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 .
Response to Amendment
The amendment filed on January 29, 2026 cancelled claims 9, 12, and 14. Claims 1, 6 and 17 were amended and no new claims were added. Thus, the currently pending claims addressed below are claims 1-8, 10-11, 13, and 15-17.
Claim Objections
Claims 1-8, 10-11, 13, and 15-16 are objected to because of the following informalities: Independent claim 1 contains limitations, apparently rolled into the independent claim from claim 9, 12 and 14. However, these limitations are not properly marked as amended portions of the claims. Neither the entered claim amended dated September 25, 2025, nor the non-entered after-final amendment dated December 29, 2025, nor the instant claim amendment included any markings indicating that the limitations of dependent claims 9, 12, and 14 have been rolled into claim 1. Since the examiner noticed the newly amended limitation, despite the lack of proper markings, the examiner has merely objects to independent claim 1, instead of issuing a Notice of Non-Responsive Amendment. However, an indication of these limitations being added to the claim is required in any future amendment. Should there be any other limitations added to the claims, the examiner is unaware of such limitations, these too must be corrected in any future amendment. The examiner further notes that the applicant’s arguments indicate that claims 1-17 remain but the claim markings indicate that claims 9, 12, and 14 have been cancelled. Dependent claims 2-8, 10-11, 13, and 15-16 fail to correct the deficiencies of the claims from which they depend, as well as, inherit the deficiencies of the claims from which they depend. As such, claim 2-8, 10-11, 13, and 15-16 are objected to by virtue of dependency.
Claims 1-8, 10-11, 13, and 15-17 are objected to because of the following informalities:
Independent claims 1 and 17 have been amended as follows: “a registration module configured to register a user using one or more credentials to link corresponding plurality of different social media channels” and “registering, by a registration module, a user using one or more credentials to link corresponding plurality of different social media channels” . This is the first time “corresponding plurality of different social media channels” is used the claims. As such it should include an article such as “a” or “an” to ensure proper antecedent based can be made for later recitations. For the purpose of prosecuting the claims the examiner is going to interpret the claim as if it recited: “a registration module configured to register a user using one or more credentials to link a corresponding plurality of different social media channels:” and “registering, by a registration module, a user using one or more credentials to link a corresponding plurality of different social media channels”, respectively. Appropriate correction is required.
Independent claims 1 and 17 have been amended as follows: “identify a plurality of key engagement metrics comprising likes, comments, shares, clicks, follows, mentions, and impressions for registered user on the corresponding plurality of different social media channels” and “identifying, by an engagement calculation module, a plurality of key engagement metrics comprising likes, comments, shares, clicks, follows, mentions, and impressions for registered user on the corresponding plurality of different social media channels” . The them “register user” does not have proper antecedent basis to the previously claimed a user which was registered in the registration step. To have proper antecedent basis to said user the limitation should recite “the registered user” or “said registered user”. For the purpose of prosecuting the claims the examiner is going to interpret the claim as if it recited: “identify a plurality of key engagement metrics comprising likes, comments, shares, clicks, follows, mentions, and impressions for the registered user on the corresponding plurality of different social media channels” and “identifying, by an engagement calculation module, a plurality of key engagement metrics comprising likes, comments, shares, clicks, follows, mentions, and impressions for the registered user on the corresponding plurality of different social media channels”, respectively. Appropriate correction is required.
Dependent claims 2-8, 10-11, 13, and 15-16 fail to correct the deficiencies of the claims from which they depend, as well as, inherit the deficiencies of the claims from which they depend. As such, claim 2-8, 10-11, 13, and 15-16 are objected to by virtue of dependency.
Claim Rejections - 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 1-8, 10-11, 13, and 15-17 are directed to a system and a method which would be classified under one of the listed statutory classifications (i.e., 2019 Revised Patent Subject Matter Eligibility Guidance (hereinafter “PEG”) “PEG” Step 1=Yes).
However, claims 1-8, 10-11, 13, and 15-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claim(s) 1 and 17 recite(s) the following abstract idea:
registering a user using one or more credentials to link a corresponding plurality of different social media channels;
identifying a plurality of key engagement metrics comprising likes, comments, shares, clicks, follows, mentions, and impressions for the registered user on the corresponding plurality of different social media channels;
calculating a plurality of individual engagement metrics corresponding to each type of engagement for each specific post or content piece;
comparing engagement across different posts or the plurality of different social media channels for normalizing the plurality of key engagement metrics for generating a normalized engagement value comparable across the plurality of different social media channels, wherein normalizing the plurality of key engagement metrics comprise calculating an engagement rate as a percentage of total audience or reach for each of the plurality of different social media channels;
calculating a total engagement value for an overall account, using the generated normalized engagement value, by summing up the plurality of individual engagement metrics of a specific post or content piece for an overall account;
obtaining a historical dataset comprising at least one of user interactions, engagement metrics, from the plurality of different social media channels;
training one or more algorithmic models on the historical dataset using a defined state representation, an action space, and a reward function to generate a trained reinforcement learning policy, wherein the state representation comprises features and variables of current state of the social media platform, wherein the current state may include user activity, post content, time of day, and contextual information;
fine-tuning hyperparameters and optimize the reward function comprising adjusting the one or more algorithmic models, learning rates, and discount factors to iterate on the training process, by iteratively adjusting the learning rates and discount factors until a convergence criterion is satisfied;
setting a conversion rate between the total engagement value and reward points;
calculating the reward points for each user or post based on determined conversion rate;
dynamically assigning loyalty in the reward points to the user based on the engagement level using one or more trained algorithmic models;
simulating the trained algorithmic model in a controlled environment to evaluate performance;
creating a virtual wallet for the user to accumulate the reward points;
converting accumulated reward points into a plurality of assets comprising money, cryptocurrency, or gift cards, wherein conversion comprises establishing an equivalent conversion rate corresponding to each asset to determine an equivalent unit of corresponding selected asset from the plurality of assets integrated with blockchain based platforms; and
sending a conversion request to trigger a fund transfer request to external financial platforms or blockchain networks.
