CTNF 19/197,411 CTNF 92928 DETAILED ACTION Acknowledgements This action is in response to Applicant’s filing on May 2, 2025 , and is made Non-Final . This action is being examined by James H. Miller, who is in the eastern time zone (EST), and who can be reached by email at James.Miller1@uspto.gov or by telephone at (469) 295-9082. Interviews Interviews are “indispensable to advance the prosecution of a patent application.” MPEP § 713. Accordingly, the following Examiner’s guidance and suggested workflow maximizes this benefit to Applicant by: (1) avoiding back and forth telephone calls for scheduling, (2) permitting Examiner out-of-office notifications to the Applicant when sending the agenda, and (3) permitting real-time document collaboration and screen sharing. Interviews are available by telephone or, preferably , by video conferencing using the USPTO’s web-based collaboration platform. Applicants are strongly encouraged to schedule via the USPTO Automated Interview Request (AIR) portal at http://www.uspto.gov/interviewpractice . If an interview is needed more quickly than permitted by the AIR scheduling tool, note this in the AIR remarks for consideration. The Examiner routinely considers such urgent requests when practicable. An agenda submitted when filing the AIR is strongly encouraged , because Examiners use agendas when determining whether to grant an interview. The AIR has character limits, so send the agenda contemporaneously to James.Miller1@uspto.gov and reference the AIR. After-Final Interviews Requests are granted only at the Examiner’s discretion and only if disposal or clarification for appeal may be accomplished with only nominal further consideration. MPEP § 713.09. An advance agenda explaining how the interview advances prosecution—e.g., through targeted arguments, identified Examiner error, or proposed claim amendments—is strongly suggested . For GRANTED requests, expect an email within two (2) business days confirming a date/time slot and collaboration tool access instructions. For DENIED requests, the record will include an explanation for the denial. The examiner is generally available for interviews, Monday through Friday, 10:00 a.m. to 4:00 p.m. ET. Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Information Disclosure Statement The information disclosure statement (IDS) submitted on May 2, 2025, was filed before the mailing of a first office action on the merits and therefore, is in compliance with the provisions of 37 CFR 1.97(b)(3). Accordingly, the IDS has been considered. Claim Status The status of claims is as follows: Claims 1–20 are pending and examined with Claims 1, 14, and 20 in independent form. This is a first action on the merits. Claim Objections 07-29-01 Claim 1, 14, and 20 are objected to because of the following informalities. Appropriate correction is required. Claims 1, 14, and 20 : It is believed that “generate, for each data structure of the plurality of data structure” and “storing, for each data structure of the plurality of data structure” are “generate, for each data structure of the plurality of data structure s ” and “storing, for each data structure of the plurality of data structure s ” to correct typographical errors. Claim Rejections - 35 USC § 112 07-30-02 AIA 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. 07-34-01 Claims 1–20 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 . Claims 1–20 : Independent Claims recite a machine learning program is “to output one or more suggested modifications based on an input target data structure, at least one input related data structure, and an input proposed modification ,” with the three input terms in italics lacking definitive antecedent basis. It is not clear whether the italicized input terms refer the previously recited claim terms or whether they are separate and distinct elements. The use of different terminology suggests that distinct elements are intended. However, if distinct, the claim recites no step of obtaining these distinct inputs. The boundaries of the claim are therefore unclear and a person of ordinary skill in the art would be unable to determine with reasonable certainty whether the machine learning program operates on the same data structures and proposed modification already recited in the body, or on additional, separately supplied inputs that the claim never affirmatively recites obtaining. All Independent Claims are implicated. Dependent Claims are rejected based on their dependence to one of the rejected Independent Claims. For examination purposes, "an input target data structure," "at least one input related data structure," and "an input proposed modification" are the previously recited "target data structure," "related data structures," and "proposed modification," respectively. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1–20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more. Analysis Step 1 : Claims 1–20 are directed to a statutory category. Claims 1–13 recite a “device” and are therefore, directed to the statutory category of a “machine.” Claims 14–19 recite a “method” and are therefore, directed to the statutory category of a “process.” Claim 20 recites a “non-transitory machine-readable storage medium having computer-executable instructions embodied thereon” and is therefore, directed to the statutory category of an "article of manufacture.” Representative Claim Claim 1 is representative [“Rep. Claim 1”] of the subject matter under examination. Normal font is used for limitations that recite the judicial exception. Bold font is used to indicate additional elements evaluated under Step 2A, Prong Two (practical application) and Step 2B (significantly more). Italics font is used where necessary to identify intended use limitations 1 and underline font is used, as needed, in further describing the judicial exception. Each limitation is identified by a letter designator for use as a shorthand notation when analyzing/referencing each limitation. Rep. Claim 1 recites: [A] 1. A computing device for managing a database , [A1] the database 2 storing a plurality of data structures 2 configured to generate one or more output values based on one or more input values 3 and one or more data parameters 2 , [A2] the computing device comprising at least one processor in communication with at least one memory device and the database , the at least one processor configured to: [B] generate, for each data structure of the plurality of data structure , one or more tags based on the one or more data parameters of each data structure , wherein the tags represent categories of input data of the one or more input values that trigger generation of one or more output values for a corresponding data structure ; [C] store, for each data structure of the plurality of data structure , the one or more tags corresponding to the data structure in the database ; [D] receive, from a first user computing device , a proposed modification to at least one of the data parameters of a target data structure ; [E] identify at least a first tag of the one or more tags associated with the target data structure that corresponds to the at least one of the data parameters relating to the proposed modification; [F] parse the database using at least the first tag to identify one or more related data structures of the plurality of data structures , the one or more related data structures including at least one tag matching the first tag; [G] generate, for each of the related data structures , at least one suggested modification using a machine learning program , the machine learning program trained to output one or more suggested modifications based on an input target data structure, at least one input related data structure, and an input proposed modification ; and [H] provide instructions configured to cause the first user computing device to display a user interface including the target data structure , the one or more related data structures , and the at least one suggested modification for each of the one or more related data structures . Claims are directed to an abstract idea exception. Step 2A, Prong One : Rep. Claim 1 recites “[B] generate … one or more tags based on the one or more data parameters;” “[C] store … the one or more tags;” “[D] receive … a proposed modification to at least one of the data parameters;” “[E] identify at least a first tag of the one or more tags … that corresponds to the at least one of the data parameters relating to the proposed modification;” “[F] parse [the database] using at least the first tag … ;” and “[G] generate … at least one suggested modification,” which recites the abstract idea exception of mental processes that under the broadest reasonable interpretation, cover performance in the human mind or with pen and paper, but fo r the recitation of the generic computer components indicated in bold , supra . MPEP § 2106.04(a)(2)(III). Claims recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include: • a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A. , 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016); . . . • a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen IDEC , 659 F.3d 1057, 1067, 100 USPQ2d 1492, 1500 (Fed. Cir. 2011). MPEP § 2106.04(a)(2)(III)(A). For example, but for the generic computer components claim language, here, Limitations B–H , recite collecting information ( Limitations C, D ) analyzing it ( Limitations B, E, F, G) , and displaying certain results of the collection and analysis (Limitations H), where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind. For example, Limitations B and G are mental processes that are practically performed in the human mind or with pen and paper because they requires mere “observation, evaluation, judgment, and/or opinion” to “generate … one or more tags based on the one or more data parameters” (Limitation B) and “generate … at least one suggested modification” (Limitation G) in any known