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 .
DETAILED ACTION
Status of Claims
This action is in reply to the communication filed on 06/11/2026.
Claims 1,13, 20, have been amended.
Claims 5, 12 have been canceled.
Claims 23-24 have been added.
Claims 1-4,6-11,13-24 are currently pending and have been examined.
Response to Applicant’s Arguments
Applicant’s amendments and arguments filed on 06/11/2026 have been fully considered and discussed in the next section. Applicant is reminded that the claims must be given its broadest, reasonable interpretation.
With regard to claims 1-4,6-11,13-22 rejection under 35 USC § 101:
Step 2 A, Prong One:
Applicant argues that “that the claims are not directed to fundamental economic practice or commercial interaction as asserted. Instead, they require particular computerized data processing steps that cannot practically be performed in the human mind or by pen and paper. The Office's characterization of the claims as falling under "certain methods of organizing human activity" (advertising or marketing) appears to overgeneralize the claims and overlooks the specific technological elements and data flows the claims require (page 3/8)”.
Examiner disagrees. Applicant's argument that the claims limitations overcome the claim rejection under Step 2a, Prong 1 because the steps cannot practically be performed in the human mind or by pen and paper is not convincing. The only abstract idea bucket in which performance by a human is required is the "Mental Process" bucket which requires that the steps be capable of being performed in the human mind. The claims of the instant invention have not been identified as a "Mental Process". Instead, the claims of the instant invention have been identified as "Certain Methods of Organizing Human Activities". The Subject Matter Eligibility Guidelines indicate that "advertising, marketing or sales related activities" is a subcategory of "Certain Methods of Organizing Human Activities". There is no requirement that these "advertising, marketing, or sales related activities" be performed by a human being. Therefore, all steps involved in the performance of advertising, marketing or sales related activities are part of the abstract idea itself irrespective of whether they are performed by a computer or performed by a human being. Thus, the applicant's arguments are moot.
Furthermore, as indicated previously and in the rejection below, the Office Action clearly stated that claim 1 for instance recite the following abstract idea of :
determining a reference impression-to-user ratio for a first time period based on historical campaign data and historical user data during the first time period, determining a predicted impression-to-user ratio for a second time period after the first time period based on the reference impression-to-user ratio and a training overlap factor, and training algorithm to generate a labelled number of unique users based on the reference impression-to-user ratio and the predicted impression-to-user ratio, provide a campaign;
receive, from, a user forecast request comprising user-selected campaign parameters;
determine, based on the user forecast request, campaign data associated with an advertising campaign;
generate, using the trained the algorithm and a parameter, a total number of unique users forecasted to be reached by the advertising campaign in a future time period based on the campaign data, wherein the parameter is computed asynchronously offline and periodically updated using an exponentially saturating overlap model based on historical user and campaign data, wherein the parameter indicates a rate of size increase of an overlap user set between unique users on different days, wherein an overlap factor between users on successive days is asynchronously computed offline based on the parameter and using the exponentially saturating overlap;
generate forecasted user data based on the total number of unique users; and
transmit, in response to the user forecast request, the forecasted user data to the campaign, wherein the campaign is configured to further provide updated forecasted user data based on changes to the user-selected campaign parameters in the campaign user interface;
selectively cause, according to the user-selected campaign parameters entered via the campaign impressions associated with the advertising campaign to be displayed on a website in response to search queries entered into the website;
capture user session data associated with displays of the impressions;
store the user session data with the user-selected campaign parameters in the historical user data and the historical campaign data; and
update using the user session data with the user-selected campaign parameters;
The above recitations are directed to analyzing data and determining results based on the analysis. Since analyzing data is part of the abstract idea itself, any improvement obtained by automating the analyzing of the data in an improvement to the abstract idea which is an improvement in ineligible subject matters (see SAP v. Investpic: 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. As such, the claims as drafted, falls within the “Certain Method of Organizing Human Activity” grouping of abstract ideas namely commercial or legal interactions because they recite advertising, marketing and sales activities or behaviors because they merely gather data, analyze the data, determine results based on the analysis, generate tailored content based on the results, and transmit the tailored content. 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 claim only recites the additional elements of “ a computing device over a network, the machine learning model, user interface” . 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 and displaying) such that it amounts to no more than mere instructions to apply the exception using a generic computer component, and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES). As such Applicant's claimed solution is NOT technological and does not addresses a technological problem. Accordingly, the claim rejection of claims 1-4,6-11,13-22 under 35 USC § 101 is maintained.
