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
This is a final rejection. Claims 1-4, 7-8, 10-15, 17-18, and 20-25 are pending.
Information Disclosure Statement (IDS)
The information disclosure statement(s) filed on 02/24/2022, and 12/14/2022 comply with the provisions 37 CFR 1.97, 1.98, and MPEP 609 and is considered by the Examiner.
Status of Claims
Applicant’s amendment date 01/29/2026, Amending Claims 1, 12, and 15.
Response to Amendment
The previously pending rejection under 35 USC 101, will be maintained. The 101 rejection is updated in light of the new claims.
With regard to the rejection under 35 USC 103- with respect to the art rejection have been fully considered and are persuasive, the rejection under 35 USC 103 has been withdrawn. No art rejection has been put forth in the rejection for the reason found in the “Allowable Subject Matter” section found below and in view of applicant remarks 08/28/2025 pages 14-15.
Response to Arguments
Applicant's arguments filed 01/29/2026 have been fully considered but they are not persuasive, moreover, any new grounds of rejection have been necessitated by applicant’s amendments to the claims,
Response to Arguments under 35 USC 101:
Applicant argues (Page 10-12 of the remarks):
However, Applicant respectfully traverses the allegation that the claims recite merely "model or artificial intelligence" at a "high level of generality," or that the explicitly claimed limitations could practically be interpretated as "generic computer functions." More particularly, Applicant submits that the independent claims require specific architecture of a "deep learning" model, wherein such architecture requires the implementation of "at least one process conformance layer" which performs the non-generic computer functions of calculating loss values by processing AI-generated prediction in conjunction with separate process model event logs and particular conformance weight factors configured as part of the at least one process conformance layer of the at least one deep learning model. Applicant respectfully reiterates that such functions could not practically be performed by an off-the-shelf generic computer.
Accordingly, Applicant asserts that the pending claims, which have been affirmatively deemed satisfactory with respect to §§ 102, 103 and 112, should be deemed satisfactory with respect to §101 as well for at least the reasons detailed above.
Notwithstanding the foregoing traversal, Applicant has amended the claims without prejudice and solely in order to expedite prosecution.
Accordingly, in connection with discussions with the Examiner during the above-noted telephonic interview, Applicant respectfully submits that the amended independent claims, by requiring the active step of "generating at least one control signal for controlling at least portions of one or more external systems based at least in part on the one or more enterprise goal-oriented recommendations," further recite additional elements that integrate any alleged judicial exception into a practical application.
Examiner respectfully disagrees:
First, examiner note, with regard to “generating at least one control signal FOR controlling at least portion of one or more external systems”. Here, the system only generate a control signal for controlling, it is not positively recited that the system control the external system. Examiner recommend the applicant to clarify the limitation and point out where the examiner can find the support in the specification “control signal for controlling … based at least in part on the one or more enterprise goal-oriented recommendation”
Second, The Applicant's Specification titled " GENERATING ORGANIZATIONAL GOAL-ORIENTED AND PROCESS-CONFORMANT RECOMMENDATION MODELS USING ARTIFICIAL INTELLIGENCE TECHNIQUES" emphasizes the business need for data analysis, "In summary, the present disclosure relates to methods and systems for predicting enterprise activities, generate a recommendation based on different data " (see specification)
As the bolded claim limitations above demonstrate, independent claims 1, 12, and 20 are recites the abstract idea of predicting enterprise activities, generate a recommendation based on different data which is part of commercial or legal interactions (including agreements in the form of contracts, legal obligations; advertising, marketing or sales activities or behaviors; business relations) and managing personal behaviors or relationships or interactions between people (including social activities, teaching, and following rules or instructions). In example aspects, predicting enterprise activities, generate a recommendation based on different data. which is considered certain methods of organizing human activity because the bolded claim limitations pertain to (i) commercial or legal interactions and (II) managing personal behavior or relationships or interactions between people . See MPEP §2106.04(a)(2)(II).
In prong two of step 2A, an evaluation is made whether a claim recites any additional element, or combination of additional element, that integrate the exception into a practical application of that exception. An “additional element” is an element that is recited in the claim in addition to (beyond) the judicial exception (i.e., an element/limitation that sets forth an abstract idea is not an additional element). The phrase “integration into a practical application” is defined as requiring an additional element or a combination of additional elements in the claim to apply, rely on, or use exception, such that it is more than a drafting effort designed to monopolize the exception.