way. Limitation B covers any solution to “generat[ing] … one or more tags based on the one or more data parameters” with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, which is so broad as to encompass mental processes. The specification confirms that tags are generated merely “based on the data elements of the rule and/or data field,” without any specific technological mechanism for accomplishing the result. Spec. ¶¶ 27, 48. Limitations E and F are mental processes that is practically performed in the human mind or with pen and paper because collecting (i.e., the “first tag”) and comparing known information (i.e., “at least one tag matching the first tag”) are steps that can be practically performed in the human mind under Classen . The specification confirms that this “comparing” is merely comparing tags to find matches. Spec. ¶¶ 30, 51. The recitation of generic computer components (a processor, a memory device, and a database) to perform these acts does not remove the limitations from the mental process grouping, because a claim that recites a mental process performed on a generic computer still recites an abstract idea. See MPEP § 2106.04(a)(2)(III)(C). If a claim limitation under BRI, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract idea exception. MPEP § 2106.04(a)(2)(III). Step 2A, Prong Two : The additional elements identified in Rep. Claim 1, considered individually and as an ordered combination, do not integrate the abstract idea exception into a practical application. MPEP § 2106.04(d). The additional elements are limited to the computer components and indicated in bold , supra . The additional elements are: A computing device comprising at least one processor and at least one memory device; a database storing a plurality of data structures (e.g., a corresponding data structure, a target data structure, and one or more related data structures); a first user computing device; a machine learning program trained to output one or more suggested modifications based on an input target data structure, at least one input related data structure, and an input proposed modification; and instructions configured to cause the first user computing device to display a user interface. The additional elements do not improve the functioning of a computer or other technology. MPEP § 2106.05(a) . A claim improves technology only when it recites a specific improvement to the way a computer itself operates, not merely the application of an existing process using a computer. MPEP § 2106.05(a) (citing Enfish, LLC v. Microsoft Corp. , 822 F.3d 1327, 1336 (Fed. Cir. 2016)). Here, the abstract idea exception was previously performed manually, Spec. ¶ 3 (“Manual modification of data structures”). Because the process can be performed manually, the computer is not being improved and is merely being used as a tool to perform the pre-existing manual process. Applying a pre-existing manual process using generic computer components, even via a user interface (UI), is not an improvement to computer technology. The specification confirms this characterization by describing the asserted advantages of the claimed system in terms of business outcomes of the abstract idea itself (e.g., identifying related rules to modify, generating suggested modifications, automatically modifying rules, “improved efficiency in updating rules and bringing the system back online,” and “reducing errors and reducing or improving bandwidth by identifying all rules that need to be modified”). Spec. ¶¶ 33, 34. The specification’s assertion that a “data structure that increases data storage efficiency of a database for a data processing network” or “increased computing efficiency” (Spec. ¶ 34), these asserted benefits are not reflected in the claims themselves as no particular data structure is claimed. Claims recite only a generic “data structure.” The specification does not describe any specific technical improvement in the way the processor executes instructions, the way in which the database stores or retrieves data, network communication protocols, encryption, display technology, rendering algorithms, data structures, or computer architecture. Spec. ¶¶ 30–40, 57–61. Further, the specification describes the UI elements (e.g., rules search field, rule “card” or list entries displaying rule numbers and data elements, etc.) only at a high functional level without any unconventional technical mechanism. Spec. ¶¶ 55, 56, Figs. 10–12. Thus, these are generic UI elements. Any improvements describe outcomes of the abstract idea, not technical improvements to the computers themselves. The additional elements do not apply the abstract idea with a particular machine. Although the claims recite specific hardware components (i.e., a computing device, at least one processor, at least one memory device, a database, and first user computing device ), these components are recited at a high functional level and perform only their generic functions of