Applicant argues that “the focus is on a specific improvement in computer-related technology: a novel processing approach for predictive modeling in targeted content delivery systems. Accordingly, the claims are not directed to recognized categories of abstract ideas (e.g., fundamental economic practices or mental processes) under the 2019 Revised Patent Subject Matter Eligibility Guidance (page 3/8)”.
Examiner disagrees. Applicant’s arguments here, are similar to the one addressed above in the proceeding section.
Applicant argues that “The Federal Circuit, in cases like McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299 (Fed. Cir. 2016), and BASCOM Global Internet Servs. v. AT&T Mobility LLC, 827 F.3d 1341 (Fed. Cir. 2016), has emphasized looking to whether a claim's focus is a specific technical improvement or simply an abstract idea performed on a computer. Here, the focus is on a specific improvement in computer-related technology: a novel processing approach for predictive modeling in targeted content delivery systems. Accordingly, the claims are not directed to recognized categories of abstract ideas (e.g., fundamental economic practices or mental processes) under the 2019 Revised Patent Subject Matter Eligibility Guidance (page 3/8)”.
Examiner disagrees. BASCOM decisions (specific arrangement of devices and the significant steps of the abstract idea each device performs) provided the technological solution to a technological problem. In the instant case, there is no arrangement of devices which could be considered "additional elements" and no new networking protocol which could be considered an "additional element". The only additional elements in the instant case are a general-purpose computer with generic computer components and a standard encoding scheme which are merely used as tools to apply the abstract idea. Therefore, the instant claims are in no way similar to Bascom , which is directed to software, at a remote server, enabling individualized/customizable filtering websites/Internet content. Thus, the claimed invention, when implemented, does not improve the functionality of the computer nor does it improve a technology/technical field. There is no technical evidence/technical support in the Applicant's Specification of technical improvements or of a technical solution to a technical problem.
The McRO decision overcame 35 USC 101 under Step 2a, Prong 1 because they did not recite an abstract idea. While this makes an analysis under Step 2a, Prong 2 unnecessary, the court did find that the claims recite an improvement to a computer-related technology which is a consideration under Step 2a, Prong 2. Since, the claims did not recite an abstract idea, each and every limitation of the claim would be an "additional element" of the claim. The execution of these "additional elements" resulted in an improvement to a computer-related technology and, as such, would also overcome the 35 USC 101 rejection under Step 2a, Prong 2. In contrast, the claims of the instant invention do recite an abstract idea under Step 2a, Prong 2. The only "additional elements" of the instant claims are a general-purpose computer with generic computer components executing software. Thus, the instant claims merely apply the abstract idea using the general-purpose computer with generic computer components which is insufficient to transform an abstract idea into a practical application. Hence, the purported improvement of the instant claims is an improvement to an abstract idea which is an improvement in ineligible subject matter (see the SAP V. Investpic decision and the Recentive Analytics decision). As such Applicant's claimed solution is NOT technological and does not addresses a technological problem. Accordingly, the claim rejection of claims 1-4,6-11,13-22 under 35 USC § 101 is maintained.
Applicant argues that “ the present claims go well beyond performing a calculation or data analysis. The recited features in these claims - including training a model with real data, computing a specialized parameter offline via an exponentially saturating model, integrating that parameter into a real-time forecasting engine, and updating the model with live user data collected through controlled content serving - collectively define a particular, non-conventional system design. This system solves a technological problem (how to handle complex forecasting with a self-improving model and with reduced latency in a network environment) in a way that is necessarily tied to computer and digital network technology. Accordingly, the claims as a whole are not "directed to" a judicial exception, but to a specific improved system rooted in the technology of networking and network digital content delivery (page 4/8)”.
