Detailed Action
Status of Claims
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 in reply to the Election filed on 12/22/2025. Claims 1-11 are pending and have been examined. Claims 12-20 are withdrawn.
Election
Applicant’s election with traverse of Group I (claims 1-11) in the reply filed on 12/22/2025 is acknowledged.
The traversal is on the grounds that the inventions “are capable of use together and have overlapping functions,” arguing that the three groups “describe different aspects of the same overall invention,” namely a “pre-processing/setup phase,” “operational phase,” and “the system implementation,” which are “different perspectives on implementing the same inventive concept,” and “cannot function independently.”
This is not found persuasive because the groups are directed to independent or distinct inventions. The three inventions, while each generally related to e-commerce video presentation, are directed to three distinct, alternative methods and systems which process, select, and display videos in different formats. For instance, the method of Group 1 has not teaching or suggestion that it “cannot function independently” of Group II’s video configuration steps, not that the machine learning and computer vision of group II is necessary to perform any operation of Group I, nor that the tagging or histogram operations of group I are necessary for or related to any operations of Group II.
Applicant further argues that the inventions “share common modes of operation,” with a common data structure, workflow, and technical problem.
This is not found persuasive because the groups are directed to independent or distinct inventions. Similar to the discussion above, each of the groups recites distinct steps not present in the other groupings, and distinct capabilities as part of a distinct workflow. Rather than being directed to the same invention for solving the same problem, the three inventions are directed to three different, alternative, methods and systems for analyzing, modifying, and presenting videos in three different ways in three different situations.
Applicant further argues that the claims “substantially overlap in scope,” with comparisons of limitations between each pairing of Groups. Applicant argues that these amount to “different components and methods within this unified system.”
This is not found persuasive because the groups are directed to independent or distinct inventions. As acknowledged by Applicant, the three groups recite “different components and methods,” which perform different, non-overlapping tasks related to different, alternative methods of video presentation. The argued limitations highlight these differences – the histogram of Claim 3 and the computer vision of Claims 12-18 are distinct, alternative methods of processing video data, with no suggestion or teaching that computer vision or machine learning from Group II would relate to the method of Group I. Similarly Group II does not “describe the process that creates this tagged metadata” in Group III; as it does not address tagging or metadata at all; instead, it addresses a machine learning process distinct from each of the other groups. Similarly, Group III recites limitations not present or necessary in Group I, such as distinct UI elements about graphical overlaps, and POS devices, while Group I recites elements related to histograms and video-indexing not present or necessary in Group III.
Applicant further argues that the three groups are obvious variants that share a “Common inventive concept,” are “predictable variations,” are recited in the Specification as a single embodiment, and share “Common elements.”
This is not found persuasive because the groups are directed to independent or distinct inventions. While each Group may at a high level recite similar phrasing in certain steps and may share certain key terms, the three groups are directed to distinct, alternative methods/systems for performing video presentation. These alternative methods, as detailed above, are not merely predictable variations of each other, but alternatives with distinct, non-overlapping elements.
Applicant further argues that there is “no serious search or examination burden,” as the claims are in “closely related subclasses,” and that “a single prior art search would uncover references relevant to all three groups,” arguing that such a search would use “common search terms such as “product recommendations” and “loyalty profiles,” that the groups have an “overlapping technical field,” and that each has “shared technical features,” such that the claims have “no separate inventive patentable distinction.”
This is not found persuasive because the groups are directed to independent or distinct inventions. The idea that similar words may be present in searches for the three distinct inventions does not negate the search burden of examining three distinct inventions, one reciting detailed machine-learning operations, another reciting specific UI elements, and another providing detailed operations related to generating histograms and tagging/indexing videos as part of a video presentation system. While all three groups do recite some (but not all) of the argued “common search terms,” the focus of each invention is a different, distinct series of detailed steps for different, non-overlapping video presentation systems.
Applicant further argues that “the restriction requirement improperly fragments a single invention,” reiterating the argument that the groups have “a single inventive concept.”
This is not found persuasive because the groups are directed to independent or distinct inventions. As discussed above, the three inventions, as written, provide three different inventive concepts for different video-presentation systems. Each recites unique steps not present in the other groups, and provides alternative means to perform each stage of a video-presentation sequence. The three groupings provide three different inventions claiming three different techniques for video presentation, with three different sets of operations to achieve distinct results.
The requirement is still deemed proper and is therefore made FINAL.
Claim Rejection - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
First, it is determined whether the claims are directed to a statutory category of invention. In the instant case, claims 1-11 are directed to a process. Therefore, claims 1-11 are directed to statutory subject matter under Step 1 as described in MPEP 2106 (Step 1: YES).