The limitations as detailed above, as drafted, falls within the “Certain Method of Organizing Human Activity” grouping of abstract ideas namely advertising, marketing, or sales related activities or behaviors. Accordingly, the claim recites an abstract idea (i.e., “PEG” Revised Step 2A Prong One=Yes).
This judicial exception is not integrated into a practical application because the only “additional elements” within the scope of the claim are:
a server comprising a hardware processor with a memory executing instructions (i.e., a processing subsystem with a registration module, an engagement calculation module, a training module, a reward generation module, a leader board module, and a reward redemption module) (e.g. a general-purpose computer with generic computer components); and
one or more machine learning models comprising at least one of a deep Q-network (DQN), a policy gradient method, and actor-critic model (generic computer components).
The following limitations, if removed from the abstract idea and considered additional elements, merely perform generic computer function of processing, storing, communicating (e.g., transmitting and receiving), and displaying data and, as such, are insignificant extra-solution activities (see MPEP 2016.05(d)(II) and MPEP 2106.05(g)):
obtaining a historical dataset comprising at least one of user interactions, engagement metrics, from the plurality of different social media channels (receiving data); and
sending a conversion request to trigger a fund transfer request to external financial platforms or blockchain networks (transmitting data).
The additional technical elements above are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of processing, communicating (e.g., transmitting and receiving), and displaying) such that it amounts to no more than mere instructions to apply the exception using one or more general-purpose computers and/or one or more generic computer components. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional technical elements above do not integrate the abstract idea/judicial exception into a practical application because it does not impose any meaningful limits on practicing the abstract idea. More specifically, the additional elements fail to include (1) improvements to the functioning of a computer or to any other technology or technical field (see MPEP 2106.05(a)), (2) applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition (see Vanda memo), (3) applying the judicial exception with, or by use of, a particular machine (see MPEP 2106.05(b)), (4) effecting a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05(c)), or (5) applying or using 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 designed to monopolize the exception (see MPEP 2106.05(e) and Vanda memo).
Rather, the limitations merely add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), or generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)).
Thus, the claim is “directed to” an abstract idea (i.e., “PEG” Revised Step 2A Prong Two=Yes)
When considering Step 2B of the Alice/Mayo test, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims do not amount to significantly more than the abstract idea.
More specifically, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a general-purpose computer with generic computer components executing instructions, wherein the instructions include one or more generic machine learning model to perform the claimed functions amounts to no more than mere instructions to apply the exception using one or more general-purpose computers and/or one or more generic computer components.
“Generic computer implementation” is insufficient to transform a patent-ineligible abstract idea into a patent-eligible invention (See Affinity Labs, _F.3d_, 120 U.S.P.Q.2d 1201 (Fed. Cir. 2016), citing Alice, 134 S. Ct. at 2352, 2357) and more generally, “simply appending conventional steps specified at a high level of generality” to an abstract idea does not make that idea patentable (See Affinity Labs, _F.3d_, 120 U.S.P.Q.2d 1201 (Fed. Cir. 2016), citing Mayo, 132 S. Ct. at 1300). Moreover, “the use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent-eligible subject matter (See FairWarning, 120 U.S.P.Q.2d. 1293, citing DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1256 (Fed. Cir. 2014)). As such, the additional elements of the claim do not add a meaningful limitation to the abstract idea because they would be generic computer functions in any computer implementation. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of the computer or improves any other technology. Their collective functions merely provide generic computer implementation.
The Examiner notes simply implementing an abstract concept on a computer, without meaningful limitations to that concept, does not transform a patent-ineligible claim into a patent-eligible one (See Accenture, 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Bancorp, 687 F.3d at 1280), limiting the application of an abstract idea to one field of use does not necessarily guard against preempting all uses of the abstract idea (See Accenture, 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Bilski, 130 S. Ct. at 3231), and further the prohibition against patenting an abstract principle “cannot be circumvented by attempting to limit the use of the [principle] to a particular technological environment” (See Accenture, 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Flook, 437 U.S. at 584), and finally merely limiting the field of use of the abstract idea to a particular existing technological environment does not render the claims any less abstract (See Affinity Labs, _F.3d_, 120 U.S.P.Q.2d 1201 (Fed. Cir. 2016), citing Alice, 134 S. Ct. at 2358; Mayo, 132 S. Ct. at 1294; Bilski v. Kappos, 561 U.S. 593, 612 (2010); Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat’l Ass’n, 776 F.3d 1343, 1348 (Fed. Cir. 2014); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014).