Examiner disagrees. Training a model with real data, computing a specialized parameter offline via an exponentially saturating model, integrating that parameter into a real-time forecasting engine, and updating the model with live user data collected through controlled content serving does not result in an improvement of the claimed additional elements of the machine learning, the computing device, model, an engine nor the user interface. As thus, those additional elements fails to (a) improve another technology or technical field and (b) improve the functioning of the computer itself and (c) applies the abstract idea with or by use of, a particular machine, which is a generic computer performing generic computer functions and are not seen to recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim as a whole merely describes how to generally “apply” the concept of gathering, obtaining, data in a computer environment. This judicial exception is not integrated into a practical application. The claim only recites the additional elements at a high level of generality performing a generic function and such it amounts no more than mere instructions to apply the exception using a generic computer components. Thus, even when viewed as a whole, nothing in the claim adds significantly more (ie an inventive concept) to the abstract idea. As such Applicant's claimed solution is NOT technological and does not addresses a technological problem. Accordingly, the claim rejection of claims 1-4,6-11,13-22 under 35 USC § 101 is maintained.
Step 2 A, Prong two:
Applicant argues that “the forecasting is not performed in isolation, but is tightly integrated with a specialized, dynamic user interface that facilitates interactive scenario testing. This is a meaningful application of the forecast calculation that improves the user's ability to configure a campaign in real time, which then directly affects parameters used for targeted digital content delivery. The Federal Circuit has held that an improved user interface can qualify as a technical improvement (e.g., Core Wireless Licensing v. LG Elecs., 880 F.3d 1356 (Fed. Cir. 2018); Data Engine Techs. v. Google LLC, 906 F.3d 999 (Fed. Cir. 2018)), and here the claims recite an interface that is designed to provide immediate, practical feedback with reduced latency in a way not existing in prior systems, thus integrating the predictive model into a user-facing application (page 5/8)”.
Examiner disagrees. In Core wireless, the patent discloses “improved display interfaces particularly to electronic devices with small screens, allowing user to more quick access to desired data stored in and functions of applications included in the device”. However, unlike the situation in Core Wireless, Applicant does not identify any problem particular to improving the functioning of the computer or to a graphical user interface that the claims overcome. Accessing dynamic user interface that facilitates interactive scenario testing does not improve the functionality of the computer neither result in reducing the number of user actions and interfaces required for a user notifications for a plurality of communications system or saving time to launching such applications. As such Applicant's claimed solution is NOT technological and does not addresses a technological problem. Accordingly, the claim rejection of claims 1-4,6-11,13-22 under 35 USC § 101 is maintained.
Applicant argues that “the machine learning model trained with this parameter is thereby able to produce an accurate forecast of unique users across days, which is a technical solution to a known problem in the field (standard linear extrapolation would over-count users across days). This is analogous to McRO, where a set of specific rules for lip synchronization was a practical application of an algorithm and improved the animation technology itself. Likewise, here the particular overlap model is applied within a computerized system to yield more accurate forecasting, providing a tangible technical benefit (page 5/8)”.
Examiner disagrees. The claims are more like Alice than McRO. The instant claims merely implement an old practice in a new environment (i.e., a computer environment). Although the instant claims require the use of a computer, it is this incorporation of a computer, not the claimed invention, that purportedly “improves the existing technological process” by allowing the automation of further tasks.
This does not make the instant claims eligible under the decision of McRO, which also involved claims involving rules. It’s not applying of the rules itself that made McRO statutory, however those rules are used in the claims for a specific way of improving computer technology, and those specific features “allow for the improvement realized by the invention,” such claims are patentable under 35 USC § 101. The instant claims ordered combination of steps, the machine learning model trained with this parameter is thereby able to produce an accurate forecast of unique users across days, which is a technical solution to a known problem in the field (standard linear extrapolation would over-count users across days), is an improvement of the abstract idea itself and not an improvement of the computer, the functioning of the computer itself or an improvement to another technology or technical field. Thus, the instant claims are not Analogous to McRO and are not patentable under 35 USC § 101. As such Applicant's claimed solution is NOT technological and does not addresses a technological problem. Accordingly, the claim rejection of claims 1-4,6-11,13-22 under 35 USC § 101 is maintained.
