DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Action is FINAL and is in response to the claims filed August 7, 2026. Claims 1-6, 8-14, and 16-22 are currently pending, of which claims 1, 10, and 17 are currently amended. Claims 7 and 15 were previously canceled.
Response to Arguments
Rejections Under 35 USC 112
Applicant has amended the claims at issue and the claim language is now directed to language that is supported by Applicant’s disclosure as originally filed. Therefore, the previous rejections under 35 U.S.C. 112(a) have been withdrawn.
Prior Art Rejections
Applicant’s arguments regarding the amended claim language have been fully considered. Specifically, Applicant argues that the amendments regarding the predetermined number of users and the threshold value is not taught by Gray or Cassidy. See Remarks 7-8. These arguments are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Previously cited (but unmapped) reference Neumann has been introduced to teach the amended features of the claim, as well as replacing Cassidy for its teachings of the notification. Neumann teaches that a threshold number of users participate in a command on content within a set period of time. This includes as it relates to the current time, as the recommendations are based on real-time input. See Neumann paras. [0024], [0120], and [0126].
It is for at least these reasons, and the reasons cited below, that the claims remain rejected in this Action.
Claim Objections
Claim 1 is objected for the following informalities:
Claim 1 recites “a quantity of user associated” in lines 2-3, and this is a typographical/grammatical error as it should read “a quantity of users”.
Appropriate correction is required.
Examiner’s Note
The prior art rejections below cite particular paragraphs, columns, and/or line numbers in the references for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-6, 9-14, 16-19, 21, and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gray et al. (U.S. Patent 10,466,955 B1; hereinafter, “Gray”) and further in view of Neumann et al. (U.S. Publication No. 2016/0274744; hereinafter “Neumann”; retrieved from PTO-892 previously mailed on April 7, 2026).
As per claim 1, Gray teaches a method comprising:
receiving, by a computing device, data indicating times and a quantity of user associated with a user command was received during prior outputs of a content item (See Gray Fig. 3 and col. 9: 5-19: Aggregate Audio Adjustment History Module where “while media content is being played on user devices, volume adjustment events with timestamps can be detected and recorded”; col. 5:34-41: “media content can be aggregated when above a predetermined number of users have made audio adjustments to a specific segment of the streaming media content”);
determining, based on the data, a time for making a recommendation for the user command (See Gray Figs. 3 and 5 and col. 9: 5-46: based on timestamped data and aggregated user data, provide a recommended volume level); and
causing, at the determined time and during a future output of the content item at a user device, output of [a notification indicating] the recommendation [and comprising an option for a user of the user device to select the recommendation] (See Gray Figs. 3 and 5 and col. 9:36-46: “recommended volume level 370 for each segmentation or piece of content being played at least in part based upon what the user and/or “similar” users have done for same or similar scenes in the past”).
However, while Gray teaches a predetermined number of users, Gray does not apply a threshold value at a current period of time.
Neumann teaches the quantity of users over a time period relative to a current time satisfies a threshold value (See Neumann paras. [0120]: “computing device may assess whether a threshold number of users have participated in the trend and/or whether a rate of change of the number of users initiating a particular command exceeds a threshold rate. As another example, the system may determine that a trend exists when a threshold number of users initiate a command within a set period of time, such as within the last five minutes.”; para. [0126]: “If a user has been inactive for a threshold duration, the computing device may mark the user as inactive and may ignore that user's current selection in further processing.”; para. [0024]: “system may analyze usage information over a range of time relative to the current time in determining the existence of trends, in some examples. For example, the system may utilize a range of 10 minutes and consider recent usage information relating to programs watched and commands issued by users within the last 10 minutes”).
Furthermore, while Gray teaches selecting a suggested volume level (See Gray Fig. 3 and cols. 6:55-62 and 9:5-9), Gray does not explicitly teach a notification indicating the recommendation.
Neumann teaches output of a notification indicating the recommendation and comprising an option for a user of the user device to select the recommendation (See Neumann paras. [0051-54] and [0061]: real-time usage information used to generate recommendations for a user. “The notification may allow the user to select an option to implement the recommendation, an option to ignore the recommendation, and an option to disable future recommendations, for example”).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine, with a reasonable expectation of success, the suggested volume levels of Gray with the thresholds and displayed settings of Neumann. One would have been motivated to combine these references because both references disclose user-based recommendation of content control actions, and Neumann further enhances the suggestions of Gray by allowing the user to easily visualize and select the suggestions, especially when presenting information to a user for selection is an incredibly common and obvious way for a user to make a choice from a list of options. Furthermore, using real-time/current activity ensures more accurate data to make better recommendations to users (See Neumann paras. [0007] and [0021]).