Applicant herein only requires one or more general-purpose computers and/or one or more generic computer components (as evidenced from the applicant’s specification in Paragraphs 19-20, 38-39 which discloses that the server is a general-purpose computer with generic computer components and paragraph 27 and 45 which disclose that the applicant is using known machine learning models and not a machine learning model invented by the applicant; and Kozlica et al, Deep Q-learning versus Proximal Policy Optimization: Performance Comparison in a Material Sorting Task, 2023, https://arxiv.org/pdf/2306.01451, pgs. 1-6 which discloses on page 1, column 1, lines 1-4 that DQN machine learning was old and well-known by at least 2023); therefore, there does not appear to be any alteration or modification to the generic activities indicated, and they are also therefore recognized as insignificant activity with respect to eligibility. Finally, the following limitations, if removed from the abstract idea and considered additional elements, would be considered insignificant extra solution activity as they are directed to merely receiving, displaying, storing, and/or transmitting data (see MPEP 2016.05(d)(II) and MPEP 2106.05(g)):
obtaining a historical dataset comprising at least one of user interactions, engagement metrics, from the plurality of different social media channels (receiving data); and
sending a conversion request to trigger a fund transfer request to external financial platforms or blockchain networks (transmitting data).
Thus, taken individually and in combination, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea) (i.e., “PEG” Step 2B=No). cancelled claims 9, 12, and 14. Claims 1, 6 and 17 were amended
The dependent claims 2-8, 10-11, 13, and 15-16 appear to merely further limit the abstract idea by further limiting the one or more credentials which is considered part of the abstract idea (Claim 2); adding an additional step of receiving current locations which is considered part of the abstract idea (Claim 3); adding an additional step of generating a verification mark which is considered part of the abstract idea (Claim 4); adding an additional step of receiving selection of a request list which is considered part of the abstract idea (Claim 5); adding an additional step of enabling the user to initiate live chat, drop, and feed which is considered part of the abstract idea (Claim 6); further limiting the defined state representation and the current state which are both considered part of the abstract idea (Claim 7); further limiting the action space which is considered part of the abstract idea (Claim 8); adding a simulating step which is considered part of the abstract idea (Claim 10); further limiting the plurality of individual engagement metrics which is considered part of the abstract idea (Claim 11); adding an additional step of determining average engagement metrics which is considered part of the abstract idea (Claim 13); adding an additional step of displaying a list of leaders which is considered part of the abstract idea (Claims 15-16), and therefore only further limit the abstract idea (i.e. “PEG” Revised Step 2A Prong One=Yes), does/do not include any new additional elements that are sufficient to amount to significantly more than the judicial exception, and as such are “directed to” said abstract idea (i.e. “PEG” Step 2A Prong Two=Yes); and do not add significantly more than the idea (i.e. “PEG” Step 2B=No)..
Thus, based on the detailed analysis above, claims 1-8, 10-11, 13, and 15-17 are not patent eligible.
Claim Rejections - 35 USC § 112
Assuming claims 1 and 17 are amended in the manner identified in the Claim Objection section above, the claim overcome the 35 USC 112(b) rejection raised in the Office Action dated June 30, 2025. Thus, the rejections are hereby withdrawn.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-8, 10-11, 13, and 15-17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Independent claims 1 and 17 are indefinite because the claims are so broad that one of ordinary skill in the art would not be able to determine how the applicant’s invention is able to perform the claims steps.
Initially, independent claims 1 and 17 recite substantially the same limitation of identifying “a plurality of key engagement metrics comprising likes, comments, shares, clicks, follows, mentions, and impressions for registered user on the corresponding plurality of different social media channels”. Based on the limitation a plurality of key engagement metrics are identified. The plurality of metrics comprise likes, comments, shares, clicks, follows, mentions, and impressions: As such, one of ordinary skill in the art would understand that, based on the language of the claim as currently written, there must be at least one like metric, at least one comment metric, at least one share metric, at least one click metric, at least one follow metric, at least one mention metric and at least one impression metric included in said plurality of key engagement metric. Assuming the antecedent basis issue in the claim is corrected in a manner consistent with examiner’s interpretation in the Claim Objections above, one or ordinary skill in the art would realize said plurality of key engagement metrics are for the user registered in the registration step. However, the breadth issue being with one of ordinary skill in the art parsing the limitation “on the corresponding plurality of different social media channels”. The claim does not require that said plurality of key engagement metrics are identified for “each different social media channels of the corresponding plurality of different social media channels”. Thus, the broadest reasonable interpretation that one of ordinary skill would apply to the limitation is that while there must be a plurality of key engagement metrics and said plurality of key engagement metrics must included at least one like metric, at least one comment metric, at least one share metric, at least one click metric, at least one follow metric, at least one mention metric and at least one impression metric in the art would interpret the limitation, the limitation is broad enough that on a first social media channel they may only identify a like metric and an impression metric, on a second social media channel they may only identify a comment metric and an impression metric, on a third social media channel…, on a sixth media channel the invention may only gather an mention metric and on a seventh media channel the invention may only gather an impression metric (Note: One or ordinary skill in the art would realize that a like, a comment, a share, a click, and/or a follow, cannot occur without someone viewing the persons social media channel, thus an impression of the channel must also inherently occur. However, one may mention a channel without viewing it and just because you view a channel does not mean you inherently must perform any other action. Thus, a mention or an impression metric may be the only key engagement metric for one of the plurality of different social media channels.).
