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 .
Status of Claims
This action is in response to amendment filed on 19 February 2026. Claims 1-3, 7-9, 11-13, and 17-19 have been amended. Claims 1-20 are currently pending and have been examined.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting over claims 1-20 of U.S. Patent No. 11,763,329 since the claims, if allowed, would improperly extend the “right to exclude” already granted in the patent.
The subject matter claimed in the instant application is fully disclosed in the patent and is covered by the patent since the patent and the application are claiming common subject matter, as follows:
18,771,248
11,763,329
A method, comprising:
receiving, by a server, from a plurality of computing devices, event data indicating completion of at least one objective of a plurality of objectives by a plurality of users associated with at least one network environment, each of the plurality of objectives defining a corresponding action to be completed;
applying, by the server, a machine learning model to the event data to determine a threshold against which to compare a remaining amount in a first account
associated with an administrator device of the at least one network environment, wherein the machine learning model is trained using historical data indicating a rate of completion of one or more of the plurality of objectives and previous transfers from the account;
verifying, by the server, a plurality of transactions transferred from the first account to a plurality of second accounts associated with the plurality of users based on the event data indicating the completion of the at least one objective;
determining, by the server responsive to verifying the plurality of transactions, that the remaining amount in the first account is less than the threshold determined using the machine learning model;
automatically generating, by the server, an alert message comprising an indicator that the remaining amount in the first account is less than the threshold; and
transmitting, by the server, the alert message to present via a graphical user interface of the account to provide the administrator device immediate access to information regarding the first account.
14. A method, comprising:
storing, by a service, on a municipal database, a plurality of goals managed by an administrator device and available for a plurality of students associated with a plurality of schools in a plurality of school districts;
providing, by the service, to a plurality of computer systems across the plurality of the school districts, access to data on the plurality of goals from which to select to complete;
receiving, by the service, from the plurality of computing systems across the plurality of school districts over a period of time when connected with the service, data indicating a completion of at least one goal of the plurality of goals by a subset of students of the plurality of students in at least one of the plurality of districts;
transferring, by the service, an amount from a municipal account into a plurality of student accounts corresponding to the subset of students based upon the received data over the period of time;
reconciling, by the service, a plurality of transactions by verifying, separate from the plurality of computer systems across the plurality of school districts, that the transfer of amounts from the municipal account are based upon completion of one or more the plurality of goals by one or more of the plurality of students in the school district;
determining, by the service a threshold against which to compare a remaining amount of the municipal account by applying a machine learning model to the data indicating the completion of the at least one goal of the plurality of goals, wherein the machine learning model is trained using historical data indicating a rate of completion of one or more of the plurality of goals and previous transfers of amounts from the municipal account; responsive to reconciling the plurality of transactions, determining, by the service, that a remaining amount in the municipal account is less than the threshold determined using the machine learning model;
automatically generating, by the service, an alert message comprising an indicator that the remaining amount in the municipal account is less than the threshold; and
transmitting, by the service, to the administrator device, the alert message via a graphical user interface for the municipal account to provide the administrator device immediate access to information regarding the municipal account.
Although the claims at issue are not identical, they are not patentably distinct from each other because: though the wordings are different, the limitation carried are either inherently implied or would have been obvious to one of ordinary skill in the art. 18/771,248 does not have steps of storing on multiple database. and providing to plurality of computer system across the plurality school district access to data…” however, does state data received by the server to be processed, therefore implies such data must be received and stored in the server, as also obvious to one ordinary skill in the art sever/database to be accessed. 18/771,248 recites “receiving, from a plurality of computing devices” vs “receiving, from the plurality of computer systems across the plurality of school districts over a period of time. One of ordinary skill in the art would have contemplated data indicating a completion of goal must have received to its destination from either plurality of computing device/computer system from users/students. While the nature of data source and the destination are different, however, do not result in a patentable distinction in either case the data indicating the completion of the goal mut be revived from a certain source to be processed. 18/771,248 differs with the patent at the step of “applying, by the server, a machine learning model to the data to determine a threshold against which to compare a remaining amount in a first account associated with an administrator device, wherein the machine learning model is trained using historical data indicating a rate of completion of one or more of the plurality of goals and previous transfers from the account”. The patent however recites “wherein the machine learning model is trained using historical data indicating a rate of completion of one or more of the plurality of goals and previous transfers of amounts from the municipal account”, therefore one of ordinary skill in the art would have contemplated prior to training the machine learning the data must be applied to establish the necessary training. 18/771,248 ’s another major difference in language by the lacking of steps of transferring an amount from a municipal account into a plurality of student accounts corresponding to the subset of students based upon the received data over the period of time” . This omitted step refer to a providing access to account where an applicant is claiming an invention that is merely a step or part of a previously claimed broader invention, effectively extending the patent term of the prior invention Further, it is widely known in the art that, in order to effectively preserve a right to broader limitation.