Applicant argues that “In Desjardins, as here, the claimed invention's focus was a technical improvement in how a model operates. Consistent with Desjardins (and Federal Circuit guidance like Enfish), the present claims specify a targeted model design, training, and deployment architecture (i.e., an offline-trained parameter integrated into a real-time forecasting engine) that improves system functioning (accuracy, latency, scalability) rather than merely executing an abstract idea on a generic computer. Accordingly, each independent claim includes specific technical features that work together to solve a concrete technological problem (fast, accurate cross-day reach forecasting) in an innovative way. As explained in MPEP § 2106.04(d)(1), examples of integration into a practical application include an improvement to computer functionality or the use of a particular machine - criteria met here. Therefore, even if a judicial exception were present, the claims as a whole integrate it into a practical application, rendering them eligible under Step 2A, Prong Two (page 6/8)”.
Examiner disagrees. The instant claims bear no similarity to the Ex Parte Desjardins Holdings decision, because the instant claim merely specify a targeted model design, training, and deployment architecture (i.e., an offline-trained parameter integrated into a real-time forecasting engine), whereas Ex Parte Desjardins (claims to a method of training a machine learning model were directed to improvements in the machine learning technology itself and additionally included data structure elements reciting adjustments in values to plurality of performance parameters while preserving prior vstepalues). Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision) (precedential), in which the specification identified the improvement to machine learning technology by explaining how the machine learning model is trained to learn new tasks while protecting knowledge about 2 previous tasks to overcome the problem of “catastrophic forgetting,” and that the claims reflected the improvement identified in the specification. Indeed, enumerated improvements identified in the Desjardins specification included disclosures of the effective learning of new tasks in succession in connection with specifically protecting knowledge concerning previously accomplished tasks; allowing the system to reduce use of storage capacity; and the enablement of reduced complexity in the system. Such improvements were tantamount to how the machine learning model itself would function in operation and therefore not subsumed in the identified mathematical calculation. In the Enfish decision the "additional element" of the self-referential database was considered an improved database, invented by the inventor, that operated in a manner different from traditional databases. Thus, in each of these cases, the improvement to the computer technology was rooted in the "additional elements" of the claim, wherein the additional elements were implemented using software. In contrast, the purported improvements in a computer technology by practicing the claims of the instant invention are rooted solely in the abstract idea itself which is merely applied using a general-purpose computer with generic computer components executing software which is an improvement to an abstract idea and, as such, an improvement in ineligible subject matter (see the SAP V. Investpic decision and the Recentive Analytics decision). Accordingly, the claim rejection of claims 1-4,6-11,13-22 under 35 USC § 101 is maintained.
Step 2 B:
Applicant argues that “Additionally, the claims recite an inventive concept that amounts to "significantly more" than any abstract idea. The ordered combination of elements in Claim 1 (similarly reflected in Claims 13 and 20) is not a well-understood, routine, or conventional arrangement. The specific approach of the system (including using an exponentially saturating overlap parameter, dividing processing between offline and online components, providing a dynamic forecasting interface, and implementing a feedback loop to update the model) is not conventional in the field. Even if individual components were known in isolation, the claims do not simply use them in a routine way. This particular combination yields a system that performs better (faster, more accurate) than prior art methods, indicating a non-obvious and inventive arrangement (see BASCOM, 827 F.3d at 1350, finding an inventive concept in a non-conventional and non-generic arrangement of known components). Therefore, the claims are narrowly tailored to a specific technique and thus do not risk preempting the abstract idea of "forecasting user engagement" in general. They leave room for other approaches to user forecasting and advertising; they seek only to protect this particular improved approach. Accordingly, under Step 2B, the claimed subject matter qualifies as patent- eligible by reciting significantly more than any abstract idea. In view of the foregoing, Claims 1, 13, and 20 are believed to recite patent-eligible subject matter under the controlling law and USPTO guidance. Applicant respectfully requests withdrawal of the § 101 rejection of these claims (page 7/8)”.