Then, independent claims independent claims 1 and 17 recite substantially the same limitation of calculating “a plurality of individual engagement metrics corresponding to each type of engagement for each specific post or content piece”. Thus, one of ordinary skill in the art would understand that for each post or content piece that is placed by the user on a social media channel of the plurality of different social media channels, a plurality of individual engagement metrics must be calculated. However, one or ordinary skill in the art would note that the claimed “a plurality of individual metrics” can be any type of metric because the claimed “a plurality of individual metrics” does not have antecedent basis to the previously claimed “a plurality of key engagement metric”. This is understandable because an interaction on an individual post may be an interaction that is not a “key engagement metric” for the specific social media channel on which it is placed. For example, if the key engagement metrics for one of the plurality of social media channels are “channel follows” and “channel impressions”, then said social media channel may not give users the ability to follow an individual post, and may not record individual post impressions. As such, the applicant’s invention would not be able to receive any such individual engagements from said social media channel, and the applicant’s invention would not be able to calculate these types of metrics for the post. Instead, the social media channel may record some other individual engagement for a post, such as, comments on the post and ratings on the post. In this case, the social media channel could provide information regarding just these two types engagement to the applicant’s invention and the applicant’s invention could calculate an individual post comment metric and an individual rating metric, such as this post was a three-star post and there were 10 total comments on the post. Thus, the breadth of this limitation does not require that each of the plurality of social media channels provide the same types of engagement information for each post or content piece and, as such does not require that the calculated plurality of individual engagement metrics for one post or content piece be the same calculated plurality of individual engagement metrics for a different post or a different content piece. Likewise, the individual engagement metrics for the post or content piece is not required to comprise likes, comments, shares, clicks, follows, mentions, and impressions for said post or content piece of the user.
As such, given the breadth of the previous two limitations, one or ordinary skill in the art would not be able to determine how the applicant’s invention can “compare engagement across different posts of the plurality of different social media channels for normalizing the plurality of key engagement metrics to generate a normalized engagement value comparable across the plurality of different social media channels, wherein normalizing the key engagement metrics comprises calculating an engagement rate as a percentage of total audience or reach for each of the plurality of different social media channels” as recited in independent claims 1 and 17.
First, the calculation is apparently done only for different posts but not for different content pieces. Since the claim is broad enough to encompass calculating the plurality of individual engagement metrics only for content pieces, the comparing step would never need occur. Without the normalizing step occurring, the calculation of the total engagement value could not be performed.
Second, “comparing engagement” does not have antecedent basis to the individual engagement metrics or the key engagement metrics for the channels. As such, one of ordinary skill in the art would not be able to determine whether the engagement being compared is the “key engagement metrics for the channel” or the individual engagement metrics for the posts”. Since, the limitation indicates the comparing is done across different posts, the engagement is probably post specific, but the comparison need not be done using the “individual engagement metrics” of the different posts. The limitation is broad enough that some type of other post specific engagement is compared.
Third, even if the examiner were to assume the engagement being compared was the “individual engagement metrics” for each post that was previously calculated, one of ordinary skill in the art would not be able to determine how the applicant’s invention performs such a comparison. Since the individual engagement metrics calculated from a first type engagement information for one post on one of the plurality of different sites may be different than the engagement metrics calculated from a second type of engagement information for a different post on a second of the plurality of different sites, it would not appear possible to perform such a comparison.
Fourth, even if for some reason the calculated individual engagement metrics happened to be the same for both the first post on the first site and the second post on the second site, one of ordinary skill in the art would not be able to determine how the applicant’s invention normalizes “the plurality of key engagement metrics” because there does not appear to the an associated between calculated individual engagement metrics for the posts an the plurality of key engagement metrics for each channel. According to the claim, normalizing the plurality key engagement metrics is done by calculating an engagement rate as a percentage of total audience or reach for each of the plurality of channels. It is unclear, whether the claimed “total audience” or “total reach” is intended to be the total audience of the social media channel or the total audience of the individual posts on each of the different the social media channel. Likewise, if the total reach is used is it the total reach of the social media channel or the total reach of the individual post on each of the different channel.
Fifth, even if one of ordinary skill in the art could somehow determine how to calculate the claimed engagement rate, according to the claim an engagement rate is calculated for each of the plurality of different social media channels. We know that from this plurality of engagement rates that a normalized engagement value is generated which is supposed to be comparable across the plurality of different social media channels. However, one of ordinary skill in the art would not be able to determine how the applicant’s invention is intended to generate the normalized engagement value based solely on the plurality of different engagement rates.