The claims recites the additional limitation a system, model, artificial intelligence techniques, deep learning model, process model, a computer program “non-transitory”, and a computing device are recited in a high level of generality and recited as performing generic computer functions routinely used in computer applications. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp. 134 S. Ct, at 2360,110 USPQ2d at 1984 (see MPEP 2106.05(f). All of these additional elements are not significantly more because these, again, are merely the software and/or hardware components used to implement the abstract idea on a general purpose computer.
The additional elements of a “model or artificial intelligence”. This language merely requires execution of an algorithm that can be performed by a generic computer component and provides no detail regarding the operation of that algorithm. As such, the claim requirement amounts to mere instructions to implement the abstract idea on a computer, and, therefore, is not sufficient to make the claim patent eligible. See Alice, 573 U.S. at 226 (determining that the claim limitations “data processing system,” “communications controller,” and “data storage unit” were generic computer components that amounted to mere instructions to implement the abstract idea on a computer); October 2019 Guidance Update at 11–12 (recitation of generic computer limitations for implementing the abstract idea “would not be sufficient to demonstrate integration of a judicial exception into a practical application”). Such a generic recitation of “model or artificial intelligence” is insufficient to show a practical application of the recited abstract idea.
The use of generic computer component does not impose any meaningful limit on the computer implementation of the abstract idea. 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 a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (step 2A-prong two: NO).
Further, with regard to mining (i.e., searching over a network), receiving, processing, storing data, and parsing (i.e. extract, transform data), the courts have recognized the following computer functions as well-understood, routing, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (i.e. “receiving, processing, transmitting, storing data”, etc.) are well-understood, routine, etc. (MPEP 2106.05(d))
The Alice framework, step 2B (Part 2 of Mayo) determine if the claim is sufficient to ensure that the claim amounts to “significantly more” than the abstract idea itself. These additional elements recite conventional computer components and conventional functions of:
Claims 1, 12, and 20 does not include my limitations amounting to significantly more than the abstract idea, along. Claims 1, 12, and 20 includes various elements that are not directed to the abstract idea. These elements include “a system, model, artificial intelligence techniques, deep learning model, process model, a computer program “non-transitory”, and a computing device”
Examiner asserts that a system, model, artificial intelligence techniques, deep learning model, process model, a computer program “non-transitory”, and a computing device are a generic computing element performing generic computing functions. (See MPEP 2106.05(f))
Therefore, the claims at issue do not require any nonconventional computer, network, or display components, or even a “non-conventional and non-generic arrangement of know, conventional pieces,” but merely call for performance of the claimed on a set of generic computer components” and display devices.
In addition, figure 1, of the specifications detail any combination of a generic computer system program to perform the method. Generically recited computer elements do not add a meaningful limitation to the abstract idea because the Alice decision noted that generic structures that merely apply abstract ideas are not significantly more than the abstract ideas.
The computing elements with a computing device is recited at high level of generality (e.g. a generic device performing a generic computer function of processing data). Thus, this step is no more than mere instructions to apply the exception on a generic computer. In addition, using a processor to process data has been well-understood routing, conventional activity in the industry for many years.
Generic computer features, such as system or storage, do not amount to significantly more than the abstract idea. These limitations merely describe implementation for the invention using elements of a general-purpose system, which is not sufficient to amount to significantly more. See, e.g., Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976; Versata Dev. Group, Inc. v. SAP Am. Inc., 793 F .3d 1306, 1334, 115 USPQ2d 1681, 1791 (Federal Circuit 2015).
Claim Rejections - 35 USC § 112
Claims 1-4, 7-8, 10-15, 17-18, and 20-25 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claims 1, 12, and 20 recites the limitation “generating at least one control signal for controlling at least portions of one or more external systems based at least in part on the one or more enterprise goal-oriented recommendations”. The specification in paragraph [0027], teaches that “performing one or more automated actions includes automatically implementing at least a portion of the one or more enterprise goal-oriented recommendations in connection with at least one enterprise system and/or automatically outputting at least a portion of the one or more enterprise goal-oriented recommendations to at least one user associated with the enterprise”. Also, in paragraph [0029], “express models using mathematical equations, but that form of expression does not confine the models disclosed herein to abstract concepts; instead, each model herein has a practical application in a computer in the form of stored executable instructions and data that implement the model using the computer”. The specification when examined as a whole does not disclose that the system generating at least one control signal for controlling at least portions of one or more external systems based at least in part on the one or more enterprise goal-oriented recommendations.