The claims are then analyzed to determine whether the claims are directed to a judicial exception. In determining whether the claims are directed to a judicial exception, the claims are analyzed to evaluate whether the claims recite a judicial exception (Prong One of Step 2A), as well as analyzed to evaluate whether the claims recite additional elements that integrate the judicial exception into a practical application of the judicial exception (Prong Two of Step 2A).
Claim 1 recites at least the following limitations that are believed to recite an abstract idea:
associating content of a content library with product codes and personas;
identifying a customer engaged in a checkout;
obtaining a known persona linked to the customer, wherein the known persona reflects one or more preferences of the customer obtained through historical interactions with the customer;
receiving at least one recommended product code based on a transaction history of the customer;
generating a playlist from the content based on the at least one recommended product code and the known persona; and
presenting at least one content from the playlist to the customer during the checkout, wherein the at least one video is presented on a display associated with processing the checkout.
The above limitations recite the concept of a personalized content suggestion. These limitations, under their broadest reasonable interpretation, fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, enumerated in MPEP 2106, in that they recite commercial interactions, e.g. sales activities/behaviors, and managing personal behavior or relationships or interactions between people, e.g., following rules or instructions. Accordingly, under Prong One of Step 2A, claims 1-11 recite an abstract idea (Step 2A, Prong One: YES).
Prong Two of Step 2A is the next step in the eligibility analyses and looks at whether the abstract idea is integrated into a practical application. This requires an additional element or combination of additional elements in the claims to apply, rely on, or user the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception.
In this instance, the claims recite the additional elements of:
Videos
a terminal or a user device
However, these elements do not amount to an improvement in the functioning of a computer or any other technology or technical field; apply the judicial exception with, or by use of, a particular machine; or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort to monopolize the exception.
In addition, the recitations are recited at a high level of generality and also do not amount to an improvement in the functioning of a computer or any other technology or technical field; apply the judicial exception with, or by use of, a particular machine; or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort to monopolize the exception.
The dependent claims also fail to recite elements which amount to an improvement in the functioning of a computer or any other technology or technical field; apply the judicial exception with, or by use of, a particular machine; or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort to monopolize the exception. For example, claims 5-9, 11 are directed to the abstract idea itself and do not amount to an integration according to any one of the considerations above. As for claims 2-4, 10 these claims are similar to the independent claims except that they recite the further additional elements of metadata, video frames, a touch interaction with a display. These additional elements are recited at a high level of generality and also do not amount to an improvement in the functioning of a computer or any other technology or technical field; apply the judicial exception with, or by use of, a particular machine; or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort to monopolize the exception. Therefore, the dependent claims do not create an integration for the same reasons.
Step 2B is the next step in the eligibility analyses and evaluates whether the claims recite additional elements that amount to an inventive concept (i.e., “significantly more”) than the recited judicial exception. According to Office procedure, revised Step 2A overlaps with Step 2B, and thus, many of the considerations need not be re-evaluated in Step 2B because the answer will be the same.
In Step 2A, several additional elements were identified as additional limitations:
Videos
a terminal or a user device
These additional limitations, including the limitations in the dependent claims, do not amount to an inventive concept because they were already analyzed under Step 2A and did not amount to a practical application of the abstract idea. Therefore, the claims lack one or more limitations which amount to an inventive concept in the claims.
For these reasons, the claims are rejected under 35 U.S.C. 101.
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 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 Rejection – 35 USC § 103
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim Rejection – 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-
obviousness.
Claims 1-2, 5-8 & 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Mahmood et al (US 20220277205 A1) hereinafter Mahmood, in view of Crossley et al (US 20200134320 A1), hereinafter Crossley.
