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 .
This Final office action is in response to the applicant’s communication received on 7/24/2026 (“Amendment”).
Status of Claims
Claims 1, 8, and 14, all being independent claims, have been amended.
Claims 3, 10, and 16 have been canceled.
Claim 22 has been newly added.
Claims 1-2, 4-9, 11-15, and 17-22 are pending.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-2, 4-9, 11-15, and 17-22 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.
Per claim 1, the claim continues to be indefinite. For example, the claim clearly recites five steps as “performance of operation”, i.e., 1) accessing training data sets … 2) training an escalation machine learning … 3) obtaining a feedback on an accuracy … 4) updating a set of training data … 5) updating the trained escalation machine learning model based on the updated set of training data.
The claim, however, further recites at an initial service provider executing in a cloud computing region, wherein (a) a higher-tiered service provider provides cloud-service computing resources in the cloud computing region to the initial service provider and (b) the initial service provider executes a process on a first set of cloud-service computing resources, of the cloud-service computing resources, associated with an operator tenancy the process comprising: providing cloud computing services … receiving an initial service ticket … identifying one or more issue attributes … inputting the one or more issue attributes … responsive to the determination and based on the initial service ticket, generating, in the operator tenancy, an escalated service ticket that identifies the issue … wherein generating the escalated service ticket comprises applying a redaction process, executing within the operator tenancy and using hardware resources of first set of cloud-service computing resources, to the initial service ticket to programmatically identify and exclude the access-restricted set of attributes of the affected entity from the escalated service ticket; transmitting the escalated service ticket … in response to transmitting the escalated service ticket: receiving, in the operator tenancy, from the higher-tiered service provider, information corresponding to the resolution of the issue; processing the initial service ticket … receiving a second initial service ticket … identifying one or more second issue attributes based on the second initial service ticket; inputting the one or more second issue attributes to the escalation machine learning model … and causing resolution of the second issue by the initial service provider.
The claim, however, is indefinite as one of ordinary skill in the art would not be able to clearly ascertain whether the recited process (italicized above) that the initial service provider executes at the initial service provider executing in a cloud computing region is part of the “performance of operations”. As such, one of ordinary skill in the art would not be able to ascertain the metes and boundaries of the claim. An essential purpose of patent examination is to fashion claims that are precise, clear, correct, and unambiguous. Only in this way can uncertainties of claim scope be removed. See In re Zletz,13 USPQ2d 1320 (Fed. Cir. 1989).
Claim 8 is similarly rejected as the claim clearly recites the method to comprise 1) accessing training data set … 2) training an escalation machine learning model … 3) obtaining feedback … 4) updating a set of training data … 5) updating the escalation machine learning model based on the updated set of training data. The claim, however, recites at an initial service provide executing in a cloud computing region … (b) the initial service provider executes a process … the process comprising: providing cloud computing services … receiving an initial service ticket for resolution … identifying one or more issue attributes … inputting the one or more issue attributes … responsive to the determination and based on the initial service ticket, generating, in the operator tenancy, an escalated service ticket that identifies the issue, wherein generating the escalated service ticket comprises applying a redaction process, executing within the operator tenancy and using hardware resources of first set of cloud-service computing resources, to the initial service ticket to programmatically identify and exclude the access-restricted set of attributes of the affected entity from the escalated service ticket; transmitting the escalated service ticket … in response to transmitting the escalated service ticket: receiving, in the operator tenancy, from the higher-tiered service provider, information corresponding to the resolution of the issue; processing the initial service ticket based on the information corresponding to the resolution of the issue; receiving a second initial service ticket for resolution of a second issue identified by the second initial service ticket, from the affected entity, wherein the second initial service ticket comprises a second access-restricted set of attributes of the affected entity, the second access-restricted set of attributes including one or more attributes, and wherein the second issue is associated with the second set of cloud- service computing resources; identifying one or more second issue attributes based on the second initial service ticket; inputting the one or more second issue attributes to the escalation machine learning model to determine that the second issue does not require escalation to the higher- tiered service provider wherein hardware resources of first set of cloud-service computing resources are not used to generate a second escalated service ticket; and causing resolution of the second issue by the initial service provider.
In other words, one of ordinary skill in the art would not be able to ascertain whether the recited “process” of the initial service provider is part of the method.
