IP Library › Granted Patent US 12,732,387
Granted Patent B2
US 12,732,387 · App. 18/921,622 · Granted Sep 8, 2026

Bot permissions

Inventors: Shelbian Fung (Mountain View, CA); Richard Dunn (Mountain View, CA); Anton Volkov (Mountain View, CA); Adam Rodriguez (Mountain View, CA)
Assignee: Google LLC
H04L9/3271H04L63/10H04L63/168
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Quick Facts
Patent No.
US 12,732,387
App. No.
18/921,622
Granted
Sep 8, 2026
Kind
B2
Abstract

Permission control and management for messaging application bots is described. A method can include providing a messaging application, on a first computing device associated with a first user, to enable communication between the first user and another user, and detecting, at the messaging application, a user request. The method can also include programmatically determining that an action in response to the user request requires access to data associated with the first user, and causing a permission interface to be rendered in the messaging application, the permission interface enabling the first user to approve or prohibit access to the data associated with the first user. The method can include accessing the data associated with the first user and performing the action in response to the user request, upon receiving user input from the first user indicating approval of the access to the data associated with the first user.

Claims (314)

1 . A computer-implemented method comprising:

receiving, by a bot deployed within a messaging application, a prediction from a suggestion machine-learning model;

generating, by the bot, a suggestion to perform a specific action, the generation of the suggestion to perform the specific action based on the prediction from the suggestion machine-learning model;

receiving, by the bot, a request of a user to perform the specific action;

programmatically determining, by the bot, that the specific action requires access to user data associated with the user;

causing, by the bot, a permission interface to be rendered, the permission interface enabling the user to approve access to user data associated with the user;

receiving, by the bot, a user input indicating approval of the access to the user data associated with the user;

responsive to receiving the user input indicating approval of the access to the user data associated with the user, accessing, by the bot, the user data associated with the user;

and

responsive to accessing the user data associated with the user, performing the specific action.

2 . The computer-implemented method of claim 1 , wherein:

the user is a first user;

the specific action is related to a second user; and

the method further comprises:

obtaining, by the bot, permission from the second user to receive one or more messages from the bot; and

sending, by the bot, the one or more messages to the second user to obtain information associated with the specific action,

wherein performing the specific action occurs responsive to receiving, by the bot, the information associated with the specific action from the second user.

3 . The computer-implemented method of claim 1 , wherein the user is a first user, the method further comprising:

obtaining, by the bot, permission from a second user to approve access to user data associated with the second user; and

analyzing, by the bot, one or more messages between the first user and the second user, wherein the suggestion to perform the specific action is determined

based on analyzing the one or more messages.

4 . The computer-implemented method of claim 1 , wherein the user is a first user, the method further comprising:

obtaining, by the bot, permission from a second user to approve access to user data associated with the second user;

receiving, by the bot, an indication from the first user that a conversation between the first user and the second user is confidential; and

abstaining from analysis, by the bot, of the conversation until the first user or the second user reactivates the bot.

5 . The computer-implemented method of claim 1 , wherein the programmatically determining that the specific action requires access to the user data associated with the user is performed by a second machine-learning model, the second machine-learning model taking as an input at least the request of the user for the messaging application to perform the specific action.

6 . The computer-implemented method of claim 1 , wherein:

the suggestion machine-learning model takes as an input at least a content from a device associated with the user;

the content is based on a context of the user; and

the context of the user comprises at least one of information on interactions of the user with one or more other users, one or more external conditions, one or more schedules of the user, or an activity of the user.

7 . The computer-implemented method of claim 1 , further comprising performing, by the bot, the specific action in a particular style.

8 . The computer-implemented method of claim 7 , wherein the particular style comprises one of a formal style, a playful style, a neutral style, or an emoji style.

9 . The computer-implemented method of claim 1 , wherein the messaging application is accessed on a user device, and:

the accessing of the messaging application comprises a virtual implementation of the messaging application; and

the messaging application is implemented on a connected device, the connected device communicatively coupled to the user device.

10 . The computer-implemented method of claim 1 , further comprising, responsive to receiving the user input indicating approval of the access to the user data associated with the user, storing the user data in:

a memory of a user device, wherein the messaging application is accessed on the user device; or

a memory of a connected device, wherein the connected device is communicatively coupled to the user device.

11 . The computer-implemented method of claim 1 , wherein the messaging application is accessed on a user device, wherein the user device is one of:

a camera;

a laptop computer;

a tablet computer;

a mobile telephone;

a wearable device;

a mobile email device;

a portable game player;

a portable music player;

a reader device;

a head-mounted display;

a smartwatch;

a smart wristband;

headphones; or

a first electronic device and a second electronic device, the first electronic device comprising a memory and communicatively coupled to the second electronic device, the second electronic device configured to receive the user input.

12 . The computer-implemented method of claim 1 , wherein the bot is in communication with one or more other messaging applications, the one or more other messaging applications different from the messaging application.

13 . The computer-implemented method of claim 1 , wherein the specific action is an action of a second bot, the second bot different from the bot.

14 . The computer-implemented method of claim 13 , wherein the second bot is not accessed by the messaging application.

15 . The computer-implemented method of claim 1 , wherein the specific action is providing one or more of an information, a travel function, a request for a taxi service, a coaching, a tutoring, an implementation of a game, a commerce action, or an interfacing.

16 . The computer-implemented method of claim 15 , wherein the information is based on an internet search.

17 . The computer-implemented method of claim 15 , wherein the travel function comprises:

a purchase of a ticket; or

a making of a reservation.

18 . The computer-implemented method of claim 15 , wherein the interfacing comprises:

accessing a remote device; and

performing a remote action on the remote device, the remote action on the remote device comprising one or more of:

chatting with the remote device;

retrieving information from the remote device; or

providing instructions to the remote device.

19 . The computer-implemented method of claim 18 , wherein the remote device is a vehicle.

20 . The computer-implemented method of claim 1 , further comprising determining, by the bot, an intent of the user, wherein the suggestion to perform the specific action is further based on the intent of the user.

21 . The computer-implemented method of claim 20 , wherein the determination of the intent of the user is based on a context of a conversation of the user.

