Patents by Inventor Lily Sin
Lily Sin 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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Publication number: 20230121138Abstract: This document describes techniques and devices for a refined search with machine learning. These techniques improve computer-aided searches through enabling selection of search criteria used in a prior search and providing a refined search result based on that selection. Furthermore, a machine-learning component of a search engine can be altered to improve future search results based on the selection and an indication of the desirability of the refined search result.Type: ApplicationFiled: December 21, 2022Publication date: April 20, 2023Inventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Patent number: 11568003Abstract: This document describes techniques and devices for a refined search with machine learning. These techniques improve computer-aided searches through enabling selection of search criteria used in a prior search and providing a refined search result based on that selection. Furthermore, a machine-learning component of a search engine can be altered to improve future search results based on the selection and an indication of the desirability of the refined search result.Type: GrantFiled: June 13, 2018Date of Patent: January 31, 2023Assignee: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Publication number: 20220318039Abstract: This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.Type: ApplicationFiled: June 24, 2022Publication date: October 6, 2022Inventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Patent number: 11403123Abstract: This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.Type: GrantFiled: March 4, 2021Date of Patent: August 2, 2022Assignee: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Patent number: 11275630Abstract: This document describes techniques and devices for task-related sorting, application discovery, and unified bookmarking for application managers. Through use of an application manager, multiple applications (including standalone applications, instant applications, websites, and other content) that a person can use to accomplish a single task, or multiple related tasks, are sorted into discrete groups for display in the application manager. The application manager can automatically recognize relationships between activities performed with the applications and recognize user actions with the applications that are related to the activities. Based on the relationships and user actions, the application manager can automatically determine that the activities and actions represent a task and display a task group that includes the applications that represent the task.Type: GrantFiled: August 5, 2020Date of Patent: March 15, 2022Assignee: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Publication number: 20210208908Abstract: This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.Type: ApplicationFiled: March 4, 2021Publication date: July 8, 2021Applicant: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Patent number: 10970096Abstract: This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.Type: GrantFiled: September 21, 2020Date of Patent: April 6, 2021Assignee: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Publication number: 20210004247Abstract: This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.Type: ApplicationFiled: September 21, 2020Publication date: January 7, 2021Applicant: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Patent number: 10846109Abstract: This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.Type: GrantFiled: May 8, 2018Date of Patent: November 24, 2020Assignee: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Publication number: 20200364099Abstract: This document describes techniques and devices for task-related sorting, application discovery, and unified bookmarking for application managers. Through use of an application manager, multiple applications (including standalone applications, instant applications, websites, and other content) that a person can use to accomplish a single task, or multiple related tasks, are sorted into discrete groups for display in the application manager. The application manager can automatically recognize relationships between activities performed with the applications and recognize user actions with the applications that are related to the activities. Based on the relationships and user actions, the application manager can automatically determine that the activities and actions represent a task and display a task group that includes the applications that represent the task.Type: ApplicationFiled: August 5, 2020Publication date: November 19, 2020Applicant: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Patent number: 10783013Abstract: This document describes techniques and devices for task-related sorting, application discovery, and unified bookmarking for application managers. Through use of an application manager, multiple applications (including standalone applications, instant applications, websites, and other content) that a person can use to accomplish a single task, or multiple related tasks, are sorted into discrete groups for display in the application manager. The application manager can automatically recognize relationships between activities performed with the applications and recognize user actions with the applications that are related to the activities. Based on the relationships and user actions, the application manager can automatically determine that the activities and actions represent a task and display a task group that includes the applications that represent the task.Type: GrantFiled: August 24, 2018Date of Patent: September 22, 2020Assignee: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Publication number: 20190188322Abstract: This document describes techniques and devices for a refined search with machine learning. These techniques improve computer-aided searches through enabling selection of search criteria used in a prior search and providing a refined search result based on that selection. Furthermore, a machine-learning component of a search engine can be altered to improve future search results based on the selection and an indication of the desirability of the refined search result.Type: ApplicationFiled: June 13, 2018Publication date: June 20, 2019Applicant: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Publication number: 20190188059Abstract: This document describes techniques and devices for task-related sorting, application discovery, and unified bookmarking for application managers. Through use of an application manager, multiple applications (including standalone applications, instant applications, websites, and other content) that a person can use to accomplish a single task, or multiple related tasks, are sorted into discrete groups for display in the application manager. The application manager can automatically recognize relationships between activities performed with the applications and recognize user actions with the applications that are related to the activities. Based on the relationships and user actions, the application manager can automatically determine that the activities and actions represent a task and display a task group that includes the applications that represent the task.Type: ApplicationFiled: August 24, 2018Publication date: June 20, 2019Applicant: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Publication number: 20190188013Abstract: This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.Type: ApplicationFiled: May 8, 2018Publication date: June 20, 2019Applicant: Google LLCInventors: Golden Gopal Krishna, Carl Magnus Borg, Miroslav Bojic, Henry Owen Newton-Dunn, Jacob M. Klinker, Mindy Pereira, Devin Mancuso, Daniel June Hyung Park, Lily Sin
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Publication number: 20190050115Abstract: In general, techniques are described for enabling a computing device to expand an element associated with an application in order to show different sets of actions associated with the application. The computing device displays a graphical user interface including an interface element associated with the application. The computing device receives an indication of user input. The computing device determines a characteristic of the user input and whether the characteristic is a first characteristic or a second characteristic. The computing device, responsive to determining that the characteristic of the user input is the first characteristic, outputs, for display, a first set of sub-elements or, responsive to determining that the characteristic of the user input is the second characteristic, outputs, for display, a second set of sub-elements. Each sub-element in the first and second sets of sub-elements is associated with unique actions associated with the application.Type: ApplicationFiled: August 11, 2017Publication date: February 14, 2019Inventors: Golden Gopal Krishna, Mindy Pereira, Carl Magnus Borg, Henry Owen Newton-Dunn, Lily Sin, Glen Murphy, Miroslav Bojic