Claims 1-20 are rejected on the ground of nonstatutory double patenting over claims 1-20 of U.S. Patent No. 12,314,973 since the claims, if allowed, would improperly extend the “right to exclude” already granted in the patent.
The subject matter claimed in the instant application is fully disclosed in the patent and is covered by the patent since the patent and the application are claiming common subject matter, as follows:
18/771,248
12,314,973
A method, comprising:
receiving, by a server, from a plurality of computing devices, event data indicating completion of at least one objective of a plurality of objectives by a plurality of users associated with at least one network environment, each of the plurality of objectives defining a corresponding action to be completed;
applying, by the server, a machine learning model to the event data to determine a threshold against which to compare a remaining amount in a first account associated with an administrator device of the at least one network environment, wherein the machine learning model is trained using historical data indicating a rate of completion of one or more of the plurality of objectives and previous transfers from the account;
verifying, by the server, a plurality of transactions transferred from the first account to a plurality of second accounts associated with the plurality of users based on the event data indicating the completion of the at least one objective;
determining, by the server responsive to verifying the plurality of transactions, that the remaining amount in the first account is less than the threshold determined using the machine learning model;
automatically generating, by the server, an alert message comprising an indicator that the remaining amount in the first account is less than the threshold; and
transmitting, by the server, the alert message to present via a graphical user interface of the account to provide the administrator device immediate access to information regarding the first account.
A method, comprising:
receiving, by a server, from a plurality of computing devices, data indicating completion of at least one goal of a plurality of goals by a plurality of users across a plurality of networks, each of the plurality of goals defining a corresponding action to be completed;
reconciling, by the server, a plurality of transaction by verifying transfers from a first account to a plurality of second accounts associated with the plurality of users based on the data indicating the completion of the at least one goal;
applying, by the server, a machine learning model to the data, wherein the machine learning model is trained using historical data indicating a rate of completion of one or more of the plurality of goals and previous transfers from the account;
determining, by the server, based on applying the machine learning to the data, a threshold against which to compare a remaining amount in a first account associated with an administrator device;
determining, by the server responsive to reconciling, that the remaining amount in the first account is less than the threshold determined using the machine learning model;
automatically generating, by the server, an alert message comprising an indicator that the remaining amount in the first account is less than the threshold; and
transmitting, by the server, the alert message to present via a graphical user interface of the account to provide the administrator device immediate access to information regarding the first account.
Although the conflicting claims are not identical, they are not patentably distinct from each other because: though the wordings are different, the limitations carried are either inherently implied or would have been obvious to one of ordinary skill in the art. 18/771,248 recites “objective” vs “goals”, which is merely a different way of wording but both covers the same thing despite a slight difference of phrasing. 18/771,248 differs from the patent by stating “ reconciling, by the server, a plurality of transaction by verifying transfers from a first account to a plurality of second accounts associated with the plurality of users based on the data indicating the completion of the at least one goal” vs “ verifying, by the server, a plurality of transactions transferred from the first account to a plurality of second accounts associated with the plurality of users based on the event data indicating the completion of the at least one objective”. While the nature of the steps are different, however do not result in a patentable distinction, in either case, and but both covers the same thing despite a slight difference of wordings.