22 . The computer-implemented method of claim 1 , further comprising receiving, by the messaging application, a command of the user to access a specific bot from among a plurality of available bots, wherein:

the bot comprises the specific bot from among the plurality of available bots; and

the accessing of the bot is responsive to the command of the user.

23 . The computer-implemented method of claim 22 , wherein the command of the user to access the specific bot from among the plurality of available bots comprises one of a text input or a voice input.

24 . The computer-implemented method of claim 1 , wherein the request of the user to perform the specific action and the user input indicating approval of the access to the user data associated with the user are a same input from the user.

25 . The computer-implemented method of claim 1 , wherein the messaging application comprises a conversation between the user and at least one other person, the method further comprising suggesting, by the messaging application and in the conversation, an invocation of the bot.

26 . The computer-implemented method of claim 1 , wherein the user data is one or more of a location data, a payment information, or a contact information.

27 . The computer-implemented method of claim 26 , wherein:

the user data is the location data; and

the specific action is based on a proximity to a location, the location based on the location data.

28 . The computer-implemented method of claim 27 , wherein the suggestion to perform the specific action comprises a recommendation for a service within the proximity.

29 . The computer-implemented method of claim 1 , wherein the prediction is based at least in part on a natural language processing.

30 . The computer-implemented method of claim 1 , wherein:

the messaging application is accessed on a first user device; and

the suggestion to perform the specific action is a suggested response to a message in the messaging application, the message from a second user device.

31 . The computer-implemented method of claim 1 , wherein the specific action is a translation.

32 . The computer-implemented method of claim 1 , wherein the suggestion to perform the specific action comprises one or more of a text, an image, a link, an emoji, or a multimedia component.

33 . The computer-implemented method of claim 1 , wherein the performing of the specific action by the bot is performed by a module of a user device, wherein the messaging application is accessed on the user device.

34 . The computer-implemented method of claim 33 , wherein the bot is a first bot and the module is a second bot, the second bot:

implemented on the user device; or

implemented on a connected device and accessed on the user device, wherein the connected device is communicatively coupled to the user device.

35 . The computer-implemented method of claim 1 , wherein:

the messaging application is implemented on a user device; and

the bot is accessed on the user device and implemented on a connected device, the connected device communicatively coupled to the user device.

36 . The computer-implemented method of claim 1 , wherein:

the messaging application is implemented on a user device; and

the bot is implemented on the user device.

37 . The computer-implemented method of claim 1 , wherein:

the messaging application is accessed on a user device and implemented on a connected device, the connected device communicatively coupled to the user device; and

the bot is implemented on the user device.

38 . The computer-implemented method of claim 1 , wherein:

the messaging application is accessed on a user device and implemented on a connected device, the connected device communicatively coupled to the user device; and

the bot is accessed on the user device and implemented on the connected device.

39 . A non-transitory computer-readable medium with instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations, the operations comprising:

receiving, by a bot deployed within a messaging application, a prediction from a suggestion machine-learning model;

generating, by the bot, a suggestion to perform a specific action, the generation of the suggestion to perform the specific action based on the prediction from the suggestion machine-learning model;

receiving, by the bot, a request of a user to perform the specific action;

programmatically determining, by the bot, that the specific action requires access to user data associated with the user;

causing, by the bot, a permission interface to be rendered, the permission interface enabling the user to approve access to user data associated with the user;

receiving, by the bot, a user input indicating approval of the access to the user data associated with the first user;

responsive to receiving the user input indicating approval of the access to the user data associated with the user, accessing, by the bot, the user data associated with the user;

and

responsive to accessing the user data associated with the user, performing the specific action.

40 . The non-transitory computer-readable medium of claim 39 , wherein:

the user is a first user;

the specific action is related to a second user; and

the operations further comprise:

obtaining, by the bot, permission from the second user to receive one or more messages from the bot; and

sending, by the bot, the one or more messages to the second user to obtain information associated with the specific action,

wherein performing the specific action occurs responsive to receiving, by the bot, the information associated with the specific action from the second user.

41 . The non-transitory computer-readable medium of claim 39 , wherein the user is a first user and the operations further comprise:

obtaining, by the bot, permission from a second user to approve access to user data associated with the second user; and

analyzing, by the bot, one or more messages between the first user and the second user, wherein the suggestion to perform the specific action is determined based on analyzing the one or more messages.

42 . The non-transitory computer-readable medium of claim 39 , wherein the user is a first user and the operations further comprise:

obtaining, by the bot, permission from a second user to approve access to user data associated with the second user;

receiving, by the bot, an indication from the first user that a conversation between the first user and the second user is confidential; and

abstaining from analysis, by the bot, of the conversation until the first user or the second user reactivates the bot.

43 . The non-transitory computer-readable medium of claim 39 , wherein the programmatically determining that the specific action requires access to the user data associated with the user is performed by a second machine-learning model, the second machine-learning model taking as an input at least the request of the user for the messaging application to perform the specific action.

44 . The non-transitory computer-readable medium of claim 39 , wherein:

the suggestion machine-learning model takes as an input at least a content from a device associated with the user;

the content is based on a context of the user; and

the context of the user comprises at least one of information on interactions of the user with one or more other users, one or more external conditions, one or more schedules of the user, or an activity of the user.

45 . The non-transitory computer-readable medium of claim 39 , wherein the operations further comprise performing, by the bot, the specific action in a particular style.

46 . The non-transitory computer-readable medium of claim 45 , wherein the particular style comprises one of a formal style, a playful style, a neutral style, or an emoji style.

47 . The non-transitory computer-readable medium of claim 39 , wherein the messaging application is accessed on a user device, and:

the accessing of the messaging application comprises a virtual implementation of the messaging application; and

the messaging application is implemented on a connected device, the connected device communicatively coupled to the user device.

48 . The non-transitory computer-readable medium of claim 39 , wherein the operations further comprise, responsive to receiving the user input indicating approval of the access to the user data associated with the user, storing the user data:

in the non-transitory computer-readable medium, wherein the messaging application is accessed on a user device; or

in a memory of a connected device, wherein the connected device is communicatively coupled to the user device.