Similarly, claim 15 is rejected as one of ordinary skill in the art would not be able to ascertain whether the recited “process” of the initial service provider is part of the operations performed by a system comprising one or more hardware processors; one or more non-transitory computer-readable media; and program instructions stored on the one or more non-transitory computer-readable media, thereby rendering the claim to be indefinite.
For the purpose of compact prosecution, this final action will interpret the process to be part of operations in claim 1, part of the method in claim 8, and part of the operations in claim 14.
In further regards to the independent claims, the scope of the claims is unclear. For example, the first five recited steps/operations are related to training of the machine learning model to generate an escalated service ticket based on a set of initial service tickets and retraining of the machine learning model using an updated set of training data based on feedback of accuracy of the machine learning model having been trained with the set of initial service tickets. The steps/operations after the first five steps/operations are directed to steps/operations related to initial service provider processing of an initial service ticket and a second initial service ticket, e.g., receiving the tickets and generation of escalation service ticket based on the attributes identified in the service tickets using the machine learning model.
The claim is indefinite as there are multiple recitations of the initial service ticket as it is unclear which one of the previously recited initial service tickets refers to the initial service ticket. Similarly, the claim recites the escalated service ticket throughout the claim. It is unclear which one of the previously recited escalated service ticket refers to the escalated service ticket.
Dependent claims 2, 4, 5, 7, 9, 11, 12, 15, 17, 18, and 20-22 recite the initial service ticket. The claims are rejected as it is unclear which one of the previously recited initial service tickets refers to the initial service ticket.
Dependent claims 2, 4, 5-7, 9, 11-13, 15, and 17-22 recite the escalated service ticket. The claims are rejected as it is unclear which one of the previously recited escalated service tickets refers to the escalated service ticket.
The dependent claims are rejected as they depend on claim(s) above.
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 1-2, 4-9, 11-15, and 17-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
MPEP 2106 provides step(s) in determining eligibility under 35 U.S.C. § 101. Specifically, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any additional elements in the claim must integrate the judicial exception into a practical application. If not, the inquiry continues to see whether any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself. Examples of abstract ideas include mathematical concepts, mental processes, and certain methods of organizing human activities.
Under Step 1, claims 1-2 and 4-7 are directed to a non-transitory computer-readable storage medium, claims 8-9, 11-13 and 21-22 are directed to a method (i.e., process), while claims 14-15 and 17-20 are directed to a system. Thus, the claimed inventions are directed towards one of the four statutory categories under 35 USC § 101. Nevertheless, the claims also fall within the judicial exception of an abstract idea without significantly more.
Step 2A, 1st prong:
Claim 8 recites: A method, comprising:
1) accessing training data sets, a particular training data set of the training data sets comprising: a first set of initial service tickets; and a first set of escalated service tickets previously generated from the first set of initial service tickets;
2) training an escalation machine learning model based on the training data sets to generate an escalated service ticket;
3) obtaining feedback on an accuracy of the escalation machine learning model;
4) updating a set of training data based on the feedback;
5) updating the escalation machine learning model based on the updated set of training data:
6) at an initial service provider executing in a cloud computing region, wherein (a) a higher-tiered service provider provides cloud-service computing resources in the cloud computing region to the initial service provider and (b) the initial service provider executes a process on a first set of cloud-service computing resources, of the cloud-service computing resources, associated with an operator tenancy the process comprising:
6a) providing cloud computing services to a customer associated with a customer tenancy, owned by the customer, in the cloud computing region, wherein a second set of cloud-service computing resources, of the cloud-service computing resources, associated with the customer tenancy is located within premises owned and operated by the initial service provider;
6b) receiving an initial service ticket for resolution of an issue identified by the initial service ticket, from an affected entity, associated with the customer operating in the customer tenancy, that is affected by the issue, wherein the initial service ticket comprises an access-restricted set of attributes of the affected entity, the access- restricted set of attributes including one or more attributes, and wherein the issue is associated with the second set of cloud-service computing resources;
6c) identifying one or more issue attributes based on the initial service ticket;
6d) inputting the one or more issue attributes to the escalation machine learning model to determine that the issue identified in the initial service ticket requires escalation to the higher-tiered service provider;
6e) responsive to the determination and based on the initial service ticket, generating, in the operator tenancy, an escalated service ticket that identifies the issue, wherein generating the escalated service ticket comprises applying a redaction process, executing within the operator tenancy and using hardware resources of first set of cloud-service computing resources, to the initial service ticket to programmatically identify and exclude the access-restricted set of attributes of the affected entity from the escalated service ticket;