As per claim 2, Gray/Neumann further teaches the method of claim 1, wherein the determining the time comprises determining a time for making a recommendation to mute audio of the content item and is based on times that other users muted the audio during the prior outputs of the content item (See Gray Figs. 3 and 5 and col. 9:5-46: tracking volume adjustment events across users at specific time stamps. “[V]olume levels within a video 360 may vary between 0 and 1. The default volume level of a new segmentation of the video 360 may be 0.75. However, the recommended volume level 370 for each segmentation or piece of content being played can be determined based on what the user has done in the past…” Therefore, users can set the volume level to 0, which is muted, and it will be aggregated and recommended to future users; col. 8:44-48: additionally, users can selectively mute specific audio tracks of the content, including the user “choos[ing] to mute the dialogues and only listen to the background sounds”).
As per claim 3, Gray/Neumann teaches the method of claim 1, wherein the determining the time comprises determining a time for making a recommendation to adjust audio volume of the content item and is based on times that other users adjusted the audio volume during the prior outputs of the content item (See Gray Fig. 3 and col. 9:20-44: various volume adjustment events recorded from users that have previously interacted with content. These volume adjustment events can then be used to provide recommended volume levels for each segmentation or piece of content that thus corresponds to those timestamps).
As per claim 4, Gray/Neumann further teaches the method of claim 1. However, while Gray/Neumann explicitly teaches aggregating user interactions for recommendations, Gray/Neumann does not explicitly do so with timestamping when a user fast-forwards content.
Neumann teaches that users can fast-forward the content item, and thus together with Gray, teaches wherein the determining the time comprises determining a time for making a recommendation to fast-forward the content item and is based on times that other users fast-forwarded the content item during the prior outputs of the content item (See Neumann paras. [0043], [0064-65], and [0143]: real-time event information may track when a user fast-forwards content and be used in recommending users to fast forward at certain points in a media content item).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Gray with the teachings of Neumann for at least the same reasons as discussed above in claim 1.
As per claim 5, Gray further teaches the method of claim 1. However, while Gray explicitly teaches aggregating user interactions for recommendations, Gray does not explicitly do so with timestamping when a user replays portions of content.
Neumann teaches that users can replay a portion of the content item, and thus together with Gray, teaches wherein the determining the time comprises determining a time for making a recommendation to replay a portion of the content item and is based on times that other users replayed the portion of the content item during the prior outputs of the content item (See Neumann paras. [0043], [0064-65], and [0143]: real-time event information may track when a user replays content and be used in recommending users to replay at certain points in a media content item).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Gray with the teachings of Neumann for at least the same reasons as discussed above in claim 1.
As per claim 6, Gray/Neumann teaches the method of claim 1. However, while Gray explicitly teaches aggregating user interactions for recommendations, Gray does not explicitly do so with timestamping when a user skips portions of content.
Neumann teaches that users can skip a portion of the content item, and thus together with Gray, teaches wherein the determining the time comprises determining a time for making a recommendation to skip a portion of the content item and is based on times that other users skipped the portion of the content item during the prior outputs of the content item (See Neumann paras. [0043], [0064-65], and [0143]: real-time event information may track when a user replays content and be used in recommending users to fast-forward/jump/skip at certain points in a media content item).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Gray with the teachings of Neumann for at least the same reasons as discussed above in claim 1.
As per claim 9, Gray/Neumann further teaches the method of claim 1, further comprising: receiving one or more tags associated with a scene of the content item at the determined time (See Gray cols. 3:61-67 to 4:1-9: storing media content data; col. 5:34-60: different scenes of media content defined and associated with segments that can be presented to a user. All of this various data is a tag, because metadata is the data about data. Therefore, particular scenes will be “tagged” with the timestamps as discussed in the rejection of claim 1, as well as the audio adjustments, etc.), and
wherein causing the output [of the notification] is further based on the one or more tags (See Gray Figs. 3 and 5 and col. 9:20-44: “When the media content is played back on a user device, the recommended volume level 370 can be provided so that the user device can automatically adjust the audio volume”).
However, while Gray teaches selecting a suggested volume level (See Gray Fig. 3 and col. 9:5-9), Gray does not explicitly teach a notification indicating the recommendation.
Neumann teaches the output of the notification (See Neumann paras. [0051-54] and [0061]: real-time usage information used to generate recommendations for a user. “The notification may allow the user to select an option to implement the recommendation, an option to ignore the recommendation, and an option to disable future recommendations, for example”).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Gray with the teachings of Neumann for at least the same reasons as discussed above in claim 1.