Sixth, even if one of ordinary skill in the art could generate a normalized engagement rate in the same manner as the applicant’s invention intends the next step requires the calculation of a total engagement value for an overall account using the generated normalized engagement value. One of ordinary skill in art would not be able to determine what account is being claimed. Is it an account of the user with the applicant’s invention, an account of the user on one of the different social media channels, an account of one of the different social media channels with the applicant’s invention, or some other account.
Seventh, even if one of ordinary skill in the art could determine which overall account the applicant is referring to they would not be able to determine how summing the plurality of engagement metrics for a specific single post or content piece which need only be on a single social media channel can result in a total engagement value for an overall account. One or ordinary skill in the art would think that summing said metrics for a single post or content piece on a single social media channel would result in a total engagement value for the single post or content piece, but not how such a value could be considered a total engagement value for an overall account.
Eighth, with regards to the training module, the claims indicate the historical data set of the registered user which is obtain comprises one of user interactions and engagement metrics “from the social media platform”. However, “a social media platform” has never been previously recited in the claims. Instead, the claims recite “a plurality of social media channels. One of ordinary skill in the art would not be able to determine whether the obtained historical data set is intended to from “the plurality of different social media channels”, a new social media platform different from the plurality of different social media channels, or “one of the plurality of different social media channels”, and if it is intended to be “one of the plurality of different social media channels” how the applicant’s invention determined which of the different social media channels are to be used by the training module.
Ninth, the claim requires the training of the machine learning module requires that the state representation to comprise features and variables of current state of the social media platform. Once again, one of ordinary skill in the art would not be able to determine what social media platform the applicant is intending to claim. The claim requires the current state to include user activity, post content, time of day, and contextual information. Is “user activity” intended to be activity of “the user”, some other user, or the activity of all users on such a social media platform. Since it’s a current state that includes the time of day, does the applicant intend said user activity to be just the user activity a said given point in time, just a post activity by the user at that specific point in time, the context of the user at that specific point in time, all user activity for all users at said given point in time, all post activity by all users at said given point in time, and/or all context for all users at said given point in time. Since, this is training step does current mean the point in time when the training is occurring, or the actual current time it is now? Perhaps, the applicant is using current to refer to a broader time range than the current given time?
Tenth, the claim requires “wherein the one or more machine learning models comprises deep reinforcement learning models comprising deep Q-networks (DNQ), policy gradient methods, and actor-critic models. The claim is broad enough to encompass just a single machine learning model. When there is only one single machine learning model, one of ordinary skill in the art would not be able to first out how the applicant intends the one single machine learning model to comprise “deep reinforcement models”. The only way this would appear to be possible is if the single machine learning model was a single ensemble machine learning model. However, the applicant’s disclosure is silent with regards to an ensemble machine learning model. Likewise, if one of ordinary skill in the determined that “deep reinforcement learning models” was a typographical error and that the applicant intend to recite “a deep reinforcement model”, then one of ordinary skill in the art would not be able to determine how a single deep reinforcement learning model can comprise “deep Q-networks (DNQ), policy gradient methods, and actor-critic models”.
Finally, the remainder of the claims include to many additional limitations which are indefinite for the examiner to describe in detail each issue. However, the same logic used in identifying the issued used above can be extrapolated and applied to the remainder of the claim.
As such, it is clear, that one of ordinary skill in the art would not be able to determine the intended metes and bound of independent claim 1 and 17 of the applicant’s invention and the claims are indefinite.
Dependent claims 2-8, 10-11, 13, and 15-16 fail to correct the deficiencies of the claims from which they depend and, as such, are rejected by virtue of dependency.
Given all the varied and different issues with the claims, it is difficult to determine the applicant’s intended metes and bounds of the claims. However, from the applicant’s arguments and specification it appears that the invention is intended to have the varied modules working in concert to arrive at accumulated reward points stored in a virtual wallet that can be then converted into at least one asset. As such, for the purpose of prosecuting the claims, using prior art, the examiner is going to interpret claim 17 as if it recited the following limitations (claim 1 will be interpreted in a manner consistent with the limitations of claim 17 recited below): A method for reward generation on a social media platform comprising:
registering, by a registration module, wherein said registering comprises the user’s name, a list of a plurality of different social media channels the user has an account with, and one or more credentials used to access said plurality of social media channels;
transmitting, by the registration module and to an engagement calculation module, the list of the plurality of social media channels, and the one or more credentials used to access said plurality of different social media channels;
accessing, by the engagement calculation module, said plurality of different social media channels using said one or more credential;
obtaining, by the engagement calculation module, a dataset of user interactions the user had on each of the plurality of different social media channels;
identifying, by the engagement calculation module, a plurality of key engagement metrics, from the dataset, comprising likes, comments, shares, clicks, follows, mentions, and impressions for the registered user for each the plurality of different social media channels;
obtaining, by the engagement calculation module, a first historical dataset of user interactions of the user with each of the plurality of different social media channels;
calculating, by the engagement calculation module, a plurality of individual engagement metrics corresponding to each type of key engagement metric for each of the plurality of different social media channels;
calculating, by the engagement calculation module, a total engagement value by summing up the plurality of individual engagement metrics from each of the plurality of different social media channels to calculate the total engagement value for the plurality of different social media channels;
