DETAILED ACTION
Acknowledgement
This final office action is in response to the request for continued examiner (RCE) filed on 01/09/2026.
Status of Claims
Claims 33-34 and 42 have been canceled.
Claims 1, 3-4, 21-23, 28-30, 32, and 41 have been amended.
Claims 43-45 have been added.
Claims 1, 3-4, 21-25, 28-32, 35, 39-41, and 43-45 are now pending.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01/09/2026 has been entered.
Response to Arguments
The 35 U.S.C. 112(a) rejection of claims 1, 21, and 28 remains. The Applicant did not address the issues in the submitted arguments or the amended claims.
The 35 U.S.C. 112(b) rejection of claim 33 is withdrawn in light of amendments.
Applicant's arguments filed on 01/09/2026 regarding the 35 U.S.C. 101 rejection of the claims have been fully considered. The Applicant argues that the claims, as amended, are directed to an improvement in a technology field. Further, the claims do not recite or reference certain methods of organizing human activity. The claim elements of claim 1 reflect multiple improvement in the technical fields such as (c) creation by a microprocessor of time-of-receipt based time slices in a computer database and (d) sorting newly-received data items into the time slices based on times in which the data items are received at a staging platform associated with the processor. Further, (e) the time-of-receipt based organization of the received data items enables efficient storage by the microprocessor into the computer database and (f) enables subsequently efficient retrievals by the microprocessor from the computer database, while (g) the compaction functionality optimizes storage resources at the computer database by virtue of the combining of older time segments into larger blocks.
The Examiner respectfully disagrees. The Examiner maintains previous arguments that the claims are directed to the abstract groupings of both Mental Processes and Certain Methods of Organizing Human Activity because the claims describe a process of receiving and processing work related data to prioritize and allocate/assign tickets (i.e. tasks), rewards, and/or penalties to a support device of a service provider (i.e. human), evaluating the performance of the tickets (i.e. tasks), and providing feedback which reflects an act of managing personal behavior. Certain Methods of Organizing Human Activity encompasses managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions. As per MPEP 2106.04(a), a claim recites a judicial exception when the judicial exception is “set forth” or “described” in the claim.
The Examiner also maintains previous arguments that the additional elements recited in the claims and highlighted in Steps 2A(2) and 2B do not integrate the abstract idea into a practical application nor provide significantly more. The Applicant’s argued improvements (c)-(g) above are not recited in the claims nor recited in the Applicant’s specification. Therefore, the claims and the Applicant’s specification do not support an improvement in technology. Utilizing machine learning technology to perform an abstract process of predicting that an objective is in danger of falling below a threshold and/or prioritizing requests is not an improvement in technology. Applying an abstract idea on a computer and/or generally linking the use of the abstract idea to a particular technological environment does not integrate a judicial exception into a practical application or provide an inventive concept (see MPEP 2106.05(f) and (h)). Therefore, the 35 U.S.C. 101 rejection is maintained.
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 .
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1, 3-4, 21-25, 28-32, 35, 39-41, and 43-45 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 claims contain 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1, 21, and 28 include the following limitations that are not supported by the Applicant’s specification.
"a set of inputs describing...(iii) a support program module associated with a support device…",
"the processing component utilizing an electronic machine-learning component (ELMC)...”;
“leveraging the EMLC by the processing component of the prioritization engine...”;
“predicting, by the processing component of the prioritization engine leveraging the electronic machine-learning component…that the objective is no longer in danger of falling below the threshold;” and
“…responsive to predicting by the processing component of the prioritization engine that the objective is no longer in danger of falling below the threshold:..."
The Applicant’s specification does recite that the set of inputs describe a support program module associated with a support device nor does the specification recite that the processing component uses/leverages the electronic machine-learning component or predicts that the objective is no longer in danger of falling below the threshold. This conclusion is based the description of input data in paragraphs [0041]-[0044] and Fig. 4 and the function of the processing component described in paragraphs [0045]-[0048]. Therefore, claims 1, 21, and 28 contain new matter and are rejected under 35 U.S.C. 112(a). Dependent claims 3-4, 22-25, 29-32, 35, 39-41 and 43-45 are also rejected under 35 U.S.C. 112(a).
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, 3-4, 21-25, 28-32, 35, 39-41, and 43-45 are rejected under 35 U.S.C. 101 because the claimed invention, “Service Request Prioritization”, is directed to an abstract idea, specifically Mental Processes and Certain Methods of Organizing Human Activity, without significantly more. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements individually or in combination provide mere instructions to implement the abstract idea on a computer.
Step 1: Claims 1, 3-4, 21-25, 28-32, 35, 39-41, and 43-45 are directed to a statutory category, namely a process (claims 1, 3-4, and 39-41), a manufacture (claims 21-25, 35, and 43-45), and a machine (claims 28-32).