6f) transmitting the escalated service ticket from the operator tenancy to the higher- tiered service provider executing on a third set of cloud-service computing resources associated with a provider tenancy, isolated from the operator tenancy and the customer tenancy, wherein the higher-tiered service provider is not authorized to access: the operator tenancy, the customer tenancy, and the access- restricted set of attributes comprised in the initial service ticket;
6g)in response to transmitting the escalated service ticket: receiving, in the operator tenancy, from the higher-tiered service provider, information corresponding to the resolution of the issue;
6h) processing the initial service ticket based on the information corresponding to the resolution of the issue;
6i) receiving a second initial service ticket for resolution of a second issue identified by the second initial service ticket, from the affected entity, wherein the second initial service ticket comprises a second access-restricted set of attributes of the affected entity, the second access-restricted set of attributes including one or more attributes, and wherein the second issue is associated with the second set of cloud- service computing resources;
6j) identifying one or more second issue attributes based on the second initial service ticket;
6k) inputting the one or more second issue attributes to the escalation machine learning model to determine that the second issue does not require escalation to the higher-tiered service provider wherein hardware resources of first set of cloud-service computing resources are not used to generate a second escalated service ticket; and
6l) causing resolution of the second issue by the initial service provider;
wherein the method is performed by at least one device comprising a hardware processor.
(Bold emphasis added on the additional element(s))
Under the broadest reasonable interpretation, the claim recites a process for resolving issue tickets among the tiered based hierarchy. The claim recites initial service provider 6a) providing service to a customer within premise owned and operated by the initial service provider and 6b)-6l) resolution of two initial tickets from an affected customer entity. In the processing of the first initial service ticket, the initial service provider 6b) receives initial ticket that comprises an access-restricted set of attributes of the affected entity, wherein the initial ticket identifies issue associated with the resources located and owned by the initial service provider; 6c) identifies one or more issue attributes based on the initial ticket; 6d) inputs the one or more issue attributes to the escalation machine learning model to determine that the issue identified in the initial service ticket requires escalation to the higher-tiered service provider; 6e) responsive to the determination and based on the initial service ticket, generating an escalated service ticket that identifies the issue by applying a redaction process to the initial ticket (identify and exclude the access-restricted set of attributes of the affected entity from the escalated service ticket; 6f) transmitting the escalated service ticket from its environment to the higher-tiered service provider; 6g) in response to the transmission, receiving in its environment from the higher-tiered service provider, information corresponding to the resolution of the issue; 6h) processing the initial service ticket based on the information corresponding to the resolution of the issue.
In other words, steps 6b) – 6h) recites handling of customer support ticket when an issue must be sent from initial service provider to a higher-tier provider for help. The recited step(s) utilizes machine learning model in determining that identified issues in the initial ticket (received from the affected entity) requires escalation to the higher-tier provider. After it is determined that the escalation is needed, the claim generates the escalation ticket that identifies the issue but omits the access-restricted customer attributes since the higher-tier provider is not authorized to access the access-restricted customer attributes in the initial ticket. This escalation ticket is sent to the high-tier provider for resolution. Information associated with the resolution to the issue is received, and the initial service ticket is processed based on the information.
In processing of the second initial ticket (steps 6i)-6l)), the steps significantly similar to the processing of the first initial ticket with exception that second escalated service ticket is not generated since the escalation machine learning model determined that the second issue as identified in the second initial ticket does not require escalation to the higher-tiered service provider. In other word, the second initial ticket does not need escalation, hence a resolution is performed by the initial service provider.
Hence, the claim recites an abstract idea, (a certain method of organizing human activities, i.e., tiered based incident resolution process). The recitation of the business arrangement relationship of the initial service provider, customer, and the higher-tiered service provider is analogous to a business arrangement in which company A (higher-tiered) leases a subset of its asset or space to company B (initial service provider) and the company B then leases the part of the subset that has been leased to its customer. As such, the claim further recites a certain method of organizing human activities, i.e., business arrangement.
The claim recitations related to omitting of access-restricted set of attributes of the affected entity further expand on the abstract idea, (a certain method of organizing human activities, i.e., business relationship and/or mitigating risk).