obtaining, by a training module and from each of the different social media channels, a historical dataset of a plurality of users, wherein the historical dataset comprises a defined state representation, an action space, a reward function and a plurality of user interactions for the plurality of users from each of the plurality of different social media channels or a plurality key engagement metrics for the plurality of users from each of the plurality of different social media channels;
training, by the training module, one or more machine learning models to output recommended reward points, using the historical dataset comprising the defined state representation, the action space, the reward function and the the plurality of user interactions of the plurality of users for each of the plurality of different social media channels or the plurality key engagement metrics of the plurality of users from each of the plurality of social media channels, wherein the one or more machine learning models comprises a learning rates hyperparameter and a discount factors hyperparameter;
iteratively fine-tuning the one or more machine learning modules, by the training module, by adjusting the learning rates hyperparameter; adjusting the discount factors hyperparameter; and adjusting the reward function of the historical data with the intended results of optimizing the one or more machine learning models;
transmitting, by the engagement calculation module and to the reward generation module the total engagement value and the dataset of user interactions;
inputting, by the reward generation module and into the one or more machine learning modules, the dataset;
receiving, by the reward generation module and from the one or more machine learning module, a recommendation of reward points for the user;
setting, by a reward generation module, a first conversion rate for converting the total engagement value to a plurality of reward points based on the recommendation of reward points;
converting, by the reward generation module, the total engagement value to the plurality of reward points based on the first conversion rate;
transmitting, from the reward generation module and to a reward redemption module, the plurality of reward points;
creating, by the reward redemption module, a virtual wallet for the users to accumulate the reward points;
storing, by the reward redemption module, the reward points in the virtual wallet; and
converting, by the reward redemption module, the reward points into at least one of a plurality of assets using a second conversion rate, wherein the at least one of a plurality of assets comprises money, cryptocurrency integrated with a blockchain, or gift cards.
Possible Allowable Subject Matter
Claims 1-8, 10-11, 13, and 15-17 would be allowable over the prior art if the applicant were to be able to overcome the Claim Objections, the 35 USC 112(b) rejections and the 35 USC 101 rejections above.
The following is a statement of reasons for the indication of allowable subject matter: The examiner has found prior art (see Peurifoy et al. (PGPUB: 2022/0292547), Singh (PGPUB: 2021/0097240), Law et al. (PGPUB: 2023/0401600), Sankararaman et al. (PGPUB: 2025/0061506), and Swamidurai (PGPUB: 2019/0325473)) which teaches each and every limitation of the independent claims 1 and 17. However, it would not have been obvious to one or ordinary skill in the art, before the effective filing date of the invention, to combine these five different references to arrive at the applicant’s invention without impermissible hindsight by using the applicants claims as a roadmap. Thus, claims 1-8, 10-11, 13, and 15-17 contain subject matter that would be allowable over the prior art if the applicant were to be able to overcome the Claim Objections, the 35 USC 112(b) rejections and the 35 USC 101 rejections above.
Response to Arguments
Applicant's arguments filed January 29, 2026 have been fully considered but they are not persuasive.
The applicant’s arguments with regards to the 35 USC 112(b) rejections are not persuasive. As indicated in the 35 USC 112(b) rejection above, the amendment attempted to correct a couple of minor antecedent basis issues and/or a single issue identified in the 35 USC 112(b) rejection of the Office Action dated June 30, 2025, but did not correct all of the issues identified by the examiner in the Office Action, as well as, introduced a number of new 112(b) issues. For a detailed explanation of the 35 USC 112(b) issues still remaining in the claim refer to the 35 USC 112(b) rejection in the Office Action above. Thus, the rejection has been maintained.
With regards to the 35 USC 101 rejection, the applicant argues that the claims as a whole overcome the rejection because it is a well-established principle of patent law that the eligibility of a under 35 USC 101 must be determined by considering the claim as a whole and as an ordered combination of its elements. The examiner disagrees. The applicant appears to be misinterpreting MPEP 2106.05, as well as the Alice Corp decision. In the Alice Corp decision, as a well as the Mayo decision, which it cites makes it clear that a claim which recites and abstract idea must also recite “additional features”. MPEP 2106.05 requires that the “additional elements” of the claim, considered both individually and as a whole, that are capable of transforming an abstract idea into a practical application under Step 2a, Prong 2, and the “additional elements” of the claim, considered both individually and as a whole, which are considered “significantly more” under Step 2b. “Additional elements” in regards to MPEP 2106.05 (and “additional feature” in regards to the Alice Corp decision) are defined as those limitations of a claim which are not part of the abstract idea itself. It is these “additional elements” which are considered, both individually and as a whole, under Step 2a, Prong 2 and Step 2b to determine whether an abstract idea transforms an abstract idea into a practical application or is “significantly more” under Step 2b. Thus, any purported improvement, must be rooted in the “additional elements” of a claim in a manner other than merely applying the abstract idea using a general-purpose computer in order to transform an abstract idea into a practical application under Step 2a, Prong 2. Likewise, it is the “additional elements” of a claim which must be considered “significantly more” under Step 2b. In the instant case, the only “additional elements” present in the claims are a general-purpose computer with generic computer components executing instructions, wherein the instructions include one or more generic machine learning model. As made clear in the Recentive Analytics decision generic machine learning models, irresepective of how they are trained, is merely software executing on a computer and, as such, is merely a generic computer component which is incapable of transforming an abstract idea into a practical application under Step 2a, Prong 2, and incapable of being considered significantly more under Step 2b. Thus, the “additional elements” of the claim, considered both individually and as a whole, are no more than a general-purpose computer with generic computer components upon which the abstract idea is merely being applied which is insufficient to transform an abstract idea into a practical application under Step 2a, Prong 2 and insufficient to be considered Significantly more under Step 2b. Thus, the applicant’s arguments are not convincing and the rejections have been maintained.
