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公开(公告)号：US20190327321A1
公开(公告)日：2019-10-24
申请号：US16457439
申请日：2019-06-28
Applicant: Google LLC
Inventor： Ilya Gennadyevich Gelfenbeyn , Artem Goncharuk , Ilya Andreevich Platonov , Pavel Aleksandrovich Sirotin , Olga Aleksandrovna Gelfenbeyn
Abstract: Disclosed is the technology for computer-based “Daily Brief” service, which includes methods and corresponding systems for proactively providing push notifications for users of chat information systems. The push notifications are dynamically generated and presented to the user based on identification of one or more triggering events, which may include predetermined time/date, current geographical location, activity of peers and friends in social media associated with the user, scheduled events, appointments, meetings, emails, instant messages, and many more. The described technology improves the interaction interface between the user and chat information system.
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公开(公告)号：US20190139538A1
公开(公告)日：2019-05-09
申请号：US16237318
申请日：2018-12-31
Applicant: Google LLC
CPC classification number: G10L15/1815 , G01C21/3608 , G06F3/0481 , G06F3/16 , G10L15/08 , G10L15/22 , G10L2015/088 , G10L2015/223 , H04M3/4936 , H04M7/0012 , H04M2201/40 , H04M2203/355
Abstract: Natural speech dialog system and methods are disclosed. In one example, a method includes identifying a dialog system intent associated with the speech input based on at least one predetermined intent keyword, the dialog system intent having required intent parameters, determining whether data for all required intent parameters of the dialog system are available, based on the determination, selectively initiating a parameter collection dialog associated with the dialog system intent, the parameter collection dialog being operable to collect data for the required parameters not otherwise available to the dialog system intent, and based on the dialog system intent and one or more required parameters, generating an action instruction.
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公开(公告)号：US20250148257A1
公开(公告)日：2025-05-08
申请号：US19018807
申请日：2025-01-13
Applicant: GOOGLE LLC
Inventor： Ilya Gennadyevich Gelfenbeyn , Artem Goncharuk , Pavel SIROTIN
Abstract: Invoking an agent during a dialog between a user and an automated assistant. Some implementations are directed to receiving, during a human-to-automated assistant dialog, natural language input of the user that indicates a desire to engage an agent, but that fails to indicate a particular agent to be engaged. Those implementations are further directed to selecting a particular agent from a plurality of available agents, and transmitting an invocation request to the selected particular agent. In some implementations an agent selection model can be utilized in selecting the particular agent, such as a machine learning model. The machine learning model can be trained to enable generation of output that indicates, for each of a plurality of available agents (and optionally intent(s) for those agents), a probability that the available agent (and optionally intent) will generate appropriate responsive content.
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24.发明授权公开(公告)号：US12271934B2
公开(公告)日：2025-04-08
申请号：US18372483
申请日：2023-09-25
Applicant: GOOGLE LLC
IPC: G06Q30/0601
Abstract: A method for enhancing dialog systems is disclosed herein. The method may include maintaining an online marketplace that may have a plurality of dialog system extension elements. The plurality of dialog system extension elements may include at least one of a dialog system plugin, a dialog system add-on, a dialog system update, and a dialog system upgrade. The method may further include receiving a selection of one of the plurality of dialog system extension elements from an end user. The end user may be associated with a dialog system. The method may continue with associating the one of the plurality of dialog system extension elements with the dialog system of the end user.
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公开(公告)号：US20240296353A1
公开(公告)日：2024-09-05
申请号：US18662647
申请日：2024-05-13
Applicant: GOOGLE LLC
Abstract: A method for example-driven machine learning is disclosed herein. The method comprises maintaining a plurality of dialog system rules and a knowledge database including a plurality of intent objects and a plurality of entity objects. The plurality of intent objects and the plurality of entity objects are associated with at least one dialog system rule. An exemplary phrase is received and one or more linguistic elements are retrieved from the exemplary phrase. It is determined that at least one of the linguistic elements is directed to at least one of the plurality of intent objects of the plurality of entity objects and at least one of the linguistic elements in association with the at least one dialog system rule is added to the knowledge database.