49 . The non-transitory computer-readable medium of claim 39 , wherein the messaging application is accessed on a user device, wherein the user device is one of:

a camera;

a laptop computer;

a tablet computer;

a mobile telephone;

a wearable device;

a mobile email device;

a portable game player;

a portable music player;

a reader device;

a head-mounted display;

a smartwatch;

a smart wristband;

headphones; or

a first electronic device and a second electronic device, the first electronic device comprising a memory and communicatively coupled to the second electronic device, the second electronic device configured to receive the user input.

50 . The non-transitory computer-readable medium of claim 39 , wherein the bot is in communication with one or more other messaging applications, the one or more other messaging applications different from the messaging application.

51 . The non-transitory computer-readable medium of claim 39 , wherein the specific action is an action of a second bot, the second bot different from the bot.

52 . The non-transitory computer-readable medium of claim 51 , wherein the second bot is not accessed by the messaging application.

53 . The non-transitory computer-readable medium of claim 39 , wherein the specific action is providing one or more of an information, a travel function, a request for a taxi service, a coaching, a tutoring, an implementation of a game, a commerce action, or an interfacing.

54 . The non-transitory computer-readable medium of claim 53 , wherein the information is based on an internet search.

55 . The non-transitory computer-readable medium of claim 53 , wherein the travel function comprises:

a purchase of a ticket; or

a making of a reservation.

56 . The non-transitory computer-readable medium of claim 53 , wherein the interfacing comprises:

accessing a remote device; and

performing a remote action on the remote device, the remote action on the remote device comprising one or more of:

chatting with the remote device;

retrieving information from the remote device; or

providing instructions to the remote device.

57 . The non-transitory computer-readable medium of claim 56 , wherein the remote device is a vehicle.

58 . The non-transitory computer-readable medium of claim 39 , wherein the operations further comprise determining, by the bot, an intent of the user, wherein the suggestion to perform the specific action is further based on the intent of the user.

59 . The non-transitory computer-readable medium of claim 58 , wherein the determination of the intent of the user is based on a context of a conversation of the user.

60 . The non-transitory computer-readable medium of claim 39 , wherein the operations further comprise receiving, by the messaging application, a command of the user to access a specific bot from among a plurality of available bots, wherein:

the bot comprises the specific bot from among the plurality of available bots; and

the accessing of the bot is responsive to the command of the user.

61 . The non-transitory computer-readable medium of claim 60 , wherein the command of the user to access the specific bot from among the plurality of available bots comprises one of a text input or a voice input.

62 . The non-transitory computer-readable medium of claim 39 , wherein the request of the user to perform the specific action and the user input indicating approval of the access to the user data associated with the user are a same input from the user.

63 . The non-transitory computer-readable medium of claim 39 , wherein:

the messaging application comprises a conversation between the user and at least one other person; and

the instructions further cause the one or more processors to suggest, by the messaging application and in the conversation, an invocation of the bot.

64 . The non-transitory computer-readable medium of claim 39 , wherein the user data is one or more of a location data, a payment information, or a contact information.

65 . The non-transitory computer-readable medium of claim 64 , wherein:

the user data is the location data; and

the specific action is based on a proximity to a location, the location based on the location data.

66 . The non-transitory computer-readable medium of claim 65 , wherein the suggestion to perform the specific action comprises a recommendation for a service within the proximity.

67 . The non-transitory computer-readable medium of claim 39 , wherein the prediction is based at least in part on a natural language processing.

68 . The non-transitory computer-readable medium of claim 39 , wherein:

the messaging application is accessed on a first user device; and

the suggestion to perform the specific action is a suggested response to a message in the messaging application, the message from a second user device.

69 . The non-transitory computer-readable medium of claim 39 , wherein the specific action is a translation.

70 . The non-transitory computer-readable medium of claim 39 , wherein the suggestion to perform the specific action comprises one or more of a text, an image, a link, an emoji, or a multimedia component.

71 . The non-transitory computer-readable medium of claim 39 , wherein the performing of the specific action by the bot is performed by a module of a user device, wherein the messaging application is accessed on the user device.

72 . The non-transitory computer-readable medium of claim 71 , wherein the bot is a first bot and the module is a second bot, the second bot:

implemented on the user device; or

implemented on a connected device and accessed on the user device, wherein the connected device is communicatively coupled to the user device.

73 . The non-transitory computer-readable medium of claim 39 , wherein:

the messaging application is implemented on a user device; and

the bot is accessed on the user device and implemented on a connected device, the connected device communicatively coupled to the user device.

74 . The non-transitory computer-readable medium of claim 39 , wherein:

the messaging application is implemented on a user device; and

the bot is implemented on the user device.

75 . The non-transitory computer-readable medium of claim 39 , wherein:

the messaging application is accessed on a user device and implemented on a connected device, the connected device communicatively coupled to the user device; and

the bot is implemented on the user device.

76 . The non-transitory computer-readable medium of claim 39 , wherein:

the messaging application is accessed on a user device and implemented on a connected device, the connected device communicatively coupled to the user device; and

the bot is accessed on the user device and implemented on the connected device.

77 . A system comprising:

one or more processors; and

a memory coupled to the one or more processors that stores instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving, by a bot deployed within a messaging application, a prediction from a suggestion machine-learning model;

generating, by the bot, a suggestion to perform a specific action, the generation of the suggestion to perform the specific action based on the prediction from the suggestion machine-learning model;

receiving, by the bot, a request of a user to perform the specific action;

programmatically determining, by the bot, that the specific action requires access to user data associated with the user;

causing, by the bot, a permission interface to be rendered, the permission interface enabling the user to approve access to user data associated with the user;

receiving, by the bot, a user input indicating approval of the access to the user data associated with the first user;

responsive to receiving the user input indicating approval of the access to the user data associated with the user, accessing, by the bot, the user data associated with the user; and

responsive to accessing the user data associated with the user, performing the specific action.

78 . The system of claim 77 , wherein:

the user is a first user;

the specific action is related to a second user; and

the operations further comprise:

obtaining, by the bot, permission from the second user to receive one or more messages from the bot; and

sending, by the bot, the one or more messages to the second user to obtain information associated with the specific action,

wherein performing the specific action occurs responsive to receiving, by the bot, the information associated with the specific action from the second user.