The applicant argues, with respect to the 35 USC 101 rejection that the claims recite a technical solution to data heterogeneity under Step 2a, a Prong 2. The examiner disagrees. Irrespective of whether or not the claimed invention recites such a technical solution, the claims are not eligible. According to the applicant’s arguments this technical solution is rooted in the manner in which the invention normalizes data received from devices outside the scope of the applicant’s invention, by calculating engagement in the manner recited in the claims. The argued normalization of data received and calculating of the engagement are part of the abstract idea itself. Thus, any such technical solution is rooted solely in the abstract idea itself which is merely applied using the general-purpose computer. Improvements of this nature are improvements to an abstract idea which is an improvement in ineligible subject matter (see SAP v. Investpic decision: Page 2, line 22 through Page 3, line 13 - Even assuming that the algorithms claimed are groundbreaking, innovative or even brilliant, the claims are ineligible because their innovation is an innovation in ineligible subject matter because they are nothing but a series of mathematical algorithms based on selected information and the presentation of the results of those algorithms. Thus, the advance lies entirely in the realm of abstract ideas, with no plausible alleged innovation in the non-abstract application realm. An advance of this nature is ineligible for patenting; and Page 10, lines 18-24 - Even if a process of collecting and analyzing information is limited to particular content, or a particular source, that limitations does not make the collection and analysis other than abstract.). Thus, the applicant’s arguments are not convincing and the rejections have been maintained.
The applicant argues, with respect to the 35 USC 101 rejection, that the machine learning recited in the claims of the instant invention are not similar to the claims of the Recentive Analytics decision because they are not directed to a mental act or a predictive result; the machine learning model is used as a tool integrated into a rewards generation server, and recite a non-abstract practical application by creating a physical/digital asset and the transfer of verified assets via a blockchain ledger. The examiner disagrees. First, nowhere in the Recentive Analytics decision does it mention that machine learning must be directed to a mental act or a predictive result for it to be a generic machine learning model. The terms predict, predicting, predicted, prediction, and/or predictive are not even mentioned in the Recentive Analytics decision. The term “mentally” is used only once with regards to the Trinity Info Media decision, as a rebuttal to the argument that machine learning performs task more quickly than humans. The Trinity Info Media decision might have been relevant is the identified abstract idea category was “Mental Process”. However, the instant claims are directed to “Certain Methods of Organizing Human Activity” and, as such, it is immaterial whether the claims can be performed in the human mind. Furthermore, there is mention of the social media APIs in the applicants claims, and even if such APIs were included, APIs are merely software and the different social media channels are outside the scope of the applicants’ claimed server and, as such, would be considered part of the abstract idea itself. Second, MPEP 2106.05 makes it clear that a general-purpose computer with generic computer component (e.g., the machine learning model) which is merely a tool used to apply an abstract idea is insufficient to transform an abstract idea into a practical application under Step 2a, Prong 2 and insufficient to be considered “significantly more” under Step 2b. Finally, the creation of a digital asset is still just generating data and, as such is still part of the abstract idea itself. The applicant disclosure does not support the applicant invention printing money, or printing a physical gift card. As such, the claimed money is a digital representation of money, and the claimed gift card is a digital representation of a gift card, both of which are considered part of the abstract idea itself and, as such, cannot be considered “additional elements” of the claimed invention. Since they are part of the abstract idea itself neither the money nor the gift card are capable of transforming an abstract idea into a practical application under Step 2a, Prong 2 or capable of being considered considered “significantly more” under Step 2b. Third, the claims do not transfer verified assets via a blockchain ledger, instead they determine an equivalent unit of the assets which are already integrated on a blockchain based platform which is outside the scope of the claim and sent a conversion request (data), the intended result of transmitting said data being that a fund transfer occur at an external blockchain network or external financial platform. Since the financial platform and its functions as well as the blockchain based platform and the blockchain networks are all outside the scope of the applicant’s invented server and, as such, cannot be considered “additional elements” of the claimed invention. Thus, they are part of the abstract idea itself, as is the determining of an equivalent unit and the sending of the conversion request. Since these limitations are all part of the abstract idea itself they are not capable of transforming an abstract idea into a practical application under Step 2a, Prong 2 or capable of being considered “significantly more” under Step 2b. Whether the claimed “determining of an equivalent unit…” and the claimed “sending of the conversion request…” are in the realm of “mathematical algorithms” is immaterial to the instant rejection. Such a consideration is only relevant to abstract ideas that are rejected as reciting a “Mathematical Concept”. The instant claims have been rejected as reciting “Certain Methods of Organizing Human Activity”. The courts have found that steps directed to receiving data, analyzing data, determining results, generating tailored content, and transmitting the tailored content are all part of the abstract idea itself when a claim recites “Certain Methods of Organizing Human Activity”. Thus, even if one were to be convinced that determining of an equivalent unit was not within the realm of a “mathematical algorithm”, both the claimed “determining of an equivalent unit…” and the claimed “sending of the conversion request…” would still be within