Furthermore, there is no apparent reason why applicant was prevented from presenting claims corresponding to those of the instant application during prosecution of the application which matured into a patent. See In re Schneller, 397 F.2d 350, 158 USPQ 210 (CCPA 1968). See also MPEP § 804.
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.
Step 1: The claims 1-10 are a method and claims 11-20 are a system. Thus, each independent claim, on its face, is directed to one of the statutory categories of 35 U.S.C. §101. However, the claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A-Prong 1: Independent claims (1 and 11) recite applying to the event data to determine a threshold against which to compare a remaining amount in a first account associated with using historical data indicating a rate of completion of one or more of the plurality of objective and previous transfers from the account; verifying transfers from the first account to a plurality of second accounts associated with the plurality of users based on the data indicating the completion of the at least one goal; determining, responsive to verifying the plurality of transactions, that the remaining amount in the first account is less than the threshold. These limitation as drafted, are a processes that, under its broadest reasonable interpretation, covers the performance of the limitation in the mind but for the recitation of generic computer compoints.
That is, other than reciting “by a server,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by a server” language, the claim encompasses the user comparing to verify the remain amount in a first account against the account threshold. The mere nominal recitation of a server and machine learning model does not take the claim limitation out of the mental processes grouping. Thus, the claim recites a mental process.
Step 2A-Prong 2: The claims recite the combination of addition elements: that a server is used to perform the receiving, applying verifying, determining, generating and transmitting steps, a machine learing model for performing the determining step. The server in the recited steps and machine learing model in the determining step in repose to applying data are recited at a high level of generality, i.e., as generic server and components performing a generic computer functions of processing data (verifying transfer from the first account to a plurality accounts in response received determined information). The receiving and transmitting is recited at a high level of generality (i.e., a general means of gathering and outputting via user interface for user determining step) and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The graphic user interface that performs the outputting step is also recited at a high level of generality, and merely automates the displaying the generated message. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component. The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer component. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to the abstract idea.
Step 2B: As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B. Here, the receiving step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The background of the example does not provide any indication that the server and machine learning model is anything other than a generic, off the- shelf computer component, and the Symantec, TLI, and OIP Techs. court decisions cited in MPEP 2106.05(d)(II) indicate that mere collection or receipt of data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Accordingly, a conclusion that the collecting step is well-understood, routine, conventional activity is supported under Berkheimer Option 2. For these reasons, there is no inventive concept
Depending claims 2, 3, 12 and 13, these claims recite limitation of applying data to the deteriming a predicted likelihood of at least on ..” that further defines the abstract idea noted above. In addition, they recite the additional elements server for performing the applying steps and a second machine learing model for performing the determining steps. The server and machine learing model are recited at a high level of generality such amount no more than mere instructions to apply the exception using a generic computer components. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract
idea. The claim is directed to the abstract idea.
Depending claims 4 and 14, these claims recite limitation that further defines the abstract idea noted above. These claims do not contain any further additional elements per step 2A prong 2. Therefore, they are considered patent ineligible for the reason give above.
Depending claims 5 , 7, 9, 10, 15, 17, 19 and 20 these claims recite limitation that further defines the abstract idea noted above. These claims do not contain any further additional elements per step 2A prong 2. Therefore, they are considered patent ineligible for the reason give above.
Depending claims 6, 8, 16 and 18, these claims recite limitation that further defines the abstract idea noted above. In addition, they recite the additional elements server for performing the transmitting step. The server are recited at a high level of generality such amount no more than mere instructions to apply the exception using a generic computer components. The receiving and transmitting is recited at a high level of generality (i.e., a general means of gathering and outputting via user interface for user determining step) and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
The closest prior art to the applicants’ claimed invention:
Meirov (US Pub., No., 2020/0364492 A1) focused there is provided a method of training a machine learning model adapted for guiding subjects to an instructional goal, the method comprising: a) executing, by a guidance system of a subject, a guidance behavior; and b) training the machine learning model, by a processor, with a training input comprising, at least, data indicative of a time of the execution of the guidance behavior, data indicative of a degree of completion of the instructional goal for the subject- at a given time, and data indicative of subject-specific information wherein the machine learning model is adapted to enable calculating a ranking derivative of an estimated likelihood of satisfaction of an instructional goal completion criterion (abstract), wherein the machine learning model is adapted to enable calculating a ranking derivative of an estimated likelihood of satisfaction of an instructional goal completion criterion(paragraph [0010]), and goal monitoring unit can collect information pertaining to whether or not instructional goal have been completed i.e. data indicative of satisfaction of the completion criteria (paragraph [0100]).