receiving, transmitting, storing, and processing data. Spec. ¶¶ 42, 43, 53, 58–61. A machine is “particular” only when it imposes a meaningful limit on the claims scope. MPEP § 2106.05(b). Here, any general-purpose computer, server, database, and user computing device would satisfy the claim’s hardware requirements, which confirms that the hardware components are generic rather than “particular.” MPEP § 2106.05(b). The specification describes each computer component using broad, open-ended language without restricting the claimed hardware to any particular design, configuration, or architecture. Spec. ¶¶ 38, 39, 40, 60. The additional elements are mere instructions to apply the abstract idea exception, MPEP § 2106.05(f); (2) generally link the judicial exception to a particular technological environment, MPEP § 2106.05(h); and/or (3) are insignificant extra solution activity, MPEP § 2106.05(g) . Regarding the additional elements, Applicant’s Specification does not otherwise describe them with specificity beyond exemplary language and instead describes them as a general-purpose computer, as a part of a general-purpose computer, or as any known and exemplary (generic) computer component known in the prior art. The specification’s own broad, exemplary characterization confirms that these components are not described in a manner that would impose any specific technical limitation that would integrate the abstract idea into a practical application. The specification failure to describe these components in any detail beyond exemplary language is itself an admission that the components are so well known to those of ordinary skill in the art that no explanation is needed under 35 U.S.C. § 112(a). Lindemann Maschinenfabrik GMBH v. Am. Hoist & Derrick Co. , 730 F.2d 1452, 1463 (Fed. Cir. 1984) (citing In re Meyers , 410 F.2d 420, 424 (CCPA 1969) (“[T]he specification need not disclose what is well known in the art”). E.g. , Spec. ¶ 38 (known and generic (exemplary) database ), ¶ 39 (known and generic (exemplary) computer processor ), ¶ 40 (known and generic (exemplary) memory ), ¶¶ 42, 43, 53, 58 (known and generic (exemplary) RM computing device, sever, processor/memory, and computer ), ¶¶ 42, 53 (known and generic (exemplary) user computing device ), ¶¶ 55, 56 (known and generic (exemplary) user interface ), ¶¶ 56, 57 (known and generic (exemplary) computer-executable instructions). The generic processor, here, executes instructions that are programmed by software directed to the abstract idea. Spec. ¶ 57. This is a computer doing what it is designed to do—performing directions it is given to follow, and whose directions are directed to the abstract idea. The displaying and user interface steps, Limitation H does not provide a practical application because it merely describes the field of use and technical environment in which the abstract idea is implemented, without resulting in an improvement to the computer or UI itself. MPEP 2106.05(h) (citing Electric Power Group ). The specification confirms that the UI elements (e.g., rules search field, rule “card” or list entries displaying rule numbers and data elements, etc.) are described only at a high, functional level without any specific technical improvement to the UI or display technology. E.g., Spec. ¶¶ 54, 55, 56, Figs, 10–12. Further, requiring the use of software to tailor information and provide it to the user on a generic computer also does not provide a practical application. MPEP § 2106.05(f) (citing Intellectual Ventures I LLC v. Capital One Bank (USA) , 792 F.3d 1363, 1370-71, 115 USPQ2d 1636, 1642 (Fed. Cir. 2015)). Regarding the machine learning program trained to output one or more suggested modifications based on an input target data structure, at least one input related data structure, and an input proposed modification , Applicant’s Specification explains it can be created in any known way using any known, artificial intelligence (AI) and/or machine learning technique, such that it could be almost anything. Spec. ¶¶ 31, 52, 63, 73, 86, 99. The trained model itself is created outside the scope of the claims and as claimed, receives inputs and provides an output, in this case a proposed modification, like any model. Therefore, the “trained machine learning program” characterization imparts no specific functional or structural limitation to the claimed “program” beyond the generic capability of any model. This describes a solution merely at the level of a “generic black box” for determining a proposed modification and reads neatly on “use a computer” to do it in any way. MPEP § 2106.05(f); see also , Recentive Analytics, Inc. v. Fox Corp. , 2025 U.S.P.Q.2d 628 (Fed. Cir. 2025) (holding “that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101”). Limitation A describes the functions of the processor in “communication” with a “memory” and “database” to perform the steps of the claimed invention. This takes a known and exemplary (generic) piece of hardware and describes