As per claim 10, Gray teaches a method comprising:
receiving, by a user device, a selection of a content item; causing, based on the selection, output of the content item (See Gray Fig. 5 and cols. 10: 49-67 to 11:1-9: receiving request for content and in response to the request, providing the content to the computing device for rendering to the user); and
causing, during the output of the content item and at the user device, output of [a notification indicating] a recommendation to adjust the output of the content item [and comprising an option for a user of the user device to select the recommendation], wherein a time of outputting the notification is based on a quantity of other users adjusted prior outputs of the content item satisfying a threshold value (See Gray Figs. 3 and 5 and cols. 9:5-46 and 11:4-22: “recommended volume level 370 for each segmentation or piece of content being played at least in part based upon what the user and/or “similar” users have done for same or similar scenes in the past”; col. 5:34-38: “recorded audio volume levels for each segment of media content can be aggregated when above a predetermined number of users have made audio adjustments to a specific segment of the streaming media content”).
However, while Gray teaches a predetermined number of users (See Gray col. 5:34-41), Gray does not apply a threshold value at a current period of time.
Neumann teaches a quantity of users over a time period relative to a current time satisfies a threshold value (See Neumann paras. [0120]: “computing device may assess whether a threshold number of users have participated in the trend and/or whether a rate of change of the number of users initiating a particular command exceeds a threshold rate. As another example, the system may determine that a trend exists when a threshold number of users initiate a command within a set period of time, such as within the last five minutes.”; para. [0126]: “If a user has been inactive for a threshold duration, the computing device may mark the user as inactive and may ignore that user's current selection in further processing.”; para. [0024]: “system may analyze usage information over a range of time relative to the current time in determining the existence of trends, in some examples. For example, the system may utilize a range of 10 minutes and consider recent usage information relating to programs watched and commands issued by users within the last 10 minutes”).).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Gray with the teachings of Neumann for at least the same reasons as discussed above in claim 1.
Furthermore, while Gray teaches selecting a suggested volume level (See Gray Fig. 3 and cols. 6:55-62 and 9:5-9), Gray does not explicitly teach a notification indicating the recommendation.
Neumann teaches output of a notification indicating a recommendation to adjust the output of the content item and comprising an option for a user of the user device to select the recommendation (See Neumann paras. [0051-54] and [0061]: real-time usage information used to generate recommendations for a user. “The notification may allow the user to select an option to implement the recommendation, an option to ignore the recommendation, and an option to disable future recommendations, for example”).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Gray with the teachings of Neumann for at least the same reasons as discussed above in claim 1.
As per claims 11-14 and 16, the claims are directed to a method that implements the same features as the method of claims 3-6 and 9, respectively, and are therefore rejected for at least the same reasons therein.
As per claim 17, Gray teaches a method comprising:
causing, by a computing device, output of a content item comprising a plurality of scenes (See Gray Figs. 3 and 5 and cols. 9:5-28 and 10:49-67 to 11:1-9: receiving request for content and in response to the request, providing the content to the computing device for rendering to the user. The content can be segmented into scenes S1-SN shown in video log 360, with different timestamps detected and recorded);
receiving a tag associated with a quantity of users adjusted prior outputs of one of the plurality of scenes and comprising a recommendation to adjust the output of the one of the plurality of scenes (See Gray cols. 3:61-67 to 4:1-9: storing media content data; Fig. 3 and col. 5:34-60 and col. 9:5-44: different scenes of media content defined and associated with segments that can be presented to a user. All of this various data is a tag, because metadata is the data about data. Therefore, particular scenes will be “tagged” with the timestamps as well as the audio adjustments, etc. Furthermore, a user can select a recommended volume level; col. 5:34-41: “media content can be aggregated when above a predetermined number of users have made audio adjustments to a specific segment of the streaming media content”); and
causing, based on the tag and the quantity of users [over a time period relative to a current time satisfying a threshold value], and during output of the one of the plurality of scenes, output of [a notification indicating] the recommendation to adjust the output of the one of the plurality of scenes [and comprising an option to select the recommendation] (See Gray Figs. 3 and 5 and col. 9: 20-44: “When the media content is played back on a user device, the recommended volume level 370 can be provided so that the user device can automatically adjust the audio volume”).
However, while Gray teaches a predetermined number of users (See Gray col. 5:34-41), Gray does not apply a threshold value at a current period of time.
