DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/20/2026 has been entered.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but 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.
Claims 1, 13 and 20 have been amended. The amendments to the claims overcome the previous 112 rejection.
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.
Claims 1-7 and 9-20 are rejected under 35 U.S.C. 103 as being unpatentable over Chaudhari (US 2013/0263174) in view of Wu (US 2017/0353463) and further in view of Myers (US 2018/0352278) and further in view of Tofighbakhsh (US 2018/0352301).
Regarding claim 1, Chaudhari discloses a system for temporally restricting multimedia content, comprising:
a memory configured to store non-transitory computer readable instructions (see at least paragraph 0059); and
a processor communicatively coupled to the memory (see at least paragraphs 0058-0059), wherein the processor, when executing the non-transitory computer readable instructions, is configured to:
receive, from a multimedia device, a request to access at least one multimedia item (receiving a request for access to a requested TV channel; see at least paragraph 0034);
receive subscription data associated with at least one user profile (determine a subscription packet associated with the receiver; see at least paragraphs 0025 and 0035);
analyze the subscription data in view of the request to access at least one multimedia item (determining if the requested channel is available or no with the user’s subscription package; see at least paragraphs 0025 and 0035);
receive current date and time data from the multimedia device (the current time and date is received in order to determine if the user has access to the programming or not, if not displaying an option to the user to purchase access to the programming; see at least Fig. 6B and paragraph 0051);
compare the current date and time data to the subscription data and based on the comparison of the current date and time data to the subscription data determine that the at least one multimedia item is not available outside of the permitted timeframe according to the subscription data (at the time/date of the request to access a programming, comparison of the time/date is performed in order to display an option to the user to purchase access to the programming; see at least Fig. 6B and paragraph 0051);
generate a permission to access the at least one multimedia item outside of the permitted timeframe (display an option to the user to purchase access to the programming; see at least Fig. 6B and paragraph 0051); and
initiate a notification before the non-permitted timeframe to prompt the subscription to access the at least one multimedia item outside of the permitted timeframe (at the time/date of the request to access a programming, comparison of the time/date is performed in order to display an option to the user to purchase access to the programming; see at least Fig. 6B and paragraph 0051).
Chaudhari discloses wherein the subscription data is indicative of a temporal restriction, and wherein the temporal restriction specifies a permitted timeframe and a non-permitted timeframe for accessing the at least one multimedia item within a subscription period; see at least Fig. 6D and paragraph 0036, but Chaudhari is not clear about wherein the permitted timeframe is within the non-permitted timeframe, and wherein the permitted timeframe is determined upon at least one user preference and wherein the user preference includes at least one of a genre, an actor, and a geography factor. Furthermore, Chaudhari is not clear about wherein the notification is generated at least based on a machine learning model trained by a past viewing frequency associated with the at least one multimedia item.
Wu discloses controlling access to content and discloses wherein the permitted timeframe is within the non-permitted timeframe and wherein the permitted timeframe is determined upon at least one user preference; access permissions for content may only be allowed on weekends or holidays but not on school days; see at least paragraph 0049. Furthermore, the user’s personal profile includes acceptable internet browsing time, the time of the day and the day of the week when the user requests the online access, preset times of the day to when the user may access certain websites…etc.; see at least paragraphs 0028, 0038-0039 and 0043-0048.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Chaudhari by the teachings of Wu by having the above limitations so to be able to control access to online content; see at least the Abstract.
Chaudhari in view of Wu are not clear about wherein the user preference includes at least one of a genre, an actor, and a geography factor and wherein the notification is generated at least based on a machine learning model trained by a past viewing frequency associated with the at least one multimedia item.
Myers discloses wherein the user preference includes at least one of a genre, an actor, and a geography factor and generating a notification at least based on a past viewing frequency associated with the at least one multimedia item; the system is configured to classify users based on a plurality of segmentation parameters including location, age group, language preferences, gender and specified user’s interests; see at least paragraph 0025. Furthermore, the system is configured to send personalized message to the user including messages to upgrade a subscription package after detecting changes in a trend in viewing habits of one or more users; see at least paragraphs 0030-0031, 0042-0043,0051, 0060, 0066 and 0071.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Chaudhari in view of Wu by the teachings of Myers by having the above limitations so to be able to enhance user engagement; see at least the Abstract.
Chaudhari in view of Wu and further in view of Myers are not clear about generating a notification at least based on a machine learning model trained by past viewing data.
Tofighbakhsh discloses the above missing limitation; obtaining viewing history data, training a machine learning application according to the viewing history data and providing a notification by the machine learning application; see at least paragraphs 0010-0012, 0039, 0044 and 0054.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Chaudhari in view of Wu in view of Myers by the teachings of Tofighbakhsh by having the above limitations so to be able to monitor and control media content using machine learning; see at least paragraph 0010.