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, 7-8, 10-15, 17-18, 20-25 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter, specifically an abstract idea without a practical application or significantly more than the abstract idea.
Under the 35 U.S.C. §101 subject matter eligibility two-part analysis, Step 1 addresses whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. See MPEP §2106.03. If the claim does fall within one of the statutory categories, it must then be determined in Step 2A [prong 1] whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea). See MPEP §2106.04. If the claim is directed toward a judicial exception, it must then be determined in Step 2A [prong 2] whether the judicial exception is integrated into a practical application. See MPEP §2106.04(d). Finally, if the judicial exception is not integrated into a practical application, it must additionally be determined in Step 2B whether the claim recites "significantly more" than the abstract idea. See MPEP §2106.05.
Examiner note: The Office's 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG) is currently found in the Ninth Edition, Revision 10.2019 (revised June 2020) of the Manual of Patent Examination Procedure (MPEP), specifically incorporated in MPEP §2106.03 through MPEP §2106.07(c).
Regarding Step 1
Claims 1-4, 7-8, and 10-11 are directed to a method (process), claims 12-15, 17-18 are directed to a method (process), and claims 20-25 are directed to a computer program “non-transitory” (Machine). Thus, all claims fall within one of the four statutory categories as required by Step 1.
Regarding Step 2A [prong 1]
Claims 1-4, 7-8, 10-15, 17-18, and 20-25 are directed toward the judicial exception of an abstract idea.
Independent claims 12 and 20 recites essentially the same abstract features as claim 1, thus are abstract for the same reasons as claim 1.
Regarding independent claim 1, the bolded limitations emphasized below correspond to the abstract ideas of the claimed invention:
Claim 1. A computer-implemented method comprising:
obtaining at least one process model associated with a given enterprise;
predicting multiple enterprise-related activities by processing data associated with the at least one process model using one or more artificial intelligence techniques, wherein the one or more artificial intelligence techniques comprises at least one deep learning model, trained using event log data derived from the at least one process model, and comprising at least one process conformance layer;
determining at least a portion of the multiple predicted enterprise-related activities that conform with the at least one process model by calculating a loss value for each of the multiple predicted enterprise-related activities, wherein calculating the loss value comprises processing, using the at least one process conformance layer of the at least one deep learning model, data associated with each of the multiple predicted enterprise-related activities in conjunction with one or more event logs from the at least one process model and one or more conformance weight factors configured as part of the at least one process conformance layer of the at least one deep learning model;
generating one or more enterprise goal-oriented recommendations comprising (i) a sequence of recommended processes which further one or more enterprise goals and (ii) a recommended respective sequence of multiple actions to be carried out for each of at least a portion of the sequence of recommended processes, by processing the at least a portion of the multiple predicted enterprise-related activities that conform with the at least one process model using the one or more artificial intelligence techniques; and
performing one or more automated actions based at least in part on the one or more enterprise goal-oriented recommendations, wherein performing one or more automated actions comprises automatically training, using at least a portion of the one or more enterprise goal-oriented recommendations, at least one a portion of the one or more artificial intelligence techniques; and
generating at least one control signal for controlling at least portions of one or more external systems based at least in part on the one or more enterprise goal-oriented recommendations;
wherein the method is carried out by at least one computing device.