the functions of transmitting and receiving data between the processor, memory, and database, which merely invokes computers or other machinery in thier ordinary capacity to receive, store, or transmit data. MPEP § 2106.05(f)(2). Limitations B–H describe the processor, memory, and database, performing the steps of the claimed invention, which represents the abstract idea exception itself. Performing the steps of the abstract idea exception using a computer, merely adds a general-purpose computer after the fact to an abstract idea exception without imposing any meaningful technical limitations. MPEP § 2106.05(f)(2). Alternatively , the claim generically recites an effect of the abstract idea without specifying how the computer achieves that effect in any technically meaningful way. MPEP § 2106.05(f)(3). Therefore, the claim as a whole, considering the additional elements individually and as an ordered combination, amounts to no more than mere instructions to apply the abstract idea using generic computer components and is not a practical application. MPEP § 2106.05(f). The additional elements do not integrate the abstract idea exception into a practical application because they do not impose any meaningful limits on the abstract idea exception. Accordingly, Rep. Claim 1 is directed to an abstract idea. Independent Claims 14 and 20 are not substantially different than Rep. Claim 1, recite the same abstract idea as Rep. Claim 1, and contain no additional elements not otherwise analyzed for Rep. Claim 1. Therefore, Independent Claims 14 and 20 are also directed to the same abstract idea. The claims do not provide an inventive concept. Step 2B : Rep. Claim 1 fails Step 2B because the claim as a whole, even when considering the additional elements individually and in combination, does not amount to significantly more than the abstract idea. MPEP § 2106.05. The additional elements (i.e., a computing device comprising at least one processor and at least one memory device; a database storing a plurality of data structures (e.g., a corresponding data structure, a target data structure, and one or more related data structures); a first user computing device; a machine learning program trained to output one or more suggested modifications based on an input target data structure, at least one input related data structure, and an input proposed modification; and instructions configured to cause the first user computing device to display a user interface) , are each well-understood, routine, and conventional (“WRC”) computer components and functions in the relevant field, as evidenced by Applicant’s own disclosure 4 . Further, Applicant’s Specification discloses that these components are implemented using generic, off-the-shelf computing technology that is “flexible and designed to run in various different environments without compromising any major functionality … [and] components of each system and each process can be practiced independently and separately from other components and processes described herein.” Spec. ¶ 35; ¶¶ 38–40, 42, 43, 53, 57–61 (describing each component using exemplary language as generic or known computing equipment and networks). (1) A computing device comprising at least one processor and at least one memory device and a first user computing device are WRC in the financial technology field. Spec. ¶¶ 39, 40, 42, 43. (2) A database storing a plurality of data structures (e.g., a corresponding data structure, a target data structure, and one or more related data structures) is WRC. Spec. ¶¶ 38 (any database may be used that enables the systems and methods described herein).” (3) A machine learning program trained to output one or more suggested modifications based on an input target data structure, at least one input related data structure, and an input proposed modification recites WRC functions of any program/model. Spec. ¶ 31 (“the RM computing device may utilize artificial intelligence and/or machine learning techniques to generate suggested modifications”); ¶¶ 52, 66, 73, 86 (same); ¶ 99 (a processing element may employ artificial intelligence and/or be trained using supervised or unsupervised machine learning, and the machine learning program may employ a neural network, which may be a convolutional neural network, a deep learning neural network, or a combined learning module or program”). (4) instructions configured to cause the first user computing device to display a user interface are WRC. Spec. ¶¶ 54, 55, 56. The Specification further confirms that the functions of receiving, storing, transmitting, and processing data are normal, well-understood operations of generic computer systems, and the steps may be performed in any order or concurrently. See, e.g. , Spec. ¶¶ 42, 43, 58–61. The combination is also WRC at the high level of generality recited : The combination of the additional elements is likewise WRC. A combination of individually well-understood, routine, and conventional elements does