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US Patent 11321736 Methods and systems for automated generation of personalized messages

Patent 11321736 was granted and assigned to HubSpot on May, 2022 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
HubSpot
HubSpot
Current Assignee
HubSpot
HubSpot
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11321736
Date of Patent
May 3, 2022
Patent Application Number
16668696
Date Filed
October 30, 2019
Patent Citations
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US Patent 10853082 Pipeline set selection based on duty cycle estimation of pipeline threads
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US Patent 10867003 Method of enhancing customer relationship management content and workflow
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US Patent 10911394 Mitigating abuse in an electronic message delivery environment
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US Patent 10931623 Introducing a new message source into an electronic message delivery environment
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US Patent 10992780 Microservices as a microservice
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US Patent 11165741 Introducing a new message source into an electronic message delivery environment
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US Patent 11070511 Managing electronic messages with a message transfer agent
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US Patent 10115060 Methods and systems for predicting a proposed electronic message as spam based on a predicted hard bounce rate for a list of email addresses
...
Patent Citations Received
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US Patent 11962546 Leveraging inferred context to improve suggested messages
0
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US Patent 11934372 Systems and methods for updating a knowledge graph through user input
0
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US Patent 11947902 Efficient multi-turn generative AI model suggested message generation
0
Patent Primary Examiner
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Saba Dagnew
CPC Code
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G06Q 50/12
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G06F 16/24578
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G06F 16/35
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G06F 16/9535
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H04L 51/32
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H04N 21/25883

A system includes a set of crawlers that find and retrieve documents from an information network, an information extraction system, a knowledge graph storing nodes and edges that connect them, wherein each node represents a respective entity of a corresponding entity type of a plurality of entity types, and wherein the knowledge graph further stores event data relating to events detected by the information extraction system, a machine learning system that trains models that are used in connection with at least one of entity extraction, event extraction, recipient identification, and content generation, a lead scoring system that scores the relevance of information to an individual and references information in the knowledge graph, and a content generation system that generates content of a personalized message to a recipient who is an individual for which the lead scoring system has determined a threshold level of relevance.

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