The Applicant's Specification titled " GENERATING ORGANIZATIONAL GOAL-ORIENTED AND PROCESS-CONFORMANT RECOMMENDATION MODELS USING ARTIFICIAL INTELLIGENCE TECHNIQUES" emphasizes the business need for data analysis, "In summary, the present disclosure relates to methods and systems for predicting enterprise activities, generate a recommendation based on different data " (see specification)
As the bolded claim limitations above demonstrate, independent claims 1, 12, and 20 are recites the abstract idea of predicting enterprise activities, generate a recommendation based on different data which is part of commercial or legal interactions (including agreements in the form of contracts, legal obligations; advertising, marketing or sales activities or behaviors; business relations) and managing personal behaviors or relationships or interactions between people (including social activities, teaching, and following rules or instructions). In example aspects, predicting enterprise activities, generate a recommendation based on different data. which is considered certain methods of organizing human activity because the bolded claim limitations pertain to (i) commercial or legal interactions and (II) managing personal behavior or relationships or interactions between people . See MPEP §2106.04(a)(2)(II).
Dependent claims 2-4, 7-8, 10-11, 13-15, 17-18, and 21-25 further reiterate the same abstract ideas with further embellishments (the bolded limitations), such as
claim 2 (Similarly Claims 13, and 21) wherein the at least one deep learning model is further trained based at least in part on one or more input enterprise-activity related sequences.
claim 3 (Similarly Claims 14, and 22) wherein the one or more artificial intelligence techniques comprise at least one reinforcement learning model trained based at least in part on data pertaining to the one or more enterprise goals and one or more key performance indicator predictions.
claim 4 (Similarly Claim 15) generating the one or more key performance indicator predictions by processing data associated with the at least one process model using the one or more artificial intelligence techniques.
claim 5 Cancelled
claim 6 (Similarly Claim 16) Cancelled
claim 7 (Similarly Claims 17, and 25) wherein obtaining at least one process model comprises implementing one or more machine learning-based process discovery tools.
claim 8 (Similarly Claims 18, and 23) wherein performing one or more automated actions comprises automatically implementing at least a portion of the one or more enterprise goal-oriented recommendations in connection with at least one enterprise system.
claim 9 (Similarly Claim 19) Cancelled
claim 10 (Similarly Claim 24) wherein performing one or more automated actions comprises automatically outputting at least a portion of the one or more enterprise goal-oriented recommendations to at least one user associated with the given enterprise.
claim 11 wherein software implementing the method is provided as a service in a cloud environment.
which are nonetheless directed towards fundamentally the same abstract ideas as indicated for independent claims 1, 12 and 20.
Regarding Step 2A [prong 2]
Claims 1-4, 7-8, 10-15, 17-18, and 20-25 fail to integrate the abstract idea into a practical application. Independent claims 1, 12 and 20 include the following additional elements which do not amount to a practical application:
Claim 1.
model using a set of one or more artificial intelligence techniques;
model, deep learning model, process model
model using the of one or more artificial intelligence techniques; and
one computing device.
Claim 12. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computing device to cause the computing device model using the one or more artificial intelligence techniques;
model deep learning model, process model
model using the one or more artificial intelligence techniques; and
one computing device.
Claim 20. A system model using the one or more artificial intelligence techniques;
model deep learning model, process model
model using the one or more artificial intelligence techniques; and
one computing device.
The bolded limitations recited above in independent claims 1, 12 and 20 pertain to additional elements which merely provide an abstract-idea-based-solution implemented with computer hardware and software components, including the additional elements of a system, model, artificial intelligence techniques, deep learning model, process model, a computer program “non-transitory”, and a computing device. which fail to integrate the abstract idea into a practical application because there are (1) no actual improvements to the functioning of a computer, (2) nor to any other technology or technical field, (3) nor do the claims apply the judicial exception with, or by use of, a particular machine, (4) nor do the claims provide a transformation or reduction of a particular article to a different state or thing, (5) nor provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment, in view of MPEP §2106.04(d)(1) and §2106.05 (a-c & e-h), (6) nor do the claims apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, in view of MPEP §2106.04(d)(2). The Specification provides a high level of generality regarding the additional elements claimed without sufficient detail or specific implementation structure so as to limit the abstract idea, for instance, (fig. 1). Nothing in the Specification describes the specific operations recited in claims 1, 8 and 15 as particularly invoking any inventive programming, or requiring any specialized computer hardware or other inventive computer components, i.e., a particular machine, or that the claimed invention is somehow implemented using any specialized element other than all-purpose computer components to perform recited computer functions. The claimed invention is merely directed to utilizing computer technology as a tool for solving a business problem of data analytics. Nowhere in the Specification does the Applicant emphasize additional hardware and/or software elements which provide an actual improvement in computer functionality, or to a technology or technical field, other than using these elements as a computational tool to automate and perform the abstract idea. See MPEP §2106.05(a & e).