not provide an inventive concept unless the combination itself produces an unconventional result or is applied in an unconventional manner. MPEP § 2106.05(d). Here, the combination performs each step in exactly the manner described as conventional throughout Applicant’s own Specification. There is no indication that the combination of these elements operates in an unconventional manner or produces a result that is other than what would be expected from the generic application of these individual components. Unlike BASCOM , where the claims recited a specific non-conventional arrangement of installing a filtering tool at a specific network location (an ISP server) rather than on individual end-user devices, Rep. Claim 1 does not recite how the elements are combined in a non-conventional way. The claims recite each element at a high level of generality without specifying the particular arrangement or order that constitutes the alleged improvement. At the high level of generality recited, the combination is WRC. Any BASCOM argument fails because nothing in Applicant’s Specification describes a non-conventional ordered arrangement of components that is then recited in the claims. Rep. Claim 1 recites only the abstract steps of generating tags, storing tags, receiving a proposed modification, identifying a tag, parsing, and generating a suggested modification without incorporating any specific technical details for how these elements are performed. A non-conventional arrangement that is described but not claimed cannot supply the inventive concept at Step 2B. Because the claims here recite only generic components performing generic functions at a high level of generality, the claim is not an improvement to the computer or another technology. MPEP § 2106.05(f). No inventive concept is present under Step 2B. MPEP § 2106.05(d). The trained machine learning program is well-understood and merely operates on the generic components. NPL Leskovec, Jure, Anand Rajaraman, and Jeffrey David Ullman, "Mining of Massive Datasets," (2019), § 13.2.9 (“Classification Loss”) at 537–38, and § 12.1.2 (“Some Illustrative Example” performed by hand), Example 12.1, at 464–65 (“NPL Leskovec”) (cited herein on PTO-892); see also Recentive Analytics, Inc. v. Fox Corp. , 2025 U.S.P.Q.2d 628 (Fed. Cir. 2025) (holding “that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101”). Here, as in Recentive , the claim applies a generic machine learning program to a new data environment (a rules/data-structure database) without disclosing any improvement to the model itself. Spec. ¶¶ 31, 52, 66, 73, 99. Accordingly, the additional elements of Rep. Claim 1 have been recognized, based on Applicant’s own disclosure, as WRC activity in the field. MPEP § 2106.05(d). These elements do no more than “apply” the recited abstract idea(s) using known computer and computer-related components. See also Step 2A, Prong Two, supra . Independent Claim 20 is a computer-readable medium claim whose instructions cause at least one processor to perform the same abstract processing and generic computer operations recited in Rep. Claim 1. Independent Claim 14 is a method claim reciting steps that perform the same abstract processing and generic computer operations recited in Rep. Claim 1. Independent Claims 14 and 20 add no additional elements beyond those of Rep. Claim 1 that would amount to significantly more than the abstract idea. Therefore, Independent Claims 14 and 20 also do not recite an inventive concept under Step 2B. Dependent Claims Not Significantly More The dependent claims have been given the full two-part analysis including analyzing the additional limitations both individually and in combination with the elements of the independent claims. Each dependent claim incorporates all the limitations of its parent Independent Claim and therefore recites the same abstract idea. The additional limitations recited in the dependent claims do not integrate the abstract idea exception into a practical application under Step 2A, Prong Two, and do not amount to significantly more than the abstract idea under Step 2B, for the following reasons: Dependent Claims 2 and 15 merely further describe the conventional training of the same generic machine learning program and “recognizing patterns” in data is itself an abstract mental process (observation/evaluation) or a generic WRC machine learning function. See NPL Leskovec (portions cited supra ). At Step 2A, Prong Two, training a generic machine learning model in any way to recognize patterns does not improve the computer or any other technology and merely applies the abstract idea with a generic computer. MPEP § 2106.05(f). The specification discloses the use of machine learning technology and artificial intelligence at the generic level and “in any known way,” without disclosing any improvement to the model. Spec. ¶¶ 31, 52, 66, 73, 99, 100, 101. At Step 2B, pattern-recognition training is WRC machine learning function and