79 . The system of claim 77 , wherein the user is a first user, the operations further comprising:

obtaining, by the bot, permission from a second user to approve access to user data associated with the second user; and

analyzing, by the bot, one or more messages between the first user and the second user, wherein the

suggestion to perform the specific action is determined based on analyzing the one or more messages.

80 . The system of claim 77 , the operations further comprising:

obtaining, by the bot, permission from a second user to approve access to user data associated with the second user;

receiving, by the bot, an indication from the user that a conversation between the user and the second user is confidential; and

abstaining from analysis, by the bot, of the conversation until the user or the second user reactivates the bot.

81 . The system of claim 77 , wherein the programmatically determining that the specific action requires access to the user data associated with the user is performed by a second machine-learning model, the second machine-learning model taking as an input at least the request of the user for the messaging application to perform the specific action.

82 . The system of claim 77 , wherein:

the suggestion machine-learning model takes as an input at least a content from a device associated with the user;

the content is based on a context of the user; and

the context of the user comprises at least one of information on interactions of the user with one or more other users, one or more external conditions, one or more schedules of the user, or an activity of the user.

83 . The system of claim 77 , the operations further comprising performing, by the bot, the specific action in a particular style.

84 . The system of claim 83 , wherein the particular style comprises one of a formal style, a playful style, a neutral style, or an emoji style.

85 . The system of claim 77 , wherein the messaging application is accessed on the system, and:

the accessing of the messaging application comprises a virtual implementation of the messaging application; and

the messaging application is implemented on a connected device, the connected device communicatively coupled to the system.

86 . The system of claim 77 , the operations further comprising, responsive to receiving the user input indicating approval of the access to the user data associated with the user, storing the user data in:

the memory of the system, wherein the messaging application is accessed on the system; or

a memory of a connected device, wherein the connected device is communicatively coupled to the system.

87 . The system of claim 77 , wherein the messaging application is accessed on the system, wherein the system is one of:

a camera;

a laptop computer;

a tablet computer;

a mobile telephone;

a wearable device;

a mobile email device;

a portable game player payer;

a portable music player;

a reader device;

a head-mounted display;

a smartwatch;

a smart wristband;

headphones; or

a first electronic device and a second electronic device, the first electronic device comprising the memory and communicatively coupled to the second electronic device, the second electronic device configured to receive the user input.

88 . The system of claim 77 , wherein the bot is in communication with one or more other messaging applications, the one or more other messaging applications different from the messaging application.

89 . The system of claim 77 , wherein the specific action is an action of a second bot, the second bot different from the bot.

90 . The system of claim 89 , wherein the second bot is not accessed by the messaging application.

91 . The system of claim 77 , wherein the specific action is providing one or more of an information, a travel function, a request for a taxi service, a coaching, a tutoring, an implementation of a game, a commerce action, or an interfacing.

92 . The system of claim 91 , wherein the information is based on an internet search.

93 . The system of claim 91 , wherein the travel function comprises:

a purchase of a ticket; or

a making of a reservation.

94 . The system of claim 91 , wherein the interfacing comprises:

accessing a remote device; and

performing a remote action on the remote device, the remote action on the remote device comprising one or more of:

chatting with the remote device;

retrieving information from the remote device; or

providing instructions to the remote device.

95 . The system of claim 94 , wherein the remote device is a vehicle.

96 . The system of claim 77 , wherein the instructions further cause the one or more processors to determine, by the bot, an intent of the user, wherein the suggestion to perform the specific action is further based on the intent of the user.

97 . The system of claim 96 , wherein the determination of the intent of the user is based on a context of a conversation of the user.

98 . The system of claim 77 , wherein:

the instructions further cause the one or more processors to receive, by the messaging application, a command of the user to access a specific bot from among a plurality of available bots;

the bot comprises the specific bot from among the plurality of available bots; and

the accessing of the bot is responsive to the command of the user.

99 . The system of claim 98 , wherein the command of the user to access the specific bot from among the plurality of available bots comprises one of a text input or a voice input.

100 . The system of claim 77 , wherein the request of the user to perform the specific action and the user input indicating approval of the access to the user data associated with the user are a same input from the user.

101 . The system of claim 77 , wherein:

the messaging application comprises a conversation between the user and at least one other person; and

the instructions further cause the one or more processors to suggest, by the messaging application and in the conversation, an invocation of the bot.

102 . The system of claim 77 , wherein the user data is one or more of a location data, a payment information, or a contact information.

103 . The system of claim 102 , wherein:

the user data is the location data; and

the specific action is based on a proximity to a location, the location based on the location data.

104 . The system of claim 103 , wherein the suggestion to perform the specific action comprises a recommendation for a service within the proximity.

105 . The system of claim 77 , wherein the prediction is based at least in part on a natural language processing.

106 . The system of claim 77 , wherein:

the messaging application is accessed on the system; and

the suggestion to perform the specific action is a suggested response to a message in the messaging application, the message from a second user device.

107 . The system of claim 77 , wherein the specific action is a translation.

108 . The system of claim 77 , wherein the suggestion to perform the specific action comprises one or more of a text, an image, a link, an emoji, or a multimedia component.

109 . The system of claim 77 , further comprising one or more modules and wherein the performing of the specific action by the bot is performed by one of the one or more modules of the system, wherein the messaging application is accessed on the system, the module being different than the bot.

110 . The system of claim 109 , wherein the bot is a first bot and the one of the one or more modules is a second bot, the second bot:

implemented on the system; or

implemented on a connected device and accessed on the system, wherein the connected device is communicatively coupled to the system.

111 . The system of claim 77 , wherein:

the messaging application is implemented on the system; and

the bot is accessed on the system and implemented on a connected device, the connected device communicatively coupled to the system.

112 . The system of claim 77 , wherein:

the messaging application is implemented on the system; and

the bot is implemented on the system.

113 . The system of claim 77 , wherein:

the messaging application is accessed on the system and implemented on a connected device, the connected device communicatively coupled to the system; and

the bot is implemented on the system.