the realm of “Certain Methods of Organizing Human Activity”. Instead. the claims are clearly similar to the Recentive Analytics decision. The Recentive Analytic decision makes it clear that: claims that do no more than apply established methods of machine learning to a new data environment are not patent eligible (see at least Page 10, lines 16-19 of the Recentive Analytics decision); The requirements that the machine learning model be “iteratively trained” or dynamically adjusted in the Machine Learning Training patents do not represent a technological improvement (see at least Page 12, lines 1-4 of the Recentive Analytics decision); claims that do not delineate steps through which machine learning technology achieves an improvement are not patent eligible (see at least Page 13, lines 1-26 of the Recentive Analytics decision); an abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment (see at least Page 14, lines 13-25 of the Recentive Analytics decision); and disclosure of an "already available [technology] with [its] already available basic functions, to use as [a] tool[] in executing the claimed process" is still an abstract idea (see at least Page 14, line 26 through Page 15, line 13 of the Recentive Analytics decision). In the instant case, there is no indication that the applicant has invented machine learning, deep reinforcement learning model, deep Q-networks (DQN), policy gradient methods, or actor-critic models. In fact, it appears that they applicant is using the terms as known machine learning models as there is no disclosure of how the internal workings of these have been invented to work. Additionally, the examiner has provided proof that deep reinforcement learning models comprising at least one of deep Q-networks (DQN), policy gradient methods, or actor-critic models were well-understood routine and conventional before the effective filing date of the applicant’s invention. Likewise, the any technical validation or transformation of real-time network events would be part of the abstract idea itself and/or considered merely applying machine learning in a particular environment. The applicant appears to admit that the claimed machine learning is merely used as a tool executing on the server for executing the abstract idea. As such, given the cited sections of the Recentive Analytics decision and the applicant’s arguments that the claims are very similar to the Recentive Analytics decision and merely recite generic machine learning models that were already in existence, which are merely trained in a desired manner to obtain the desired output, and iteratively retrained based on hyperparameters which is merely being used as a software tool executing on the server such that the abstract idea is merely applied. Thus, the applicant’s arguments are not convincing and the rejections have been maintained.
The applicant argues that the claims of the instant invention are distinguishable from the SAP decision because the advancement in the instant claims lies in a technical normalization framework that allows a server to interface with multiple heterogeneous social media networks. The examiner strongly disagrees. The claims recite no technical normalization framework and no interface with multiple heterogeneous social media network. If the applicant has invented such technical normalization framework or some inventive manner of interfacing with heterogeneous social media networks, such interactions must be occurring well before the implementation of the claimed invention, or is merely data that is received from such networks in the normal manner where it is transmitted from one computer to another. The only time data is obtained in the claims is when it obtains a historical dataset from a social media platform in the singular. All other data that the applicant server used to perform the abstract idea, such as the key engagement metric from a corresponding plurality of different social media channels, the engagement for specific posts or a content piece, the total audience of reach information, the features and variables of current state of the social media platform, is merely assumed to already be in possession by the server before the claimed invention starts to execute or is merely received from such platforms and/or channels when said social media platforms and/or social media channels deem to transmit such data to the server. As such, it is clear that the advancement in the instant claims in no way recites a technical normalization framework that allows a server to interface with multiple heterogeneous social media networks. Instead, any purported advancement obtained by practicing the claimed invention is clearly rooted solely in the abstract idea itself which is merely applied using a general-purpose computer. Therefore, the claims are extremely similar to the SAP v. Investpic decision because any purported advancement is rooted solely in an abstract idea which is merely applied using the general-purpose computer. The instant claims merely recite purported improvements to an abstract idea, and, as clearly decided in the SAP decision, improvements of this nature, irrespective of how groundbreaking, innovative or even brilliant they may be, are improvements in ineligible subject matter. Additionally, the examiner notes that MPEP 2106, specifically states "the judicial exception alone cannot provide the improvement.". Thus, the applicant’s arguments are not convincing and the rejections have been maintained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Dinh (US Patent: 11,620,682) which discloses calculating an engagement score based on social engagement metrics of the user with the system or online closet community, wherein the score is based on number of posts, number of likes received, number of likes given, etc.; determining reward points based on the engagement score, and converting the reward points into assets.
Fuller et al. (PGPUB: 2019/0050911) which discloses calculating social media engagement metrics of customers (likes, shares, etc.), as well as real-world activity (product purchases, physical attendance at advertised locations, etc.), attributable to each influencer, and calculating reward points based on the engagement metrics, wherein the reward points are converted into a monetary reward.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN W VAN BRAMER whose telephone number is (571)272-8198. The examiner can normally be reached Monday-Thursday 5:30 am - 4 pm EST.
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/John Van Bramer/
Primary Examiner, Art Unit 3622