Examiner disagrees. BASCOM decisions (specific arrangement of devices and the significant steps of the abstract idea each device performs) provided the technological solution to a technological problem. In the instant case, there is no arrangement of devices which could be considered "additional elements" and no new networking protocol which could be considered an "additional element". The only additional elements in the instant case are a general-purpose computer with generic computer components which are merely used as tools to apply the abstract idea. As such, This judicial exception is not integrated into a practical application. The claim only recites the additional elements at a high level of generality performing a generic function and such it amounts no more than mere instructions to apply the exception using a generic computer components. Thus, even when viewed as a whole, nothing in the claim adds significantly more (ie an inventive concept) to the abstract idea. As such Applicant's claimed solution is NOT technological and does not addresses a technological problem. Accordingly, the claim rejection of claims 1-4,6-11,13-22 under 35 USC § 101 is maintained.
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 1-4,6-11,13-24 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 1-4,6-11,13-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the following abstract idea:
determining a reference impression-to-user ratio for a first time period based on historical campaign data and historical user data during the first time period, determining a predicted impression-to-user ratio for a second time period after the first time period based on the reference impression-to-user ratio and a training overlap factor, and training algorithm to generate a labelled number of unique users based on the reference impression-to-user ratio and the predicted impression-to-user ratio, provide a campaign;
receive, from, a user forecast request comprising user-selected campaign parameters;
determine, based on the user forecast request, campaign data associated with an advertising campaign;
generate, using the trained the algorithm and a parameter, a total number of unique users forecasted to be reached by the advertising campaign in a future time period based on the campaign data, wherein the parameter is computed asynchronously offline and periodically updated using an exponentially saturating overlap model based on historical user and campaign data, wherein the parameter indicates a rate of size increase of an overlap user set between unique users on different days, wherein an overlap factor between users on successive days is asynchronously computed offline based on the parameter and using the exponentially saturating overlap;
generate forecasted user data based on the total number of unique users; and
transmit, in response to the user forecast request, the forecasted user data to the campaign, wherein the campaign is configured to further provide updated forecasted user data based on changes to the user-selected campaign parameters in the campaign user interface;
selectively cause, according to the user-selected campaign parameters entered via the campaign impressions associated with the advertising campaign to be displayed on a website in response to search queries entered into the website;
capture user session data associated with displays of the impressions;
store the user session data with the user-selected campaign parameters in the historical user data and the historical campaign data; and
update using the user session data with the user-selected campaign parameters;
This judicial exception is not integrated into a practical application because the claim only recites the additional elements of a computer with one or more hardware processors coupled to a non-transitory memory and configured to execute software instructions (A system, comprising: a processor; and a non-transitory memory storing instructions and user interface to a computing device over a network; the machine learning model (e.g. a general purpose computer with generic computer components) and a database to perform the claimed functions amounts to no more than mere instructions to apply the exception using one or more general-purpose computers and one or more generic computer component.
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)):
receive, from, a user forecast request comprising user-selected campaign parameters (receiving data);
transmit, in response to the user forecast request, the forecasted user data to the campaign, wherein the campaign is configured to further provide updated forecasted user data based on changes to the user-selected campaign parameters in the campaign user interface ( transmitting data);
store the user session data with the user-selected campaign parameters in the historical user data and the historical campaign data ( storing data);
More, the additional technical elements above are recited at a high-level of generality (i.e., as a generic processor and generic computer components performing a generic computers function of processing, communicating and displaying) such that it amounts to no more than mere instructions to apply the exception using one or more general-purpose computers and 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 one or more computers, or merely uses computers 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.
Specifically, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a computer with one or more hardware processors coupled to a non-transitory memory and configured to execute software instructions, and a database A system, comprising: a processor; and a non-transitory memory storing instructions (e.g. a general purpose computer with generic computer component), to perform the claimed functions amounts to no more than mere instructions to apply the exception using one or more general-purpose computers and one or more generic computer component.