114 . The system of claim 77 , wherein:

the messaging application is accessed on the system and implemented on a connected device, the connected device communicatively coupled to the system; and

the bot is accessed on the system and implemented on the connected device.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 21, 2024
From: FUNG, SHELBIAN; RODRIGUEZ, ADAM; VOLKOV, ANTON; DUNN, RICHARD
To: GOOGLE LLC
Reel/Frame 068957/0295 →
Continuity (6)
Continuation 18327459 · Jun 1, 2023
Continuation 17732778 · Apr 29, 2022
Continuation 16695967 · Nov 26, 2019
Continuation 15709440 · Sep 19, 2017
Provisional Application 62397047 · Sep 20, 2016
Related Publication 20250047508A1 · Feb 6, 2025
References Cited (291)
US 5963649A · Sako · 1999 [cited by applicant]
US 6092102A · Wagner · 2000 [cited by applicant]
US D599363S · Mays · 2009 [cited by applicant]
US 7603413B1 · Herold et al. · 2009 [cited by applicant]
US D611053S · Kanga et al. · 2010 [cited by applicant]
US D624927S · Allen et al. · 2010 [cited by applicant]
US D648343S · Chen · 2011 [cited by applicant]
US D648735S · Arnold et al. · 2011 [cited by applicant]
US D651609S · Pearson et al. · 2012 [cited by applicant]
US D658201S · Gleasman et al. · 2012 [cited by applicant]
US D658677S · Gleasman et al. · 2012 [cited by applicant]
US D658678S · Gleasman et al. · 2012 [cited by applicant]
US D673172S · Peters et al. · 2012 [cited by applicant]
US 8391618B1 · Chuang et al. · 2013 [cited by applicant]
US 8423577B1 · Lee et al. · 2013 [cited by applicant]
US 8515958B2 · Knight · 2013 [cited by applicant]
US 8554701B1 · Dillard et al. · 2013 [cited by applicant]
US 8589407B2 · Bhatia · 2013 [cited by applicant]
US D695755S · Hwang et al. · 2013 [cited by applicant]
US D699739S · Voreis et al. · 2014 [cited by applicant]
US D699744S · Ho Kushner et al. · 2014 [cited by applicant]
US 8645697B1 · Emigh et al. · 2014 [cited by applicant]
US 8650210B1 · Cheng et al. · 2014 [cited by applicant]
US D701228S · Lee · 2014 [cited by applicant]
US D701527S · Brinda et al. · 2014 [cited by applicant]
US D701528S · Brinda et al. · 2014 [cited by applicant]
US 8688698B1 · Black et al. · 2014 [cited by applicant]
US 8700480B1 · Fox et al. · 2014 [cited by applicant]
US D704726S · Maxwell · 2014 [cited by applicant]
US D705244S · Arnold et al. · 2014 [cited by applicant]
US D705251S · Pearson et al. · 2014 [cited by applicant]
US D705802S · Kerr et al. · 2014 [cited by applicant]
US D706802S · Myung et al. · 2014 [cited by applicant]
US 8825474B1 · Zhai et al. · 2014 [cited by applicant]
US D714821S · Chand et al. · 2014 [cited by applicant]
US D716338S · Lee · 2014 [cited by applicant]
US 8938669B1 · Cohen · 2015 [cited by applicant]
US 8996639B1 · Faaborg et al. · 2015 [cited by applicant]
US 9020956B1 · Barr et al. · 2015 [cited by applicant]
US 9191786B2 · Davis · 2015 [cited by applicant]
US 9213941B2 · Petersen · 2015 [cited by applicant]
US 9230241B1 · Singh et al. · 2016 [cited by applicant]
US 9262517B2 · Feng et al. · 2016 [cited by applicant]
US 9467435B1 · Tyler et al. · 2016 [cited by applicant]
US 9560152B1 · Jamdar et al. · 2017 [cited by applicant]
US 9674120B2 · Davis · 2017 [cited by applicant]
US 9715496B1 · Sapoznik et al. · 2017 [cited by applicant]
US 9805371B1 · Sapoznik et al. · 2017 [cited by applicant]
US 9807037B1 · Sapoznik et al. · 2017 [cited by applicant]
US 9817813B2 · Faizakof et al. · 2017 [cited by applicant]
US 9973705B2 · Kinugawa et al. · 2018 [cited by applicant]
US 10146748B1 · Barndollar et al. · 2018 [cited by applicant]
US 11336467B2 · Fung et al. · 2022 [cited by applicant]
US 11700134B2 · Fung et al. · 2023 [cited by applicant]
US 12126739B2 · Fung et al. · 2024 [cited by applicant]
US 20020040297A1 · Tsiao et al. · 2002 [cited by applicant]
US 20020103837A1 · Balchandran et al. · 2002 [cited by applicant]
US 20030105589A1 · Liu et al. · 2003 [cited by applicant]
US 20030182374A1 · Haldar · 2003 [cited by applicant]
US 20060021023A1 · Stewart et al. · 2006 [cited by applicant]
US 20060029106A1 · Ott et al. · 2006 [cited by applicant]
US 20060150119A1 · Chesnais et al. · 2006 [cited by applicant]
US 20060156209A1 · Matsuura et al. · 2006 [cited by applicant]
US 20060172749A1 · Sweeney · 2006 [cited by applicant]
US 20070030364A1 · Obrador et al. · 2007 [cited by applicant]
US 20070094217A1 · Ronnewinkel · 2007 [cited by applicant]
US 20070162942A1 · Hamynen et al. · 2007 [cited by applicant]
US 20070244980A1 · Baker et al. · 2007 [cited by applicant]
US 20080086522A1 · Biggs · 2008 [cited by examiner]
US 20080114837A1 · Biggs · 2008 [cited by examiner]
US 20080120371A1 · Gopal · 2008 [cited by applicant]
US 20080153526A1 · Othmer · 2008 [cited by applicant]
US 20080189367A1 · Okumura · 2008 [cited by applicant]
US 20090076795A1 · Bagalore et al. · 2009 [cited by applicant]
US 20090119584A1 · Herbst · 2009 [cited by applicant]
US 20090282114A1 · Feng et al. · 2009 [cited by applicant]