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Patent Agency Ranking
公开(公告)号：US20240137423A1
公开(公告)日：2024-04-25
申请号：US18400887
申请日：2023-12-29
Applicant: GOOGLE LLC
Inventor： Ilya Gennadyevich Gelfenbeyn , Artem Goncharuk , Ilya Andreevich Platonov , Pavel Aleksandrovich Sirotin , Olga Aleksandrovna Gelfenbeyn
Abstract: Disclosed is the technology for computer-based “Daily Brief” service, which includes methods and corresponding systems for proactively providing push notifications for users of chat information systems. The push notifications are dynamically generated and presented to the user based on identification of one or more triggering events, which may include predetermined time/date, current geographical location, activity of peers and friends in social media associated with the user, scheduled events, appointments, meetings, emails, instant messages, and many more. The described technology improves the interaction interface between the user and chat information system.
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27.发明公开公开(公告)号：US20240013269A1
公开(公告)日：2024-01-11
申请号：US18372483
申请日：2023-09-25
Applicant: GOOGLE LLC
IPC: G06Q30/0601
CPC classification number: G06Q30/0601
Abstract: A method for enhancing dialog systems is disclosed herein. The method may include maintaining an online marketplace that may have a plurality of dialog system extension elements. The plurality of dialog system extension elements may include at least one of a dialog system plugin, a dialog system add-on, a dialog system update, and a dialog system upgrade. The method may further include receiving a selection of one of the plurality of dialog system extension elements from an end user. The end user may be associated with a dialog system. The method may continue with associating the one of the plurality of dialog system extension elements with the dialog system of the end user.
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28.发明授权公开(公告)号：US11769184B2
公开(公告)日：2023-09-26
申请号：US18094256
申请日：2023-01-06
Applicant: GOOGLE LLC
IPC: G06Q30/0601
CPC classification number: G06Q30/0601
Abstract: A method for enhancing dialog systems is disclosed herein. The method may include maintaining an online marketplace that may have a plurality of dialog system extension elements. The plurality of dialog system extension elements may include at least one of a dialog system plugin, a dialog system add-on, a dialog system update, and a dialog system upgrade. The method may further include receiving a selection of one of the plurality of dialog system extension elements from an end user. The end user may be associated with a dialog system. The method may continue with associating the one of the plurality of dialog system extension elements with the dialog system of the end user.
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公开(公告)号：US11693637B1
公开(公告)日：2023-07-04
申请号：US17319739
申请日：2021-05-13
Applicant: Google LLC
Inventor： Rishabh Singh , Hanjun Dai , Manzil Zaheer , Artem Goncharuk , Karen Davis , David Andre
CPC classification number: G06F8/436 , G06F40/279 , G06F40/40 , G06N3/08 , G06N7/01
Abstract: Using a natural language (NL) latent presentation in the automated conversion of source code from a base programming language (e.g., C++) to a target programming language (e.g., Python). A base-to-NL model can be used to generate an NL latent representation by processing a base source code snippet in the base programming language. Further, an NL-to-target model can be used to generate a target source code snippet in the target programming language (that is functionally equivalent to the base source code snippet), by processing the NL latent representation. In some implementations, output(s) from the NL-to-target model indicate canonical representation(s) of variables, and in generating the target source code snippet, technique(s) are used to match those canonical representation(s) to variable(s) of the base source code snippet. In some implementations, multiple candidate target source code snippets are generated, and a subset (e.g., one) is selected based on evaluation(s).
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公开(公告)号：US20220147712A1
公开(公告)日：2022-05-12
申请号：US17582881
申请日：2022-01-24
Applicant: GOOGLE LLC
IPC: G06F40/279 , G10L15/26
Abstract: A method for context-based natural language processing is disclosed herein. The method comprises maintaining a plurality of dialog system rules, receiving a user request from a Dialog System Interface, receiving one or more attributes associated with the user request from the Dialog System Interface or a user device, and identifying a type of context associated with the user request based on the user request and the one or more attributes. A context label is assigned to the user request associated with the type of context. Based on the context label and the user request, a particular dialog system rule is selected from the plurality of dialog system rules. A response to the user request is generated by applying the dialog system rule to at least a part of the user request.
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