Rosenstein et al. (2020/0005157 A1) focused on systems and method for automated custom training of a scoring model are disclosed herein. The method include: receiving a plurality of responses received from a plurality of students in response to providing of a prompt; identifying an evaluation model relevant to the provided prompt, which evaluation model can be a machine learning model trained to output a score relevant to at least portions of a response; generating a training indicator that provides a graphical depiction of the degree to which the identified evaluation model is trained; determining a training status of the model; receiving at least one evaluation input when the model is identified as insufficiently trained; updating training of the evaluation model based on the at least one received evaluation input; and controlling the training indicator to reflect the degree to which the evaluation model is trained subsequent to the updating of the training of the evaluation model (abstract),
Mizuma et al (US Pub/. 2004/0033475 Al) discloses the present invention relates generally to educational systems, and may include methods of using a computer system to create student records in a database; methods of using a computer system to present student records stored in a computer database; methods for measuring a student's performance relative to predetermined educational goals; automated processes that utilize a relational database for student education; automated education management systems; and computer programs for automating an education system.
James-Hatter et al (US Pub., 2015/0050637 A1) discloses a system and method for assessing student performance. The method includes receiving student data, a set of predetermined thresholds, and an activity guide at a computer processor. The student data and third-party data are linked into a collected data, at least a part of which is evaluated against the set of predetermined thresholds (abstract), and on a periodic basis, the evaluated data can be reviewed with school officials and individual students, parents and mentors, to identify early intervention strategies when necessary, and to recognize and reward success of achievement goals (paragraph [0007]).
Del Vecchio et al (US Pub., No., 2015/0193867 Al) discloses the disclosed embodiments include methods and systems for providing account status notifications. The disclosed embodiments include, for example, a device for providing account status notifications including a memory storing software instructions and one or more processors configured to execute the software instructions to pe1fom1 operations.
Stringfellow (US Patent No., 10,783,544 Bl) discloses in one implementation, a system with a decentralized architecture to provide secure loyalty program includes a plurality of separate database systems to disperse storage of data for the secure loyalty program across a plurality of separate file systems with different authentication and encryption schemes, a loyalty program computer system to securely allocate loyalty rewards in real-time, a first intermediary computer system to securely manage and provide access to the first intermediary database system.
None of the above reference either alone or in combination teach or suggest the in response to completion of objective received across from plurality of networks environment applying, by the server, a machine learning model to the event data to determine a threshold against which to compare a remaining amount in a first account associated with an administrator device of the at least one network environment, wherein the machine learning model is trained using historical data indicating a rate of completion of one or more of the plurality of objectives and previous transfers from the account; verifying, by the server, a plurality of transactions transferred from the first account to a plurality of second accounts associated with the plurality of users based on the event data indicating the completion of the at least one objective; determining, by the server responsive to verifying the plurality of transactions, that the remaining amount in the first account is less than the threshold determined using the machine learning model; automatically generating, by the server, an alert message comprising an indicator that the remaining amount in the first account is less than the threshold; and transmitting, by the server, the alert message to present via a graphical user interface of the account to provide the administrator device immediate access to information regarding the first account.
Response to Arguments
Applicant's arguments of the 35 U.S.C 101 rejections with respect to claims 1-20 filed 19 February 2026 have been fully considered but they are not persuasive. Applicants’ arguments of the claims recite features reflect the technical solution to the technical problem as laid out in the specification is not persuasive.