US 20100077029A1 · Shook et al. · 2010 [cited by applicant]
US 20100228590A1 · Muller et al. · 2010 [cited by applicant]
US 20100260426A1 · Huang et al. · 2010 [cited by applicant]
US 20110074685A1 · Causey et al. · 2011 [cited by applicant]
US 20110107223A1 · Tilton et al. · 2011 [cited by applicant]
US 20110164163A1 · Bilbrey et al. · 2011 [cited by applicant]
US 20110252108A1 · Morris et al. · 2011 [cited by applicant]
US 20120030289A1 · Buford et al. · 2012 [cited by applicant]
US 20120033876A1 · Momeyer et al. · 2012 [cited by applicant]
US 20120041941A1 · King et al. · 2012 [cited by applicant]
US 20120041973A1 · Kim et al. · 2012 [cited by applicant]
US 20120042036A1 · Lau et al. · 2012 [cited by applicant]
US 20120089847A1 · Tu et al. · 2012 [cited by applicant]
US 20120096097A1 · Morinaga et al. · 2012 [cited by applicant]
US 20120131520A1 · Tang et al. · 2012 [cited by applicant]
US 20120179717A1 · Kennedy et al. · 2012 [cited by applicant]
US 20120224743A1 · Rodriguez et al. · 2012 [cited by applicant]
US 20120239761A1 · Linner et al. · 2012 [cited by applicant]
US 20120245944A1 · Gruber et al. · 2012 [cited by applicant]
US 20120278164A1 · Spivack et al. · 2012 [cited by applicant]
US 20130036162A1 · Koenigs · 2013 [cited by applicant]
US 20130050507A1 · Syed et al. · 2013 [cited by applicant]
US 20130061148A1 · Das et al. · 2013 [cited by applicant]
US 20130073366A1 · Heath · 2013 [cited by applicant]
US 20130144961A1 · Park et al. · 2013 [cited by applicant]
US 20130260727A1 · Knudson et al. · 2013 [cited by applicant]
US 20130262574A1 · Cohen · 2013 [cited by applicant]
US 20130346235A1 · Lam · 2013 [cited by applicant]
US 20140004889A1 · Davis · 2014 [cited by applicant]
US 20140012927A1 · Gertzfield et al. · 2014 [cited by applicant]
US 20140035846A1 · Lee et al. · 2014 [cited by applicant]
US 20140047413A1 · Sheive et al. · 2014 [cited by applicant]
US 20140067371A1 · Liensberger · 2014 [cited by applicant]
US 20140088954A1 · Shirzadi et al. · 2014 [cited by applicant]
US 20140108562A1 · Panzer · 2014 [cited by applicant]
US 20140150068A1 · Janzer · 2014 [cited by applicant]
US 20140163954A1 · Joshi et al. · 2014 [cited by applicant]
US 20140164506A1 · Tesch et al. · 2014 [cited by applicant]
US 20140164953A1 · Lynch et al. · 2014 [cited by applicant]
US 20140171133A1 · Stuttle et al. · 2014 [cited by applicant]
US 20140189027A1 · Zhang et al. · 2014 [cited by applicant]
US 20140189538A1 · Martens et al. · 2014 [cited by applicant]
US 20140195621A1 · Rao Dv · 2014 [cited by applicant]
US 20140201675A1 · Joo et al. · 2014 [cited by applicant]
US 20140228009A1 · Chen et al. · 2014 [cited by applicant]
US 20140237057A1 · Khodorenko · 2014 [cited by applicant]
US 20140317030A1 · Shen et al. · 2014 [cited by applicant]
US 20140337438A1 · Govande et al. · 2014 [cited by applicant]
US 20140344058A1 · Brown · 2014 [cited by applicant]
US 20140372349A1 · Driscoll · 2014 [cited by applicant]
US 20150006143A1 · Skiba et al. · 2015 [cited by applicant]
US 20150032724A1 · Thirugnanasundaram et al. · 2015 [cited by applicant]
US 20150058720A1 · Smadja et al. · 2015 [cited by applicant]
US 20150088998A1 · Isensee et al. · 2015 [cited by applicant]
US 20150095855A1 · Bai et al. · 2015 [cited by applicant]
US 20150100537A1 · Grieves et al. · 2015 [cited by applicant]
US 20150171133A1 · Kim et al. · 2015 [cited by applicant]
US 20150178371A1 · Seth et al. · 2015 [cited by applicant]
US 20150178388A1 · Winnemoeller et al. · 2015 [cited by applicant]
US 20150207765A1 · Brantingham et al. · 2015 [cited by applicant]
US 20150227797A1 · Ko et al. · 2015 [cited by applicant]
US 20150244653A1 · Niu et al. · 2015 [cited by applicant]
US 20150248411A1 · Krinker et al. · 2015 [cited by applicant]
US 20150250936A1 · Thomas et al. · 2015 [cited by applicant]
US 20150286371A1 · Degani · 2015 [cited by applicant]
US 20150288633A1 · Ogundokun et al. · 2015 [cited by applicant]
US 20150302301A1 · Petersen · 2015 [cited by applicant]
US 20150347769A1 · Espinosa et al. · 2015 [cited by applicant]
US 20150350117A1 · Bastide et al. · 2015 [cited by applicant]
US 20160037311A1 · Cho · 2016 [cited by applicant]
US 20160042252A1 · Sawhney et al. · 2016 [cited by applicant]
US 20160043974A1 · Purcell et al. · 2016 [cited by applicant]
US 20160065519A1 · Waltermann et al. · 2016 [cited by applicant]
US 20160072737A1 · Forster · 2016 [cited by applicant]
US 20160140447A1 · Cohen et al. · 2016 [cited by applicant]
US 20160140477A1 · Karanam et al. · 2016 [cited by applicant]
US 20160162791A1 · Petersen · 2016 [cited by applicant]
US 20160179816A1 · Glover · 2016 [cited by applicant]
US 20160210279A1 · Kim et al. · 2016 [cited by applicant]
US 20160224524A1 · Kay et al. · 2016 [cited by applicant]
US 20160226804A1 · Hampson et al. · 2016 [cited by applicant]
US 20160234553A1 · Hampson et al. · 2016 [cited by applicant]
US 20160283454A1 · Leydon et al. · 2016 [cited by applicant]
US 20160284011A1 · Dong et al. · 2016 [cited by applicant]