supplies no inventive concept. NPL Leskovec (portions cited supra ); Recentive (quotation cited supra ). Dependent Claims 3, 4, 5, 16, and 17 recite further steps of the abstract idea and merely append insignificant extra-solution activity. The specification discloses building and storing modified rules and displaying modifications at additional user computing devices as ordinary operations of the RM computing device and generic user computing devices. Spec. ¶¶ 29, 50, 52. Mere storage of data and transmission of data for display are insignificant extra-solution activity and does not integrate the abstract idea into a practical and is WRC at Step 2B. Dependent Claims 6 and 18 recite generic, conventional database check-out/check-in operation that merely governs which user may modify a record. The specification discloses the check-out/check-in flag at a functional level as an ordinary database operation performed by a generic database module. Spec. ¶¶ 28, 49, 63, 92, 93. Flagging a record a check-in or check-out are insignificant extra-solution activity and does not integrate the abstract idea into a practical and is WRC at Step 2B. Dependent Claims 7, 8, and 19 recite organizing information hierarchically and labeling items by their location or identifier, which recite a method of organizing human activity and mental process exception, recited on by functionally (by result) and without reciting any specific data structure that achieves the organization. The specification describes the hierarchy as an optional organization scheme and not as an improvement to database functionality. Spec. ¶¶ 26, 47, 78. Because the claims recite the result rather than a particular, no-generic way of achieving it, they do not improve the functioning of the computer or database and do not integrate the abstract idea into a practical application or inventive concept. Dependent Claims 9, 10, 11, and 12 merely narrows the data on which the abstract idea operates. The specification discloses input values as billing events, tags generated from data elements as rules conditions, and output as a generated document. (e.g., an invoice), all generic data. Spec. ¶¶ 24, 25, 27. Limiting the abstract idea to a field of use or particular data types does not integrate the abstract idea int a practical application and does not provide an inventive concept. MPEP § 2106.06(h). Dependent Claim 13 recites applying a rule to an input to produce an output performed by a generic processor. The specification describes rule execution generically. Spec. ¶¶ 3, 24, 44, 45. Executing a data structure to compute an output is a normal function of generic computer and WRC. MPEP § 2106.05(f). Combined Consideration . Considered in any combination, the dependent claims' additional limitations merely add further rule-management sub-steps or narrow the data on which the abstract idea operates. None of these limitations recites a particular machine, a non-conventional ordered arrangement of components in the sense of BASCOM , or any specific technical mechanism for performing the recited steps. The limitations, considered as an ordered combination, do no more than the limitations considered individually and add nothing beyond generic computer components performing their ordinary functions. Accordingly, none of Dependent Claims 2–7, 9, 10, 12–17, and 20 integrates the abstract idea into a practical application under Step 2A, Prong Two, and none amounts to significantly more than the abstract idea under Step 2B. Conclusion Claims 1–20 are therefore drawn to ineligible subject matter as they are directed to an abstract idea without significantly more. The analysis above applies to all statutory categories of invention. As such, the presentment of Rep. Claim 1 otherwise styled as another statutory category is subject to the same analysis. Examiner Statement of Prior Art—No Prior Art Rejections The § 112(b) rejection supra , explains that the limitation "generate, for each of the related data structures, at least one suggested modification using a machine learning program trained to output one or more suggested modifications based on an input target data structure, at least one input related data structure, and an input proposed modification" is indefinite. Because the metes and bounds of this limitation cannot be determined, a prior-art rejection directed to this limitation would necessarily be based on speculation and is not made at this time. MPEP § 2143.03. Based on the prior art search results, the prior art of record does not appear to teach or suggest using a machine learning program, as opposed to user-performed correction, to generate the recited suggested modifications as recited by Independent Claims and as interpreted by the Examiner (See § 112(b) rejection supra ). Tan (U.S. Pat. Pub. No. 2009/0299949) is directed to limiting the modifiability of rules through tags that constrain how rule components may be edited (Tan, ¶ 25 (“tags that may be authored to limit how