The additional elements of a “model and artificial intelligence techniques”. This language merely requires execution of an algorithm that can be performed by a generic computer component and provides no detail regarding the operation of that algorithm. As such, the claim requirement amounts to mere instructions to implement the abstract idea on a computer, and, therefore, is not sufficient to make the claim patent eligible. See Alice, 573 U.S. at 226 (determining that the claim limitations “data processing system,” “communications controller,” and “data storage unit” were generic computer components that amounted to mere instructions to implement the abstract idea on a computer); October 2019 Guidance Update at 11–12 (recitation of generic computer limitations for implementing the abstract idea “would not be sufficient to demonstrate integration of a judicial exception into a practical application”). Such a generic recitation of “model and artificial intelligence techniques” is insufficient to show a practical application of the recited abstract idea.
The relevant question under Step 2A [prong 2] is not whether the claimed invention itself is a practical application, instead, the question is whether the claimed invention includes additional elements beyond the judicial exception that integrate the judicial exception into a practical application by imposing a meaningful limit on the judicial exception. This is not the case with Applicant's claimed invention which merely pertains to steps for predicting enterprise activities, generate a recommendation based on different data. In example aspects, based on different data and the additional computer elements a tool to perform the abstract idea, and merely linking the use of the abstract idea to a particular technological environment. See MPEP §2106.04 and §21062106.05(f-h). Alternatively, the Office has long considered data gathering, analysis and data output to be insignificant extra-solution activity, and these additional elements do not impose any meaningful limits on practicing the abstract idea. See MPEP §2106.04 and §2106.05(g). Thus, the additional elements recited above fail to provide an actual improvement in computer functionality, or to a technology or technical field. See MPEP §2106.04(d)(1) and §2106§2106.05 (a & e).
Instead, the recited additional elements above, merely limit the invention to a technological environment in which the abstract concept identified above is implemented utilizing the computational tools provided by the additional elements to automate and perform the abstract idea, which is insufficient to provide a practical application since the additional elements do no more than generally link the use of the abstract idea to a particular technological environment. See MPEP §2106.04. Automating the recited claimed features as a combination of computer instructions implemented by computer hardware and/or software elements as recited above does not qualify an otherwise unpatentable abstract idea as patent eligible. Alternatively, the Office has long considered data gathering and data processing as well as data output recruitment information on a social network to be insignificant extra-solution activity, and these additional elements used to gather and output recruitment information on a social network are insignificant extra-solution limitations that do not impose any meaningful limits on practicing the abstract idea. See MPEP §2106.05(g). The current invention is idea of predicting enterprise activities, generate a recommendation based on different data. When considered in combination, the claims do not amount to improvements of the functioning of a computer, or to any technology or technical field. Applicant's limitations as recited above do nothing more than supplement the abstract idea using additional hardware/software computer components as a tool to perform the abstract idea and generally link the use of the abstract idea to a technological environment, which is not sufficient to integrate the judicial exception into a practical application since they do not impose any meaningful limits.
Dependent claims 2-4, 7-8, 10-11, 13-15, 17-18, and 21-25 merely incorporate the additional elements recited above, along with further embellishments of the abstract idea of independent claims 1, 12 and 20 for example claims 2-4, 7-8, 11, 13-15, 17-18, “deep learning model, reinforcement learning model, third AI, machine learning, enterprise system, and a cloud environment platform”.
The additional elements of a “deep learning model, reinforcement learning model, AI, machine learning”. This language merely requires execution of an algorithm that can be performed by a generic computer component and provides no detail regarding the operation of that algorithm. As such, the claim requirement amounts to mere instructions to implement the abstract idea on a computer, and, therefore, is not sufficient to make the claim patent eligible. See Alice, 573 U.S. at 226 (determining that the claim limitations “data processing system,” “communications controller,” and “data storage unit” were generic computer components that amounted to mere instructions to implement the abstract idea on a computer); October 2019 Guidance Update at 11–12 (recitation of generic computer limitations for implementing the abstract idea “would not be sufficient to demonstrate integration of a judicial exception into a practical application”). Such a generic recitation of “deep learning model, reinforcement learning model, AI, machine learning” is insufficient to show a practical application of the recited abstract idea.