US 20160342895A1 · Gao et al. · 2016 [cited by applicant]
US 20160350304A1 · Aggarwal et al. · 2016 [cited by applicant]
US 20160352656A1 · Galley et al. · 2016 [cited by applicant]
US 20160378080A1 · Uppala et al. · 2016 [cited by applicant]
US 20170075878A1 · Jon et al. · 2017 [cited by applicant]
US 20170093769A1 · Lind et al. · 2017 [cited by applicant]
US 20170098122A1 · El Kaliouby et al. · 2017 [cited by applicant]
US 20170118152A1 · Lee · 2017 [cited by applicant]
US 20170134316A1 · Cohen et al. · 2017 [cited by applicant]
US 20170142046A1 · Mahmoud et al. · 2017 [cited by applicant]
US 20170149703A1 · Willett et al. · 2017 [cited by applicant]
US 20170153792A1 · Kapoor et al. · 2017 [cited by applicant]
US 20170171117A1 · Carr et al. · 2017 [cited by applicant]
US 20170180276A1 · Gershony et al. · 2017 [cited by applicant]
US 20170180294A1 · Milligan et al. · 2017 [cited by applicant]
US 20170187654A1 · Lee · 2017 [cited by applicant]
US 20170250930A1 · Ben-itzhak · 2017 [cited by applicant]
US 20170250935A1 · Rosenberg · 2017 [cited by applicant]
US 20170250936A1 · Rosenberg · 2017 [cited by examiner]
US 20170293834A1 · Raison et al. · 2017 [cited by applicant]
US 20170308589A1 · Liu et al. · 2017 [cited by applicant]
US 20170324868A1 · Tamblyn et al. · 2017 [cited by applicant]
US 20170339076A1 · Patil · 2017 [cited by applicant]
US 20170344224A1 · Kay et al. · 2017 [cited by applicant]
US 20170357442A1 · Peterson et al. · 2017 [cited by applicant]
US 20180004397A1 · Mazzocchi · 2018 [cited by applicant]
US 20180005272A1 · Todasco et al. · 2018 [cited by applicant]
US 20180005288A1 · Delaney · 2018 [cited by examiner]
US 20180012231A1 · Sapoznik et al. · 2018 [cited by applicant]
US 20180013699A1 · Sapoznik et al. · 2018 [cited by applicant]
US 20180060705A1 · Mahmoud et al. · 2018 [cited by applicant]
US 20180083894A1 · Fung et al. · 2018 [cited by applicant]
US 20180083898A1 · Pham · 2018 [cited by applicant]
US 20180083901A1 · Mcgregor et al. · 2018 [cited by applicant]
US 20180090135A1 · Schlesinger et al. · 2018 [cited by applicant]
US 20180137097A1 · Su-min et al. · 2018 [cited by applicant]
US 20180196854A1 · Burks · 2018 [cited by applicant]
US 20180210874A1 · Fuxman et al. · 2018 [cited by applicant]
US 20180293601A1 · Glazier · 2018 [cited by applicant]
US 20180309706A1 · Yu-na et al. · 2018 [cited by applicant]
US 20180316637A1 · Desjardins · 2018 [cited by applicant]
US 20180322403A1 · Ron et al. · 2018 [cited by applicant]
US 20180336226A1 · Anorga et al. · 2018 [cited by applicant]
US 20180336415A1 · Anorga et al. · 2018 [cited by applicant]
US 20180367483A1 · Rodriguez et al. · 2018 [cited by applicant]
US 20180367484A1 · Rodriguez et al. · 2018 [cited by applicant]
US 20180373683A1 · Hullette et al. · 2018 [cited by applicant]
US 20200099538A1 · Fung et al. · 2020 [cited by applicant]
US 20220255760A1 · Fung et al. · 2022 [cited by applicant]
US 20230379173A1 · Fung et al. · 2023 [cited by applicant]
CN 1475908 · 2004 [cited by applicant]
CN 102222079 · 2011 [cited by applicant]
CN 102395966 · 2012 [cited by applicant]
CN 102467574 · 2012 [cited by applicant]
CN 103226949 · 2013 [cited by applicant]
CN 103548025 · 2014 [cited by applicant]
CN 104951428 · 2015 [cited by applicant]
CN 105068661 · 2015 [cited by applicant]
CN 105141503 · 2015 [cited by applicant]
CN 105306281 · 2016 [cited by applicant]
CN 105830104 · 2016 [cited by applicant]
EP 1376392 · 2004 [cited by applicant]
EP 1394713 · 2004 [cited by applicant]
EP 2523436 · 2012 [cited by applicant]
EP 2560104 · 2013 [cited by applicant]
EP 2688014 · 2014 [cited by applicant]
EP 2703980 · 2014 [cited by applicant]
EP 3091445 · 2016 [cited by applicant]
JP 2002132804 · 2002 [cited by applicant]
JP 2014086088 · 2014 [cited by applicant]
JP 2014142919 · 2014 [cited by applicant]
KR 20110003462 · 2011 [cited by applicant]
KR 20130008036 · 2013 [cited by applicant]
KR 20130061387 · 2013 [cited by applicant]
WO 2004104758 · 2004 [cited by applicant]
WO 2011002989 · 2011 [cited by applicant]
WO 2015183493 · 2015 [cited by applicant]
WO 2016130788 · 2016 [cited by applicant]
WO 2018039092A1 · 2018 [cited by applicant]
WO 2018089109 · 2018 [cited by applicant]
“Examination Report”, AU Application No. 2015214298, Apr. 24, 2017, 3 pages. [cited by applicant]
“Examination Report”, AU Application No. 2015214298, Nov. 2, 2017, 3 pages. [cited by applicant]
“Extended European Search Report”, EP Application No. 15746410.8, Sep. 5, 2017, 7 pages. [cited by applicant]
“Final Office Action”, U.S. Appl. No. 16/999,702, filed Feb. 1, 2022, 15 pages. [cited by applicant]
“Final Office Action”, U.S. Appl. No. 15/386,760, filed May 30, 2019, 12 pages. [cited by applicant]
“Final Office Action”, U.S. Appl. No. 15/386,162, filed Jun. 5, 2019, 12 pages. [cited by applicant]
“Final Office Action”, U.S. Appl. No. 15/238,304, filed Nov. 23, 2018, 13 pages. [cited by applicant]