Regarding Claim 1, Mahmood discloses a method, comprising:
associating content items of a content item library with product codes and personas [content type/outcome] (Mahmood: “recommendation server system 102 may receive … content data from server system 140… also receive a recommendable content set from server system 140. … also receive a target dataset (that includes data on conversions or outcomes) from server system 140” [0045] – “obtaining a list of content items of the content type for each cluster,” [0011] – “the content identifier may specifically identify the content item, e.g., by a product stock keeping unit (SKU) or other unique identifier.” [0120]);
identifying a customer engaged in a checkout (Mahmood: “a shopping website includes three slots in the user interface for recommendations (e.g., during checkout), the recommendation context may indicate that three content items are to be included in the recommendation.” [0103]);
obtaining a known persona linked to the customer, wherein the known persona reflects one or more preferences of the customer obtained through historical interactions with the customer (Mahmood: “As seen in FIG. 2A, a user feature matrix may include a plurality of user features with corresponding values for each user.” [0048] – “user FM 202 may include aggregated features based on user behavior while using client application 150, or accessing a website provided by server system 140 via a browser on a client device. For example, such features can be based on how the user navigates the app or website user interface, e.g., while using a food shopping app, a user searches for “sandwich,” taps on “Chicken club sandwich,” views “nutritional information,” scrolls the app user interface to view the ingredients, taps a back button, and searches for “gyros,” and so on.” [0050]);
receiving at least one recommended product code based on a transaction history of the customer (Mahmood: “ user FM 202 may also include content interaction behavior related to a particular outcome. For example, the columns “bought sandwich week 1” and “bought soda week 1” indicate whether a particular item (“purchase”) was performed with respect to a particular content item (or category of content item), namely “sandwich” and “soda.”” [0051]);
generating a playlist [ranked list] from the content items based on the at least one recommended product code and the known persona (Mahmood: “the current user FM and current content FM may be transformed into a suitable format for the ML model …a ranked list of content items may be generated for current users (in the current user data) using the trained ML model. In some implementations, the model may generate a set of content items and associated scores, and the scores may be used to generate the ranked list …the generated ranked list of content items for each user” [0079-0082]); and
presenting at least one content item from the playlist to the customer during the checkout, wherein the at least one content item is presented on a display associated with a terminal or a user device that is processing the checkout (Mahmood: “the recommendation context indicates a number of content items, e.g., to be included in the recommendation. For example, if a shopping website includes three slots in the user interface for recommendations (e.g., during checkout), the recommendation context may indicate that three content items are to be included in the recommendation” [0103] – “client application 150 such as a mobile app that displays recommendations of content items or a web browser application that displays websites that include recommendations of content items, etc.),” [0126] – See also Fig. 8, [0115]).
While Mahmood teaches that content includes videos [0047], it does not specifically teach that the content items are videos. However, Crossley teaches a video platform for purchasing products (Crossley: [0007]), including that the content items are videos (Crossley: “provides a way for consumers of video content to know what products appear in a video in real time” [0078] – “a video advertisement” [0113]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of invention to combine these references because the results would be predictable. Specifically, Mahmood would continue to teach associating content items of a content item library with product codes and personas, except that now it would also teach that the content items are videos, according to the teachings of Crossley. This is a predictable result of the combination.
In addition, it would have been obvious to one of ordinary skill in the art before the effective filing date of invention to combine these references because it would result in an improved ability to increase engagement and purchase click through of products (Crossley: [0007]).
Regarding Claim 2, Mahmood/Crossley teach the method of claim 1, wherein associating further includes tagging the videos with metadata that includes the product codes and the personas and indexing the videos based on the metadata for retrieval (Crossley: “The metadata for each tagged video frame may include object or product identification information (e.g., product IDs) for all objects and products associated with the people appearing in the video frame” [0045] – “the product server 207 can obtain metadata in real-time using the object recognition server 200 and fetch previously indexed metadata from the product metadata database 209. To access real-time or previously indexed metadata, the product server 207 can send metadata requests to product metadata database 209 to retrieve metadata for the display of product information” [0053]),
And wherein Mahmood further teaches that retrieval occurs during the checkout (Mahmood: “a shopping website includes three slots in the user interface for recommendations (e.g., during checkout), the recommendation context may indicate that three content items are to be included in the recommendation.” [0103]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Crossley with Mahmood for the reasons identified above with respect to claim 1.
Regarding Claim 5, Mahmood/Crossley teach the method of claim 1, wherein receiving further includes providing the transaction history in real time to a recommendation service and receiving real-time recommended product recommendations from the recommendation service during the checkout (Mahmood: “a processor may perform its functions in “real-time,”” [0124] – “the food shopping application may generate and record (with user permission) user data based on the user's interaction with the application, e.g., items that the user searches for, items that the user views/adds to cart/adds to wishlist, purchases made by the user, the user's navigation patterns within the application, etc. Such user data is provided (with user permission) to the recommendation server system 102 which may utilize the data” [0116] – “in a shopping application where the recommendation is provided as a suggested item, the subsequent user actions may include “added to wish list,” “added to cart,” “purchased,” or “not selected.” Such user actions may be included in subsequent user data.” [0111] – “various implementations described herein may be included as part of a website or app by the provider, or may be provided as a third-party service utilized by the provider” [0033]).