Also, these features only serve to further limit the abstract idea of independent claims 1, 12 and 20. furthermore, merely using/applying in a computer environment such as merely using the computer as a tool to apply instructions of the abstract idea do nothing more than provide insignificant extra-solution activity since they amount to data gathering, analysis and outputting. Furthermore, they do not pertain to a technological problem being solved in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, and/or the limitations fail to achieve an actual improvement in computer functionality or improvement in specific technology other than using the computer as a tool to perform the abstract idea.
Therefore, the additional elements recited in the claimed invention individually, and in combination fail to integrate the recited judicial exception into any practical application.
Regarding Step 2B
Claims 1-4, 7-8, 10-15, 17-18, and 20-25 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional element(s) as described above with respect to Step 2A Prong 2, the additional element of claims 1, 12 and 20 include a system, model, artificial intelligence techniques, a computer program “non-transitory”, deep learning model, process model and a computing device. Further, claims 2-4, 7-8, 11, 13-15, 17-18, “deep learning model, reinforcement learning model, third AI, machine learning, enterprise system, and a cloud environment platform”. The displaying interface and storing data merely amount to a general purpose computer used to apply the abstract idea(s) (MPEP 2106.05(f)) and/or performs insignificant extra-solution activity, e.g. data retrieval and storage, as described above (MPEP 2106.05(g)) which are further merely well-understood, routine, and conventional activit(ies) as evidenced by MPEP 2106.06(05)(d)(II) (describing conventional activities that include transmitting and receiving data over a network, electronic recordkeeping, storing and retrieving information from memory, electronically scanning or extracting data from a physical document, and a web browser’s back and forward button functionality). Therefore, similarly the combination and arrangement of the above identified additional elements when analyzed under Step 2B also fails to necessitate a conclusion that the claims amount to significantly more than the abstract idea directed to predicting enterprise activities, generate a recommendation based on different data.
Claims 1-4, 7-8, 10-15, 17-18, and 20-25 is accordingly rejected under 35 USC 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea(s)) without significantly more.
Examiner Note: regarding claim 20 a computer program product, the computer program product, the specification discloses in ¶[0040], “a computer readable storage medium, as used herein, is not to be construed as being transitory signals per se”.
Allowable Subject Matter
Regarding the 35 USC 103 rejection, No art rejections has been put forth in the rejection.
Closest prior art to the invention include Singh et al. US 2022/0300881: Value realization analytics systems and related methods of use, Savalle et al. US 2021/0294818: Extraction of prototypical trajectories for automatic classification of network KPI predictions, Bishop et al. US 2019/013867: Managing resource allocation in a stream processing framework, and Ke, Gang, Hong-Le Du, and Yeh-Cheng Chen. "Cross-platform dynamic goods recommendation system based on reinforcement learning and social networks." Applied Soft Computing 104 (2021). None of the prior art of record, taken individually or in combination, teach, inter alia, teaches the claimed invention as detailed in independent claims, “determining at least a portion of the multiple predicted enterprise-related activities that conform with the at least one process model by calculating a loss value for each of the multiple predicted enterprise-related activities, wherein calculating the loss value comprises processing, using the at least one process conformance layer of the at least one deep learning model, data associated with each of the multiple predicted enterprise-related activities in conjunction with one or more event logs from the at least one process model and one or more conformance weight factors configured as part of the at least one process conformance layer of the at least one deep learning model;”. The reason to withdraw the 35 USC 103 rejection of claims 1-4, 7-8, 10-15, 17-18, and 20-25 in the instant application is because the prior art of record fails to teach the overall combination as claimed. Therefore, it would not have been obvious to one of ordinary skill in the art to modify the prior art to meet the combination above without unequivocal hindsight and one of ordinary skill would have no reason to do so. Upon further searching the examiner could not identify any prior art to teach these limitations. The prior art on record, alone or in combination, neither anticipates, reasonably teaches, not renders obvious the Applicant’s claimed invention.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 filed within TWO MONTHS of 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 action.
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/HAMZEH OBAID/Primary Examiner, Art Unit 3624