The claim recitations of steps 1-5 in retraining of escalation machine learning model and use of the escalation machine learning model in determining whether to escalate the issue identified in the initial ticket is also an abstract idea, i.e., mental process, as the claim’s recitation of evaluation information, adjusting the input criteria, and modifying of the predictive model describes a fundamental feedback loop (i.e., learning from mistakes) and using the knowledge gained in the predictive model to perform the determination. Machine learning is just a form of automation of the mental process.
The other independent claims, i.e., claims 1 and 14, are significantly similar to claim 8. As such, claims 1 and 14 also recite abstract idea.
Under the Step 2A (prong 2), this judicial exception is not integrated into a practical application. Specifically, the additional elements in the claim(s), i.e., at least one device including a hardware processor and a non-transitory computer readable media, cloud computing to describe resource(s), region(s), tenancy(s), hardware resources, programmatically, one or more processors, programs, machine learning, etc., amount to no more than mere instructions to implement the abstract idea and/or merely uses a computer as a tool to perform an abstract idea and/or generally linking the use of the judicial exception to a particular technological environment or field of user, i.e., cloud computing environment.
Under Step 2B, examiners should evaluate additional elements individually and in combination to determine whether they provide an inventive concept (i.e. whether the additional elements amount to significantly more than the exception itself). Here, the claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Specifically, the claim(s) as a whole, taken individually and in combination, do not provide an inventive concept. As explained above with respect to the integration of the abstract idea into a practical application, the additional elements used to perform the claimed judicial exception amount to no more than mere instructions to implement the abstract idea and/or merely uses a computer as a tool to perform an abstract idea and/or . Mere instructions to implement the abstract idea on a computer, or merely using the computer as a tool to perform an abstract idea to apply the exception using a generic computer component cannot provide an inventive concept. Looking at the limitations as a combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of the elements improves the functioning of the recited system or the system’s component(s) that is responsible for performing the step(s).
Dependent claims 2, 9, and 15 further expand on the concept of anonymizing the escalated ticket and protecting of the access-restricted set of attributes. As such, the claims further expand on certain methods of organizing human activity (i.e., business relationship/risk mitigation). The claims do not recite further additional elements other than those that have been identified above in the independent claims.
Dependent claims 4, 11, and 17 further expand on the use of intermediate service ticket in generating of the escalated service ticket, i.e., business flow, in creation of the escalated service ticket. As such, the claims further expand on certain methods of organizing human activity (i.e., business relationship/risk mitigation). The claims do not recite further additional elements other than those that have been identified above in the independent claims.
Dependent claims 5, 12, and 18 further expand on the abstract idea of mathematical concept, i.e., use of feature vector, in machine learning. The claims do not recite further additional elements other than those that have been identified above in the independent claims.
Dependent claims 6, 13, and 19 recitation that describe what is not permitted by the affected entity expand on the abstract idea, i.e., certain methods of organizing human activity (i.e., business relationship/risk mitigation). The claims do not recite further additional elements other than those that have been identified above in the independent claims.
Dependent claims 7, 20, and 21 recitation of first format and second format for the initial service ticket and the escalated service ticket respectively wherein the second format is in format associated with the higher tiered service provider further expand on the abstract idea, i.e., certain methods of organizing human activity (i.e., business relationship/risk mitigation). The additional element of second ticket management system amount to no more than mere instructions to implement the abstract idea and/or merely uses a computer as a tool to perform an abstract idea. The additional element(s), alone or in combination, do not improve upon the additional element(s) performing the abstract idea or to any technology. The claim does not include an inventive concept.
Dependent claim 22 recites what the tickets comprise, particularly that the initial service ticket comprises a first reference to the escalated service ticket and the escalated service ticket comprises a second reference to the initial service ticket. As such, the claim further expands on abstract idea of including reference information on the tickets for tracking purposes which represents certain methods of organizing human activity, i.e., managing of interaction between entities. The claims do not recite further additional elements other than those that have been identified above in the independent claims.
Response to the Argument(s)/Amendment(s)
112
The claims remain rejected under 112(b) for the reasons outlined above.
101
The applicant asserts that claim 1, as amended, recites a specific technical solution to the problem (i.e., when a PLC customer experience an issue that the initial service provider cannot resolve without escalating to the higher-tiered, the initial service provider needs to transmit information about the issuer, across a tenancy isolation boundary, to a party that is architecturally barred from accessing the tenancy where the issue occurred and the tenancy where the issue occurred and the customer data in the tenancy), the technical solution including automated software processes for 1) training a machine learning model to determine if a service ticket issue needs to be escalated and 2) a redaction process. See pages 13-14 of the Amendment.