Regarding Claim 6, Mahmood/Crossley teach the method of claim 1, wherein generating further includes filtering the content items based on a first match between the product codes and the at least one recommended product code and a second match between the personas and the known persona (Mahmood: “the ranked list may be filtered to remove content items that are not in the recommendable content set, … if the recommendation context indicates that two content items are to be provided, the top two content items in the ranked list may be provided.” [0109-0110] – “the ranked list of content items may be generated based on one or more other parameters. For example, after the scores are generated, the ranked list of content items may be generated with specific subsets of items having a higher likelihood of inclusion in the ranked list of content items. For example, if a recommendable content set is received, it may be utilized during the post-processing to generate the ranked list. ” [0081]),
Wherein Crossley further teaches that the content items are videos (Crossley: “provides a way for consumers of video content to know what products appear in a video in real time” [0078] – “a video advertisement” [0113]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Crossley with Mahmood for the reasons identified above with respect to claim 1.
Regarding Claim 7, Mahmood/Crossley teach the method of claim 6, wherein filtering further includes scoring and ranking the content items in the playlist according a relevance to the known persona and a likelihood of purchase based on the at least one recommended product code (Mahmood: “ the content items in the list may be ranked based on the likelihood of the predicted result for the outcome identifier being TRUE (e.g., “Purchase made,”” [0076] -“the ranked list may be filtered to remove content items that are not in the recommendable content set, … if the recommendation context indicates that two content items are to be provided, the top two content items in the ranked list may be provided.” [0109-0110] – “the ranked list of content items may be generated based on one or more other parameters. For example, after the scores are generated, the ranked list of content items may be generated with specific subsets of items having a higher likelihood of inclusion in the ranked list of content items. For example, if a recommendable content set is received, it may be utilized during the post-processing to generate the ranked list. ” [0081]),
Wherein Crossley further teaches that the content items are videos (Crossley: “provides a way for consumers of video content to know what products appear in a video in real time” [0078] – “a video advertisement” [0113]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Crossley with Mahmood for the reasons identified above with respect to claim 1.
Regarding Claim 8, Mahmood/Crossley teach the method of claim 7, wherein scoring further includes providing the at least one content item to the terminal or the user device as a highest scored content item from the playlist (Mahmood: “ the content items in the list may be ranked based on the likelihood of the predicted result for the outcome identifier being TRUE (e.g., “Purchase made,”” [0076] -“the ranked list may be filtered to remove content items that are not in the recommendable content set, … if the recommendation context indicates that two content items are to be provided, the top two content items in the ranked list may be provided.” [0109-0110]),
Wherein Crossley further teaches that the content items are videos (Crossley: “provides a way for consumers of video content to know what products appear in a video in real time” [0078] – “a video advertisement” [0113]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Crossley with Mahmood for the reasons identified above with respect to claim 1.
Regarding Claim 10, Mahmood/Crossley teach the method of claim 1 further comprising, providing an interactive element in the at least one content item that allows the customer to directly add a particular recommended product associated with the at least one content item to the checkout through touch interaction with the display (Mahmood: “generates a ranked list of content items, which are provided in the recommendations section 806—fresh basil, sliced mushrooms, and tiramisu, along with an option to add these items to the shopping cart.” [0115] – “mode through which the user interactions with the application 150 (e.g., via touchscreen,” [0050]),
Wherein Crossley further teaches that the content items are videos (Crossley: “provides a way for consumers of video content to know what products appear in a video in real time” [0078] – “a video advertisement” [0113]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Crossley with Mahmood for the reasons identified above with respect to claim 1.
Regarding Claim 11, Mahmood/Crossley teach the method of claim 1 further comprising, logging interactions of the customer with the at least one content item including any interactions with interactive elements of the at least one content item and updating a loyalty profile associated with the customer based on the interactions (Mahmood: “ user FM 202 may include aggregated features based on user behavior while using client application 150, or accessing a website provided by server system 140 via a browser on a client device. … event data generated from such interaction (interaction events) with the app or the website may be aggregated over a time period (e.g., 1 day, 1 week, etc.) to obtain features in the user FM. … user FM 202 may include any other statistics associated with events of the website or app, e.g., an average count of certain types of events per day (e.g., number of logins, number of page views, etc.,), time since the most recent event of a particular type (e.g., time since items added to cart, time since last order, etc.)” [0050]),
Wherein Crossley further teaches that the content items are videos (Crossley: “provides a way for consumers of video content to know what products appear in a video in real time” [0078] – “a video advertisement” [0113]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Crossley with Mahmood for the reasons identified above with respect to claim 1.
Claims 3-4 are rejected under 35 U.S.C. 103 as being unpatentable over Mahmood/Crossley in view of Fleischman et al (US 20210319228 A1), hereinafter Fleischman.