Neumann teaches a quantity of users over a time period relative to a current time satisfies a threshold value (See Neumann paras. [0120]: “computing device may assess whether a threshold number of users have participated in the trend and/or whether a rate of change of the number of users initiating a particular command exceeds a threshold rate. As another example, the system may determine that a trend exists when a threshold number of users initiate a command within a set period of time, such as within the last five minutes.”; para. [0126]: “If a user has been inactive for a threshold duration, the computing device may mark the user as inactive and may ignore that user's current selection in further processing.”; para. [0024]: “system may analyze usage information over a range of time relative to the current time in determining the existence of trends, in some examples. For example, the system may utilize a range of 10 minutes and consider recent usage information relating to programs watched and commands issued by users within the last 10 minutes”).).
Furthermore, while Gray teaches selecting a suggested volume level (See Gray Fig. 3 and cols. 6:55-62 and 9:5-9), Gray does not explicitly teach a notification indicating the recommendation.
Neumann teaches output of a notification indicating the recommendation to adjust the output of the one of the plurality of scenes and comprising an option to select the recommendation (See Neumann paras. [0051-54] and [0061]: real-time usage information used to generate recommendations for a user. “The notification may allow the user to select an option to implement the recommendation, an option to ignore the recommendation, and an option to disable future recommendations, for example”).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Gray with the teachings of Neumann for at least the same reasons as discussed above in claim 1.
As per claim 18, Gray/Neumann further teaches the method of claim 17, wherein the recommendation to adjust the output of the one of the plurality of scenes comprises: a recommendation to adjust a playback speed of the one of the plurality of scenes, a playback location of the one of the plurality of scenes, or audio of the one of the plurality of scenes (See Gray Fig. 3 and col. 9:20-44: various volume adjustment events recorded from users that have previously interacted with content. These volume adjustment events can then be used to provide recommended volume levels for each segmentation or piece of content that thus corresponds to those timestamps)
As per claim 19, Gray/Neumann further teaches the method of claim 17, further comprising:
receiving data indicating times a user command was received during prior outputs of the content item (See Gray Fig. 3 and col. 9: 5-19: Aggregate Audio Adjustment History Module where “while media content is being played on user devices, volume adjustment events with timestamps can be detected and recorded”);
determining, based on the data, a time for making a second recommendation for the user command (See Gray Figs. 3 and 5 and col. 9: 5-46: based on timestamped data and aggregated user data, provide a recommended volume level); and
causing, at the determined time and during the output of the content item, output of the second recommendation for the user command (See Gray Figs. 3 and 5 and col. 9:36-46: “recommended volume level 370 for each segmentation or piece of content being played at least in part based upon what the user and/or “similar” users have done for same or similar scenes in the past”).
As per claim 21, Gray/Neumann further teaches the method of claim 1, further comprising: receiving second data indicating a selection of the recommendation; and causing, based on the second data and the user command, adjusting of the future output of the content item (See Gray Figs. 3 and 5 and col. 9:5-46: user can select recommended volume levels and “recommended volume level 370 for each segmentation or piece of content being played at least in part based upon what the user and/or “similar” users have done for same or similar scenes in the past”. Therefore, this information is aggregated for future users as well).
As per claim 22, the claim is directed to a method that implements the same features as the method of claim 21, and is therefore rejected for at least the same reasons therein.
Claims 8 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gray/Neumann, as applied above, and further in view of Golan et al. (U.S. Publication No. 2015/0134673; hereinafter, “Golan”).
As per claim 8, Gray/Neumann further teaches the method of claim 1, wherein the data further indicates that prior users adjusted, for a duration, the prior outputs of the content item (See Gray Fig. 3 and col. 9:5-19: scenes S1-SN shown in video log 360, with different timestamps detected and recorded, through different time windows w, x, y, etc.).
However, while Gray/Neumann teaches segmenting the video content as well as the notification, Gray/Neumann does not explicitly teach outputting the duration of these segments.
Golan teaches and wherein the notification further indicates the duration (See Golan para. [0039]: “A metadata object associated with a time slot or segment may record a…duration value”; Fig. 2B and paras. [0052] and [0062]: timeline of the video clip with different segments highlighted based on the associated metadata with the video clip. This would include the recommended content settings and the various timeframes of Gray/Neumann).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine, with a reasonable expectation of success, the user segments and durations of Gray/Neumann with the outputting and timelines of Golan. One would have been motivated to combine these references because both references disclose tracking user interactions while viewing content, and Golan enhances the user experience of Gray/Neumann by allowing the users of Gray/Neumann to easily visualize the segments so that the users don’t “have to watch an entire video clip” as “users often do not have the time or patience to watch every video clip” (See Golan paras. [0003-04]).
As per claim 20, the claim is directed to a method that implements the same features as the method of claim 8, and is therefore rejected for at least the same reasons therein.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/NICHOLAS KLICOS/Primary Examiner, Art Unit 2118
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