The core of the claims involve monitoring user completion of objectives (actions), transferring funds, determining the back account balance is below threshold and setting an alert threshold for bank account based on those transfers, is a fundamental economic practices (monitoring) and a mathematical calculation, which is are consider abstract idea (economic activity/data processing) without a sufficient inventive concept. Further, the claims fall under the Alice Corp. v. CLS Bank precedent, determining if a bank account balance is below a threshold is a fundamental economic practice (monitoring) and a mathematical calculation, which are considered abstract ideas. Automating this on a generic server does not make it patent-eligible. The claimed element merely using “a trained neural network” or” machine learning model” to calculate a threshold does not on it own overcome the abstract idea rejection if the model is used in a conventional, non-technical way. The claims futher recite receiving event data and comparing an account balance to a threshold is a standard data processing task (gathering data, comping it, and sending an alert), which does not constitute a technical improvement in itself. The use of a server, computing device, and network environment are likely to be viewed as generic computer compoints acting in standard capacity (receiving data, processing it, sending alerts).
The claims to be eligible, the claim must be re-focused on a specific technological improvement to the computer system or the machine learning model itself (e.g., how the neural network's architecture reduces data processing loads), rather than just using it to analyze financial data. For the above reason, the 35 U.S.C 101 rejections is maintained.
Applicants’ arguments of technical improvement are reflected in the claims. For example, claim 1 is directed to a method for improving commucation across network environment and recites: “receiving, by the server in commucation with a plurlity of network environment….” See applicants argument in pages 12-13 of Applicants remark, applicants’ argument is not persuasive. The limitation of "improving communication across a network environment" typically arises an abstract idea (e.g., a method of organizing human activity or a mathematical algorithm) implemented using a conventional computer, rather than a specific technical improvement to the network technology itself.
As indicted above, the core of the claimed elements involves monitoring a remaining amount in a "first account" and setting a threshold based on historical transfer data. This is often viewed as a financial or business method (a "method of organizing human activity"). The generating an alert message based on a threshold comparison is a foundational computer function (automation of a manual check), which courts frequently consider an abstract idea on a computer. There is not technical improvement , the claims does not describe how the neural network is improved (e.g., new training method), bur rather what data is processes (historical rates of completion and transfer). The receipt of event data from multiple network environments is, in this context, considered routine data gathering, which is insufficient to make an abstract claims patentable. Thus, for the above reason, the 35 U.S.C 101 rejections is maintained.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SABA DAGNEW whose telephone number is (571)270-3271. The examiner can normally be reached 9-6:45.
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/SABA DAGNEW/Primary Examiner, Art Unit 3621
A method for improving communications across network environments, comprising:
receiving, by a server in communication with a plurality of network environments and an administrator device, from a plurality of computing devices across the plurality of network environments, event data indicating completion of at least one objective of a plurality of objectives by a plurality of users associated with at least one the plurality of network environments environment, each of the plurality of objectives defining a corresponding action to be completed, at least one of the plurality of computing devices in transit between a first network environment of the plurality of network environments to a second network environment of the plurality of network environments;
executing applying, by the server, a machine learning model [[to]] that receives the event data and determines to determine a threshold against which to compare a remaining amount in a first account associated with [[an]]the administrator device of the plurality of at least one network environments environment, the threshold defining a value for the remaining amount at which to cause automated generation of an alert message, wherein the machine learning model [[is]]comprises a neural network trained using historical data indicating a rate of completion of one or more of the plurality of objectives and previous transfers from the first account;
verifying identifying, by the server, a plurality of transactions values as transferred from the first account to a plurality of second accounts associated with the plurality of users based on the event data indicating the completion of the at least one objective;
determining, by the server responsive to verifying identifying transfer of the plurality of transactions values, that the remaining amount in the first account is less than the threshold determined using the trained neural network of the machine learning model; responsive to determining that the remaining amount is less than the threshold,
automatically generating, by the server, [[an]] the alert message comprising a graphical indicator to indicate that the remaining amount in the first account is less than the threshold, the alert message configured to provide immediate access to information regarding the first account; and
transmitting, by the server, the alert message to cause the administrator device to present the graphical indicator via a graphical user interface of the first account, the graphical user interface configured to provide and automatically authorize the administrator device immediate access to information regarding the first account responsive to presentation of the graphical indicator.