04L 12/4625: {Single bridge functionality, e.g. connection of two networks over a single bridge} - H04L 51/52: for supporting social networking services - H04L 67/306: User profiles - 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) - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract A system and method includes obtaining activity data of an online social networking system, the activity data including duration data indicative of a duration in which at least some of the content items has previously been displayed on other feeds of members of the online social networking system and interactions with the content items by the members. For each of the content items, a probability score of the member to interact with the content item is determined by applying a logistic regression model to the duration data and the interactions to determine, at least in part, a probability score of the member to interact with the content item and the feed is generated with at least some of the content items having an order based on the probability score for each of the at least some content items. ## Claims ### Claim 1 A processor implemented method, comprising: receiving a request to generate a feed for an online social networking system, the feed to be displayed on a user interface associated with a member of the online social networking system; obtaining, from an activity database of the online social networking system, activity data of content items of the online social networking system, the activity data including: duration data indicative of a duration in which at least some of the content items has previously been displayed on other feeds of members of the online social networking system, the duration data provided, at least in part, to the activity database by client devices on which the feeds were displayed, wherein the duration data comprises a first time at which a first percentage of associated content item was displayed on a prior feed and a second time at which a second percentage of the associated content item was no longer displayed on the prior feed; and interactions with the content items by the members; for each of the content items, determining a probability score of the member to interact with the content item by applying a logistic regression model to the duration data and the interactions to determine, at least in part, a probability score of the member to interact with the content item; generating the feed with at least some of the content items having an order based on the probability score for each of the at least some content items; and transmitting via a network interface, the feed as generated to a client device associated with the member. ### Claim 2 (depends on 1) The method of claim 1, wherein determining, for each of the content items, the probability score is further based on a contextual relevance score computed based, at least in part, on characteristics of the member and the activity data of the content item. ### Claim 3 (depends on 2) The method of claim 2, wherein at least one of the content items has an associated actor-verb-object triplet based on content of the content item, and wherein determining, for each of the content items, the probability score is further based on a reducing the probability score based on a number of times the member has viewed, on a feed, content items having at least one similar actor, verb, or object as the content item. ### Claim 4 (depends on 1) The method of claim 1, wherein the first and second percentages are both fifty percent. ### Claim 5 (depends on 4) The method of claim 4, wherein determining the probability score is further based, at least in part, on the duration exceeding a predetermined minimum time. ### Claim 6 (depends on 5) The method of claim 5, wherein determining the probability score is further based, at least in part, on the duration not exceeding a predetermined maximum time. ### Claim 7 A non-transitory computer readable medium comprising instructions which, when implemented by a processor, cause the processor to perform operations comprising: receive a request to generate a feed for an online social networking system, the feed to be displayed on a user interface associated with a member of the online social networking system; obtain from an activity database of the online social networking system, activity data of content items of the online social networking system, the activity data including: duration data indicative of a duration in which at least some of the content items has previously been displayed on other feeds of members of the online social networking system, the duration data provided, at least in part, to the activity database by client devices on which the feeds were displayed, wherein the duration data comprises a first time at which a first percentage of associated content item was displayed on a prior feed and a second time at which a second percentage of the associated content item was no longer displayed on the prior feed; and interactions with the content items by the members; for each of the content items, determine a probability score of the member to interact with the content item by applying a logistic regression model to the duration data and the interactions to determine, at least in part, a probability score of the member to interact with the content item; generate the feed with at least some of the content items having an order based on the probability score for each of the at least some content items; and transmit, via a network interface, the feed as generated to a client device associated with the member. ### Claim 8 (depends on 7) The computer readable medium of claim 7, wherein the instructions further cause the processor to determine, for each of the content items, the probability score further based on a contextual relevance score computed based, at least in part, on characteristics of the member and the activity data of the content item. ### Claim 9 (depends on 8) The computer readable medium of claim 8, wherein at least one of the content items has an associated actor-verb-object triplet based on content of the content item, and wherein the instructions further cause the processor to determine, for each of the content items, the probability score further based on a reducing the probability score based on a number of times the member has viewed, on a feed, content items having at least one similar actor, verb, or object as the content item. ### Claim 10 (depends on 7) The computer readable medium of claim 7, wherein the first and second percentages are both fifty percent. ### Claim 11 (depends on 10) The computer readable medium of claim 10, wherein the instructions further cause the processor to determine the probability score further based, at least in part, on the duration exceeding a predetermined minimum time. ### Claim 12 (depends on 11) The computer readable medium of claim 11, wherein the instructions further cause the processor to determine the probability score further based, at least in part, on the duration not exceeding a predetermined maximum time. ### Claim 13 A system, comprising: a non-transitory computer readable medium comprising instructions which, when implemented by a processor, cause the processor to perform operations comprising: receive a request to generate a feed for an online social networking system, the feed to be displayed on a user interface associated with a member of the online social networking system; obtain from an activity database of the online social networking system, activity data of content items of the online social networking system, the activity data including: duration data indicative of a duration in which at least some of the content items has previously been displayed on other feeds of members of the online social networking system, the duration data provided, at least in part, to the activity database by client devices on which the feeds were displayed, wherein the duration data comprises a first time at which a first percentage of associated content item was displayed on a prior feed and a second time at which a second percentage of the associated content item was no longer displayed on the prior feed; and interactions with the content items by the members; for each of the content items, determine a probability score of the member to interact with the content item by applying a logistic regression model to the duration data and the interactions to determine, at least in part, a probability score of the member to interact with the content item; generate the feed with at least some of the content items having an order based on he probability score for each of the at least some content items; and transmit, via a network interface, the feed as generated to a client device associated with the member. ### Claim 14 (depends on 13) The system of claim 13, wherein the instructions further cause the processor to determine, for each of the content items, the probability score further based on a contextual relevance score computed based, at least in part, on characteristics of the member and the activity data of the content item. ### Claim 15 (depends on 14) The system of claim 14, wherein at least one of the content items has an associated actor-verb-object triplet based on content of the content item, and wherein the instructions further cause the processor to determine, for each of the content items, the probability score further based on a reducing the probability score based on a number of times the member has viewed, on a feed, content items having at least one similar actor, verb, or object as the content item. ### Claim 16 (depends on 13) The system of claim 13, wherein the first and second percentages are both fifty percent. ### Claim 17 (depends on 16) The system of claim 16, wherein the instructions further cause the processor to determine the probability score further based, at least in part, on the duration exceeding a predetermined minimum time. ### Claim 18 (depends on 17) The system of claim 17, wherein the instructions further cause the processor to determine the probability score further based, at least in part, on the duration not exceeding a predetermined maximum time. ### Claim 19 (depends on 13) The system of claim 13, further comprising the processor and the network interface.