“First Action Interview Office Action”, U.S. Appl. No. 15/624,637, filed Jan. 25, 2019, 3 pages. [cited by applicant]
“First Action Interview Office Action”, U.S. Appl. No. 15/386,760, filed Jan. 30, 2019, 4 pages. [cited by applicant]
“First Action Interview Office Action”, U.S. Appl. No. 16/999,702, filed Sep. 28, 2021, 3 pages. [cited by applicant]
“First Action Interview Office Action”, U.S. Appl. No. 16/695,967, filed Sep. 30, 2021, 4 pages. [cited by applicant]
“First Action Interview Office Action”, U.S. Appl. No. 15/350,040, filed Oct. 30, 2018, 4 pages. [cited by applicant]
“First Action Interview Office Action”, U.S. Appl. No. 16/003,661, filed Dec. 14, 2018, 12 pages. [cited by applicant]
“Foreign Notice of Allowance”, CN Application No. 201680070359.3, Jul. 5, 2021, 4 pages. [cited by applicant]
“Foreign Notice of Allowance”, CN Application No. 201780056982.8, Jul. 13, 2021, 4 pages. [cited by applicant]
“Foreign Notice of Allowance”, KR Application No. 10-2019-7020465, Aug. 5, 2020, 5 pages. [cited by applicant]
“Foreign Notice of Allowance”, JP Application No. 2018-532399, Sep. 23, 2020, 2 pages. [cited by applicant]
“Foreign Office Action”, KR Application No. 10-2018-7019756, Jan. 17, 2020, 8 pages. [cited by applicant]
“Foreign Office Action”, JP Application No. 2018-532399, Mar. 10, 2020, 9 pages. [cited by applicant]
“Foreign Office Action”, EP Application No. 16825663.4, Apr. 16, 2019, 5 pages. [cited by applicant]
“Foreign Office Action”, EP Application No. 16825666.7, Apr. 23, 2019, 6 pages. [cited by applicant]
“Foreign Office Action”, KR Application No. 10-2019-7011687, May 7, 2019, 5 pages. [cited by applicant]
“Foreign Office Action”, KR Application No. 10-2018-7013953, May 8, 2019, 8 pages. [cited by applicant]
“Foreign Office Action”, KR Application No. 10-2018-7019756, May 13, 2019, 17 pages. [cited by applicant]
“Foreign Office Action”, CN Application No. 201680070359.3, Jun. 3, 2020, 22 pages. [cited by applicant]
“Foreign Office Action”, KR Application No. 10-2018-7013953, Jun. 13, 2019, 8 pages. [cited by applicant]
“Foreign Office Action”, JP Application No. 2018-532399, Jun. 16, 2020, 5 pages. [cited by applicant]
“Foreign Office Action”, IN Application No. 201847014172, Jun. 17, 2020, 7 pages. [cited by applicant]
“Foreign Office Action”, EP Application No. 16825666.7, Jun. 18, 2020, 6 pages. [cited by applicant]
“Foreign Office Action”, KR Application No. 10-2019-7020465, Jun. 29, 2020, 7 pages. [cited by applicant]
“Foreign Office Action”, JP Application No. 2018-532399, Jul. 23, 2019, 12 pages. [cited by applicant]
“Foreign Office Action”, KR Application No. 10-2018-7013953, Oct. 29, 2018, 10 pages. [cited by applicant]
“Foreign Office Action”, CN Application No. 201580016692.1, Nov. 2, 2018, 16 pages. [cited by applicant]
“Foreign Office Action”, CN Application No. 201780056982.8, Nov. 19, 2020, 22 pages. [cited by applicant]
“Intent to Grant”, EP Application No. 16825666.7, Oct. 18, 2021, 6 pages. [cited by applicant]
“International Preliminary Report on Patentability”, Application No. PCT/US2017/046858, Feb. 19, 2019, 7 pages. [cited by applicant]
“International Preliminary Report on Patentability”, Application No. PCT/US2017/052349, Mar. 26, 2019, 7 pages. [cited by applicant]
“International Preliminary Report on Patentability”, Application No. PCT/US2016/068083, Jun. 26, 2018, 10 pages. [cited by applicant]
“International Preliminary Report on Patentability”, Application No. PCT/US2017/052333, Dec. 4, 2018, 15 pages. [cited by applicant]
“International Preliminary Report on Patentability”, Application No. PCT/US2018/022501, Dec. 17, 2019, 7 pages. [cited by applicant]
“International Search Report”, Application No. PCT/US2017/057044, Jan. 18, 2018, 5 pages. [cited by applicant]
“International Search Report”, Application No. PCT/US2018/022501, May 14, 2018, 4 pages. [cited by applicant]
“International Search Report”, Application No. PCT/US2018/022503, Aug. 16, 2018, 6 pages. [cited by applicant]
“International Search Report”, Application No. PCT/US2017/052713, Dec. 5, 2017, 4 pages. [cited by applicant]
“International Search Report”, Application No. PCT/US2017/052349, Dec. 13, 2017, 5 pages. [cited by applicant]
“International Search Report and Written Opinion”, Application No. PCT/US2016/068083, Mar. 9, 2017, 13 pages. [cited by applicant]
“International Search Report and Written Opinion”, Application No. PCT/US2015/014414, May 11, 2015, 8 pages. [cited by applicant]
“International Search Report and Written Opinion”, Application No. PCT/US2018/021028, Jun. 15, 2018, 11 pages. [cited by applicant]
“International Search Report and Written Opinion”, Application No. PCT/US2017/046858, Oct. 11, 2017, 10 pages. [cited by applicant]
“International Search Report and Written Opinion”, Application No. PCT/US2017/052333, Nov. 30, 2017, 15 pages. [cited by applicant]
“Foreign Office Action”, DE Application No. 112017003594.5, Jun. 25, 2025, 15 pages. [cited by applicant]