Patents by Inventor Venumadhav Satuluri
Venumadhav Satuluri has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11550804Abstract: A messaging system provides recommendations of content that account holders of the messaging system might be interested in engaging with. In order to determine what to recommend, the messaging system generates a model of account holder engagement behavior organized by type of engagement. The model parameters are trained on differences between expected engagement behavior based on past data and actual engagement behavior, and include a set of common factor matrices that are trained using data from more than on engagement type. As a consequence, engagement behavior of other account holders with respect to other types of engagements different than the one sought to be recommended serves as a partial basis for determining what engagements of the sought-after type are recommended.Type: GrantFiled: October 5, 2020Date of Patent: January 10, 2023Assignee: Twitter, Inc.Inventors: Venumadhav Satuluri, Sebastian Scheiter, Reza Bosagh Zadeh
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Publication number: 20220283883Abstract: A method for distributed processing involves receiving a graph (G) of targets and of influencers, with each influencer related to at least one target, receiving an action graph of actions performed by one or more of the influencers, and key partitioning G across shards. The method further involves transposing the first graph (G) to obtain a first transposed graph (GT), value partitioning GT across the shards, storing the action graph on multiple shards, issuing, to a shard, a request specifying an influencer, to perform an intersection, receiving a response to the request of a set of influencers each of which is related to a target, and determining whether to send a recommendation to the target based on the response.Type: ApplicationFiled: January 24, 2022Publication date: September 8, 2022Inventors: Ajeet Grewal, Siva Gurumurthy, Venumadhav Satuluri, Pankaj Gupta, Brian A. Larson, Volodymyr Zhabuik, Aneesh Sharma, Ashish Goel
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Patent number: 11231977Abstract: A method for distributed processing involves receiving a graph (G) of targets and of influencers, with each influencer related to at least one target, receiving an action graph of actions performed by one or more of the influencers, and key partitioning G across shards. The method further involves transposing the first graph (G) to obtain a first transposed graph (GT), value partitioning GT across the shards, storing the action graph on multiple shards, issuing, to a shard, a request specifying an influencer, to perform an intersection, receiving a response to the request of a set of influencers each of which is related to a target, and determining whether to send a recommendation to the target based on the response.Type: GrantFiled: June 17, 2019Date of Patent: January 25, 2022Assignee: Twitter, Inc.Inventors: Ajeet Grewal, Siva Gurumurthy, Venumadhav Satuluri, Pankaj Gupta, Brian Larson, Volodymyr Zhabuik, Aneesh Sharma, Ashish Goel
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Patent number: 10795900Abstract: A messaging system provides recommendations of content that account holders of the messaging system might be interested in engaging with. In order to determine what to recommend, the messaging system generates a model of account holder engagement behavior organized by type of engagement. The model parameters are trained on differences between expected engagement behavior based on past data and actual engagement behavior, and include a set of common factor matrices that are trained using data from more than on engagement type. As a consequence, engagement behavior of other account holders with respect to other types of engagements different than the one sought to be recommended serves as a partial basis for determining what engagements of the sought-after type are recommended.Type: GrantFiled: November 11, 2015Date of Patent: October 6, 2020Assignee: Twitter, Inc.Inventors: Venumadhav Satuluri, Sebastian Schelter, Reza Bosagh Zadeh
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Publication number: 20190370096Abstract: A method for distributed processing involves receiving a graph (G) of targets and of influencers, with each influencer related to at least one target, receiving an action graph of actions performed by one or more of the influencers, and key partitioning G across shards. The method further involves transposing the first graph (G) to obtain a first transposed graph (GT), valuing partitioning GT across the shards, storing the action graph on multiple shards, issuing, to a shard, a request specifying an influencer, to perform an intersection, receiving a response to the request of a set of influencers each of which is related to a target, and determining whether to send a recommendation to the target based on the response.Type: ApplicationFiled: June 17, 2019Publication date: December 5, 2019Inventors: Ajeet Grewal, Siva Gurumurthy, Venumadhav Satuluri, Pankaj Gupta, Brian Larson, Volodymyr Zhabuik, Aneesh Sharma, Ashish Goel
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Patent number: 10324776Abstract: A method for distributed processing involves receiving a graph (G) of targets and of influencers, with each influencer related to at least one target, receiving an action graph of actions performed by one or more of the influencers, and key partitioning G across shards. The method further involves transposing the first graph (G) to obtain a first transposed graph (GT), valuing partitioning GT across the shards, storing the action graph on multiple shards, issuing, to a shard, a request specifying an influencer, to perform an intersection, receiving a response to the request of a set of influencers each of which is related to a target, and determining whether to send a recommendation to the target based on the response.Type: GrantFiled: December 29, 2017Date of Patent: June 18, 2019Assignee: Twitter, Inc.Inventors: Ajeet Grewal, Siva Gurumurthy, Venumadhav Satuluri, Pankaj Gupta, Brian Larson, Volodymyr Zhabuik, Aneesh Sharma, Ashish Goel
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Publication number: 20180121269Abstract: A method for distributed processing involves receiving a graph (G) of targets and of influencers, with each influencer related to at least one target, receiving an action graph of actions performed by one or more of the influencers, and key partitioning G across shards. The method further involves transposing the first graph (G) to obtain a first transposed graph (GT), valuing partitioning GT across the shards, storing the action graph on multiple shards, issuing, to a shard, a request specifying an influencer, to perform an intersection, receiving a response to the request of a set of influencers each of which is related to a target, and determining whether to send a recommendation to the target based on the response.Type: ApplicationFiled: December 29, 2017Publication date: May 3, 2018Inventors: Ajeet Grewal, Siva Gurumurthy, Venumadhav Satuluri, Pankaj Gupta, Brian Larson, Volodymyr Zhabuik, Aneesh Sharma, Ashish Goel
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Patent number: 9858130Abstract: A method for distributed processing involves receiving a graph (G) of targets and of influencers, with each influencer related to at least one target, receiving an action graph of actions performed by one or more of the influencers, and key partitioning G across shards. The method further involves transposing the first graph (G) to obtain a first transposed graph (GT), valuing partitioning GT across the shards, storing the action graph on multiple shards, issuing, to a shard, a request specifying an influencer, to perform an intersection, receiving a response to the request of a set of influencers each of which is related to a target, and determining whether to send a recommendation to the target based on the response.Type: GrantFiled: September 26, 2014Date of Patent: January 2, 2018Assignee: Twitter, Inc.Inventors: Ajeet Grewal, Siva Gurumurthy, Venumadhav Satuluri, Pankaj Gupta, Brian Larson, Volodymyr Zhabuik, Aneesh Sharma, Ashish Goel
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Publication number: 20150089514Abstract: A method for distributed processing involves receiving a graph (G) of targets and of influencers, with each influencer related to at least one target, receiving an action graph of actions performed by one or more of the influencers, and key partitioning G across shards. The method further involves transposing the first graph (G) to obtain a first transposed graph (GT), valuing partitioning GT across the shards, storing the action graph on multiple shards, issuing, to a shard, a request specifying an influencer, to perform an intersection, receiving a response to the request of a set of influencers each of which is related to a target, and determining whether to send a recommendation to the target based on the response.Type: ApplicationFiled: September 26, 2014Publication date: March 26, 2015Inventors: Ajeet Grewal, Siva Gurumurthy, Venumadhav Satuluri, Pankaj Gupta, Brian Larson, Volodymyr Zhabuik, Aneesh Sharma, Ashish Goel