Regarding Claim 3, Mahmood/Crossley teach the method of claim 1, wherein associating further includes generating at least one representation per video, wherein the at least one representation includes unique tags for corresponding product codes and objects detected in a corresponding video along with frequency counts for the unique tags within frames of the corresponding video (Crossley: “Concurrently the real-time recognition application 210 can store metadata of the recognized objects, including a reference timestamp corresponding to a time within the video duration, and other suitable information associated with the objects included in the video frames of a video.” [0052] – “every frame of the video (or every frame at a set interval, e.g., every 15th frame) can be associated with the products (and corresponding product information, such as images, price, purchase link, etc.) that appear in the given frame. The timestamp for when the frame (and products) appears in the video is also kept in the database, so that the code can display the products in real-time.” [0081]).
However, Mahmood/Crossley do not specifically teach that the representation is a histogram.
However, Fleischman teaches a video display system [Abstract] including that the representation is a histogram (Fleischman: “the histogram with the timeline corresponding to the timestamps of the set of walkthrough videos, the histogram including highlighted bars indicating instances of the identified portions of frames within the set of walkthrough videos. … the height of the highlighted bars of the histogram indicate the number of instances of identified portions, corresponding to instances of objects or surfaces, included within a walkthrough video captured on a particular day on the timeline.” [0156]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of invention to combine these references because the results would be predictable. Specifically, Mahmood/Crossley would continue to teach generating at least one representation per video, wherein the at least one representation includes unique tags for corresponding product codes and objects detected in a corresponding video along with frequency counts for the unique tags within frames of the corresponding video, except that now it would also teach that the representation is a histogram, according to the teachings of Fleischman. This is a predictable result of the combination.
In addition, it would have been obvious to one of ordinary skill in the art before the effective filing date of invention to combine these references because it would result in an improved ability to identify instances of an object in a video (Fleischman: [0004]).
Regarding Claim 4, Mahmood/Crossley/Fleischman teach the method of claim 3, wherein generating the at least one representation per video further includes assigning corresponding personas per video based on a corresponding at least one representation (Crossley: “Concurrently the real-time recognition application 210 can store metadata of the recognized objects, including a reference timestamp corresponding to a time within the video duration, and other suitable information associated with the objects included in the video frames of a video.” [0052] – “every frame of the video (or every frame at a set interval, e.g., every 15th frame) can be associated with the products (and corresponding product information, such as images, price, purchase link, etc.) that appear in the given frame. The timestamp for when the frame (and products) appears in the video is also kept in the database, so that the code can display the products in real-time.” [0081]),
wherein Fleischman further teaches that the representation is a histogram (Fleischman: “the histogram with the timeline corresponding to the timestamps of the set of walkthrough videos, the histogram including highlighted bars indicating instances of the identified portions of frames within the set of walkthrough videos. … the height of the highlighted bars of the histogram indicate the number of instances of identified portions, corresponding to instances of objects or surfaces, included within a walkthrough video captured on a particular day on the timeline.” [0156]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Fleischman with Mahmood/ Crossley for the reasons identified above with respect to claim 3.
Claims 9 is rejected under 35 U.S.C. 103 as being unpatentable over Mahmood/Crossley, in view of Farrelly (US 20090077052 A1).
Regarding Claim 9, Mahmood/Crossley teach the method of claim 6, but do not teach that filtering further includes randomly selecting the at least one video from the playlist and providing to the terminal or the user device.
However, Farrelly teaches a system for recommending media [Abstract], including that filtering further includes randomly selecting the at least one video from the playlist and providing to the terminal or the user device (Farrelly: “operates to play media content such as, for example, songs and videos” [0021] – “generates a list of recommended songs based on the responses from the servers … the songs from the servers 30, 36, and 42 are randomly sorted to provide the list of recommended songs. … The list of recommended songs is then provided to the user device” [0031-0032]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of invention to combine these references because the results would be predictable. Specifically, Mahmood/Crossley would continue to teach filtering the content items based on a first match between the product codes and the at least one recommended product code and a second match between the personas and the known persona, except that now it would also teach that filtering further includes randomly selecting the at least one video from the playlist and providing to the terminal or the user device, according to the teachings of Farrelly This is a predictable result of the combination.
In addition, it would have been obvious to one of ordinary skill in the art before the effective filing date of invention to combine these references because it would result in an improved ability to provide recommendations based on context (Farrelly: [0007]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 20160005097 A1 teaches recommendation systems based on user purchase history and preferences. Recommendations are determined in real time and presented during checkout.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THOMAS J SULLIVAN whose telephone number is (571)272-9736. The examiner can normally be reached Mon - Fri 8-5 MT.
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/T.J.S./Examiner, Art Unit 3689
/MARISSA THEIN/Supervisory Patent Examiner, Art Unit 3689