“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 one or more computers, 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 computer and generic computer components (as evidenced from paragraphs 41-55 of the applicant’s specification) and the affinity v Direct TV decision which states that a database is a generic computer component); 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)):
receive, from, a user forecast request comprising user-selected campaign parameters (receiving data);
transmit, in response to the user forecast request, the forecasted user data to the campaign, wherein the campaign is configured to further provide updated forecasted user data based on changes to the user-selected campaign parameters in the campaign user interface ( transmitting data);
store the user session data with the user-selected campaign parameters in the historical user data and the historical campaign data ( storing 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). For the same reason these elements are not sufficient to provide an inventive concept. For these reasons, there is no inventive concept in the claim, and thus the claim is not patent eligible. Same Judicial analysis is applied here to independent claims 13 and 20.
The dependent claims 2-4, 6-11, 13-24 are rejected under 35 U.S.C.101 because the claimed invention is directed to an abstract idea without significantly more. The claims merely add further details that narrow that abstract idea of, without significantly more. The dependent claims 2-4, 6-11, 13-22 appears to merely further limit the abstract idea of Certain methods of organizing Human Activity” as it relates to commercial interactions of advertising, marketing, or sales activities or behaviors; business relations), Thus, the dependent claims further narrows the abstract idea and/or recite additional elements previously rejected in the independent 1,13 and 20.
Possible Allowable Subject Matter
Claims 1-4,6-11,13-24 recite subject matter that would be allowable over the prior art if the Applicant were to be able to overcome the claim rejection under 35 USC § 101 above.
The following is a statement of reasons for the indication of allowable subject matter: The most relevant prior the examiner has found is:
Kalish et al, US pub No: 20160379244 A1 teaches The present teaching relates to forecasting a campaign performance using predictive modeling. In one example, a request for forecasting a campaign performance is received from a user. A plurality of parameters associated with the request are retrieved. A predictive score is generated based on the plurality of parameters. A variable vector is constructed based on one or more key performance indicators (KPIs) selected by the user. A campaign data matrix is generated in accordance with the predictive score based on the variable vector.
Jacobs et al, US Pub No: 20190114672 A1, teaches Application personalization techniques and systems are described that leverage an embedded machine learning module to preserve a user's privacy while still supporting rich personalization with improved accuracy and efficiency of use of computational resources over conventional techniques and systems. The machine learning module, for instance, may be embedded as part of an application to execute within a context of the application to learn user preferences to train a model using machine learning. This model is then used within the context of execution of the application to personalize the application, such as control access to digital content, make recommendations, control which items of digital marketing content are exposed to a user via the application, and so on.
Brenner et al, US Pub No: 20210264465 A1, teaches The present disclosure provides for management of impressions in advertisement campaigns. Impressions may be moved between different impression media based on performance metrics and historical data. Impression budgets may be modified in an active campaign based on forecasts determined using current performance data. Impression budgets may be reallocated between simultaneously active advertisement campaigns.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Chittilappily et al, US Pub No: 2017/0300939 A1 teaches A method, system, and computer program product for promotional offer spend management. A computer implementation commences upon performing calculations to predict future market response of presenting a particular offer to an audience. The prediction calculations include machine-learning processing of historical offer specification parameters that at least partially characterize the offer. The offer specification comprises a unique combination of parameters and respective media channels, which combination was not measured as pertains to that particular specific unique combination. A predicted market response to the unique offer delivered being over selected media channels is forecasted by using a predictive model.
Wang et al, US pub No: 2012/0158456 A1, teaches A method, advertising network, and computer readable medium for forecasting ad traffic based on business metrics in performance-based display advertising. The method commences by defining a set of advertising campaign parameters, the advertising campaign parameters comprising target predicates, a campaign pricing model, and a campaign performance model. The method continues by forecasting a supply of impressions satisfying target predicates, based on a statistical analysis of a historical dataset containing impressions satisfying target predicates. Once a measure of forecasted supply is known, an auction model serves for calculating the likelihood of winning the forecasted impression at auction, based the campaign pricing model and the campaign performance model. Having a forecasted supply, and also an assessment of the likelihood of winning at auction, the method proceeds by determining values for various performance metrics. The performance metrics are displayed; the user makes changes to any one or more of the advertising campaign parameters.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is files within TWO MONTHS from the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX Months from the mailing date of this final.
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/AFAF OSMAN BILAL AHMED/ Primary Examiner, Art Unit 3622
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