In response, the examiner submits that handling of customer support ticket, i.e., receiving of initial ticket, determining whether the initial ticket should be escalated to a higher-tiered entity and generating an escalated ticket while protecting sensitive information that the higher-tiered entity should not have access to, sending the escalated ticket to the higher-tiered entity, receiving instruction associated with a resolution of the issue, and processing the instruction, is certain methods of organizing human activity, i.e., tiered based incident resolution process/business relationship/risk mitigation.
The amendment addition to include the training of a machine learning model to determine if a service ticket issue needs to be escalated, with exception to machine learning, is also abstract idea as the feedback loop is a mental process. Machine learning is just a form of automation of the mental process.
In other words, the additional elements recited in the claims are mere instructions to implement the judicial exception and/or merely uses a computer to perform the judicial exception and/or generally linking the use of the judicial exception to a particular technological environment or field of user, i.e., cloud computing environment.
The applicant asserts on pages 14-15 that the claims are not directed to an abstract idea. In response, the analysis was based on whether the claim recites abstract idea. The description of “Enity A that does not have access to the entity B tenancy or to the customer C tenancies. Likewise, entity B and customer C do not have access to the entity A tenancy.” merely describes the business arrangement/environment to which the abstract idea as identified above is applied.
The applicant asserts that training a machine learning model or neural network is explicitly cited at MPEP 2106.04(a)(1)(vii) as an example of a claim that is not directed to an abstract idea (see page 15 of the Amendment). In response, the applicant is reminded that the example was directed to image processing, i.e., collecting a set of digital facial images, applying one or more transformations to the digital images, creating a first training set including the modified set of digital facial images, training the neural network in a first stage using the first training set, creating a second training set including digital non-facial images that are incorrectly detected as facial images in the first stage of training, and training the neural network in a second stage using the second training set. The example set forth does not cover all training of the neural network as not to recite abstract idea as the example limits to the particulars of the claim limitations in the example that are deemed to be highly computational. In other words, the human mind cannot process or manipulate raw digital image arrays as recited in the example claim. Instant claim, however, does not recite image processing nor process that the human mind cannot process rather recites fundamental feedback loop that can be performed in human mind with pen and paper.
The applicant asserts that the claim integrates judicial exception into a practical application as 1) the specification describes technical improvement, 2) the improvement are reflected in the claim amendment, and 3) the additional element are not merely a particular technological environment. In response, the examiner respectfully disagrees. The escalation process as recited in the claim is clearly a business process not a technical improvement. The additional elements recited in the claims are merely instructions to carry out the judicial exception and/or merely uses a computer to perform the judicial exception and/or “apply it” and/or generally linking the use of the judicial exception to a particular technological environment or field of user, i.e., cloud computing environment.
The applicant asserts that the amended claim recites significantly more than any abstract idea as the claim recites specific software processes performing specific technical operations (automated escalation determination and programmatic access-restricted attribute and exclusion) (see page 19 of the Amendment). The examiner submits that the software is merely an instruction to perform the abstract idea, i.e., escalation determination, and identifying and exclusion of sensitive information. There simply is no improvement on the software itself.
The applicant further asserts that the claim as a whole produces a result that the alleged abstract idea alone does not and cannot achieve. In response, the rejection was not based on the abstract idea alone.
The applicant asserts that claim 22 addresses the technical problem presented by providing a technical routing mechanism. The examiner respectfully disagrees in that the claim further expands on the abstract idea of including reference information on the tickets for tracking purposes which represent certain methods of organizing human activity, i.e., managing of interaction between entities.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US Patent Publication No. 20180199217 discloses generating of an issue ticket in order to escalate a case to another level of support and anonymization of sensitive information;
US Patent Publication No. 20190260804 and 20130282725 disclose anonymizing or removing any private, sensitive information from incident/support ticket;
US Patent Publication No. 20210092029 discloses techniques for managing support computing services including analysis of service ticket using machine learning (i.e., vectors) techniques and escalation of the service ticket based on the analysis. The background also discloses multiple support tiers in a support management system.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEVEN S KIM whose telephone number is (571)270-5287. The examiner can normally be reached Monday -Friday: 7:00 - 3:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Patrick McAtee can be reached on 571-272-7575. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/STEVEN S KIM/Primary Examiner, Art Unit 3698
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