Regarding claim 2, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 1, the processor further configured to:
present the notification during the permitted timeframe (Myers; a notification to upgrade the channel or an existing subscription package; see at least Fig. 4B and paragraphs 0031 and 0051).
Regarding claim 3, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 1, wherein the at least one multimedia item is at least one of: a television show, a movie, a sporting event, a live event, a song, a concert, a picture, and a video (Chaudhari; see at least Fig. 6F).
Regarding claim 4, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 2, the processor further configured to:
receive an input associated with the notification, wherein the input indicates acceptance of the at least one method of accessing the at least one multimedia item; and
based on the acceptance of the at least one method of accessing the at least one multimedia item, permit access to the at least one multimedia item (the user can select continue or order to watch the channel; see at least Figs. 6B-6E).
Regarding claim 5, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 2, wherein the at least one method of accessing the at least one multimedia item is an option to upgrade a subscription (Chaudhari; see at least paragraph 0055).
Regarding claim 6, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 2, wherein the at least one method of accessing the at least one multimedia item is an option to pay a one-time fee (Chaudhari; i.e., a day pass; see at least Fig. 6D).
Regarding claim 7, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 2, the processor further configured to:
analyze at least one machine-learning mode, wherein the at least one machine-learning model is trained on data based on the at least one user profile (see at least Chaudhari; paragraph 0040 and Tofighbakhsh; see at least the rejection of claim 1).
Regarding claim 9, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 7, wherein the data based on the at least one user profile comprises a past viewing history associated with the at least one user profile (Chaudhari; see at least paragraph 0041 and Tofighbakhsh; see at least the rejection of claim 1).
Regarding claim 10, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 7, the processor further configured to:
present for display on the multimedia device a notification associated with a second multimedia item (Chaudhari; see at least Figs. 6B-6E), wherein the second multimedia item is selected by the at least one machine-learning model (in combination with the machine learning model of Tofighbakhsh; see at least the rejection of claim 1).
Regarding claim 11, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 1, wherein the permitted timeframe includes a weekday (Chaudhari; i.e., a day pass; see at least Fig. 6D and paragraph 0036 and the weekend of Wu).
Regarding claim 12, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 1, wherein the permitted timeframe for accessing multimedia items comprises a weekend of a week, and wherein the non-permitted timeframe for accessing multimedia items comprises weekdays of the week (Wu; see at least the rejection of claim 1).
Claim 13 is rejected on the same grounds as claim 1.
Claim 14 is rejected on the same grounds as claim 7.
Regarding claim 15, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the method of claim 14, further comprising:
based on the analysis of the at least one machine-learning model, presenting the notification associated with a second multimedia item during the permitted timeframe (the combination of the machine learning model of Tofighbakhsh; see at least the rejection of claim 1 and the notification of Chaudhari; see at least Figs. 6B-6E in combination with Myers’s notification; see at least Fig. 4B and paragraphs 0031 and 0051).
Regarding claim 16, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the method of claim 15, wherein the second multimedia item is a restricted multimedia item at a future data and time (it will be restricted outside the time window; Chaudhari; it can be any time; see at least paragraph 0036).
Regarding claim 17, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the method of claim 15, wherein the notification presents at least one method of accessing the second multimedia item (Chaudhari; see at least Figs. 6B-6E).
Regarding claim 18, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the method of claim 17, wherein the at least one method of accessing the second multimedia item is an option to upgrade a subscription (Chaudhari; see at least paragraph 0055).
Regarding claim 19, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the method of claim 17, wherein the at least one method of accessing the second multimedia item is an option to pay a one-time fee (Chaudhari; i.e., a day pass; see at least Fig. 6D).
Claim 20 is rejected on the same grounds as claim 1, wherein presenting for display on the multimedia device a notification associated with the at least one multimedia item, wherein the notification presents an option to upgrade a subscription to access the at least one multimedia item (see at least Fig. 6B), receiving an input associated with the notification, wherein the input indicates acceptance of the option to upgrade the subscription (the user can select continue or order; see at least Figs. 6B-6C); and permitting access to the at least one multimedia item (after the order completed; see at least Fig. 6E).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh and further in view of Rustamov (US 2021/0345001).
Regarding claim 8, Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh disclose the system of claim 7, but are not clear about wherein the at least one machine-learning model is trained according to at least one of: a linear regression, a logistic regression, a linear discriminant analysis, a regression tress, a naive Bayes algorithm, a k-nearest neighbors algorithm, a learning vector quantization, a neural network, a support vector machine (SVM), and a random forest.
Rustamov discloses the above missing limitation; using a machine learning algorithm, such as a neural network; see at least paragraphs 0040 and 0093-0094.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Chaudhari in view of Wu and further in view of Myers and further in view of Tofighbakhsh by the teachings of Rustamov by having the above limitations so to be able to provide content recommendation with reduced habit bias effects; see at least the Abstract.
Conclusion
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/YASSIN ALATA/Primary Examiner, Art Unit 2426
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