rules in the rule base database 112 may be modified”); ¶ 27 (allow a user … to limit how elements of rules may be modified and who may make such modifications”), and its "inference engine" applies deterministic, tag-defined value constraints rather than a trained machine learning program (Tan, ¶ 30 (“interference engine 210 … a tag may set a range of acceptable values that must be within a certain percentage of an average of values that already exist for a particular field”). Studer et al. (U.S. Pat. Pub. No. 2020/0326933) discloses deterministic state/version propagation among grouped rulesets and regeneration of a transform upon rule edits (Studer, ¶ 63 (“The generator may also update the transform when the rule set is edited”); ¶ 71 (“the modification can propagate to the process management application 28 and affect the outputs of the application”); ¶ 87 (“when a ruleset is promoted or demoted to be associated with a different state, the content of the tag is updated to reflect the current state associated with the ruleset”), but likewise does not employ a machine learning program to generate suggested modifications. Brisimi et al. (U.S. Pat. Pub. No. 2020/0160191) employs a machine learning classifier to identify rules as correct/incorrect for subsequent user correction (Brisimi, ¶ 60 (“The correction component 450 may use one or more modifications to the one or more rules to revise similar rules having incorrect data”); ¶ 63 (“The machine learning component 470 may learn, determine, or identify the incorrect data relating to the one or more rules and one or more user-provided modifications to the one or more rules, and/or revise the one or more rules according to collected feedback from a user”); ¶ 73 (“one learned model may be a decision tree or an artificial neural network ("ANN") that takes as input a rule and returns a label such as "correct rule" or "incorrect rule." The incorrect rules may then be presented to the user. Once the user corrects the rule …”) rather than to generate suggested modifications from the recited inputs. In Brisimi, the correction is performed by the user, and the system reuses that user-supplied modification to revise similar rules. Brisimi, ¶ 73. Upon resolution of the rejection under § 112(b), the claims will be re-examined, and an updated search and any appropriate prior-art rejection will be considered. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES H MILLER whose telephone number is (469)295-9082. The examiner can normally be reached M-F: 10- 4 PM (EST). Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bennett M Sigmond can be reached at (303) 297-4411. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JAMES H MILLER/Primary Examiner, Art Unit 3694 Application/Control Number: 19/197,411 Page 2 Art Unit: 3694 Application/Control Number: 19/197,411 Page 3 Art Unit: 3694 Application/Control Number: 19/197,411 Page 4 Art Unit: 3694 Application/Control Number: 19/197,411 Page 5 Art Unit: 3694 Application/Control Number: 19/197,411 Page 6 Art Unit: 3694 Application/Control Number: 19/197,411 Page 7 Art Unit: 3694 Application/Control Number: 19/197,411 Page 8 Art Unit: 3694 Application/Control Number: 19/197,411 Page 9 Art Unit: 3694 Application/Control Number: 19/197,411 Page 10 Art Unit: 3694 Application/Control Number: 19/197,411 Page 11 Art Unit: 3694 Application/Control Number: 19/197,411 Page 12 Art Unit: 3694 Application/Control Number: 19/197,411 Page 13 Art Unit: 3694 Application/Control Number: 19/197,411 Page 14 Art Unit: 3694 Application/Control Number: 19/197,411 Page 15 Art Unit: 3694 Application/Control Number: 19/197,411 Page 16 Art Unit: 3694 Application/Control Number: 19/197,411 Page 17 Art Unit: 3694 Application/Control Number: 19/197,411 Page 18 Art Unit: 3694 Application/Control Number: 19/197,411 Page 19 Art Unit: 3694 Application/Control Number: 19/197,411 Page 20 Art Unit: 3694 Application/Control Number: 19/197,411 Page 21 Art Unit: 3694 Application/Control Number: 19/197,411 Page 22 Art Unit: 3694 Application/Control Number: 19/197,411 Page 23 Art Unit: 3694 Application/Control Number: 19/197,411 Page 24 Art Unit: 3694 Application/Control Number: 19/197,411 Page 25 Art Unit: 3694 1 Statements of intended use fail to limit the scope of the claim under BRI. MPEP § 2103(I)(C). 2 Preamble structure necessary to give meaning to the body of the claim. MPEP 2111.02. 3 Preamble structure not necessary to give meaning to the bod of the claim. MPEP 2111.02. 4 See Changes in Examination Procedure Pertaining to Subject Matter Eligibility, Recent Subject Matter Eligibility Decision (Berkheimer v. HP, Inc.) , 3-4, https://www.uspto.gov/sites/default/files/documents/memo-berkheimer-20180419.PDF (April, 18, 2018) (That additional elements are well-understood, routine, or conventional may be supported by various forms of evidence, including "[a] citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s).").
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