Step 2A (1): Claims 1, 3-4, 21-25, 28-32, 35, 39-41, and 44-45 are directed to an abstract idea of Mental Processes and Certain Methods of Organizing Human Activity, based on the following claim limitations:
Mental Processes:
“accessing,…, a set of inputs describing: (i) a ticket originating with a client organization and relating to a solution request associated with the client organization, (ii) the client organization, (iii) …resolution of the ticket, and (iv) ticket processing related details;
analyzing…the set up inputs…;
applying a first allocation scheme to a set of tickets…, wherein applying the first allocation scheme orders the set of tickets… according to the first allocation scheme and comprises utilizing … (i) the set of inputs and (b) a set of prioritization criteria;
…generates…a prediction that an objective defined by a performance guideline…is in danger of falling below a threshold;
applying a second allocation scheme to the set of tickets… responsive to predicting that the objective is in danger of falling below the threshold, wherein applying the second allocation scheme orders the set of tickets…according to the second allocation scheme and comprises adjusting the first set of scoring elements to generate a second set of scoring elements for the set of tickets and a second set of priorities for the set of tickets;
utilizing at least one of the second set of scoring elements and the second set of priorities in a feedback loop…; (claims 1, 21, and 28)
dynamically adjusting, on the fly…, values of a set of different weights that are assigned to the ticket based on performance feedback from the feedback loop for the set of tickets, and generating an aggregate score based on the performance feedback, wherein the aggregate score (a) is based on a score reward allocated for each ticket of the set of tickets and a score penalty allocated for each ticket of the set of tickets and (b) corresponds to an adherence to a priority …for the set of tickets. (claim 3)
wherein predicting that the objective is in danger of falling below the threshold is based on one or both of the first set of priorities and the first set of scoring elements, wherein the second set of priorities differs from a third set of priorities indicated by the third allocation scheme, and further comprising dynamically adjusting ticket processing details based on the client organization input (claims 4, 24, and 31)
dynamically adjusting on the fly…, values of a set of different weights that are assigned to the ticket based on performance feedback from the feedback loop for the set of tickets (claims 22 and 29)
generating an aggregate score based on the performance feedback, wherein the aggregate score is based on a score reward allocated for each ticket of the set of tickets and a score penalty allocated for each ticket of the set of tickets.(claims 23, 30, and 32)
wherein predicting that the objective is in danger of falling below the threshold is based on one or both of the first set of priorities and the first set of scoring elements. (claims 24 and 31)
generating an aggregate score that corresponds to an adherence to a priority at the support device for the set of tickets (claim 25)
generating an aggregate score based on a score reward allocated for each ticket of the set of tickets and a score penalty allocated for each ticket of the set of tickets, and wherein the aggregate score corresponds to an adherence to the a priority at the support device for the set of tickets (claim 32)
wherein one or more operations selected from a group comprising predicting that the objective is in danger of falling below a threshold and predicting that the objective is no longer in danger of falling below the threshold are performed… (claim 35)
wherein the second set of priorities is determined based on content other than the first set of scoring elements (claim 39)
wherein the prioritizing criteria is determined based on content other than the scoring criteria (claim 40)
wherein the ticket identifies an issue and identifies a request by the client organization for resolution of the issue (claim 41)
wherein predicting that the objective is in danger of falling below a threshold and predicting that the objective is no longer in danger of falling below the threshold are performed…(claim 44);
wherein the operations further comprise dynamically adjusting, on the fly …, the allocation logic based on performance feedback from the feedback loop. (claim 45)
Certain Methods of Organizing Human Activity:
allocating…the ticket …wherein allocating the ticket comprises: determining a first set of priorities relating to prioritizing criteria and a first set of scoring elements relating to scoring criteria differing from the prioritizing criteria, wherein a scoring element of the first set of scoring elements includes an item configured to: convey a first indication to increase a performance score value for the ticket; and/or convey a second indication to decrease the performance score value for the ticket; (claims 1, 21, and 28)
applying a third allocation scheme to the set of tickets…responsive to predicting,…that the objective is no longer in danger of falling below the threshold, wherein applying the third allocation scheme comprises: automatically and dynamically initiating, on the fly…re-ordering of the set of tickets…according to the third allocation scheme;
transmitting… ticket reallocation information…the ticket reallocation information indicating a re-prioritized set of tickets ordered in accordance with the third allocation scheme (claims 1, 21, and 28)
These claims describe a process of receiving and processing work related data to prioritize, score, and assign tickets (i.e. tasks) and evaluate performance of associates. Dependent claims 3-4, 22-25, 29-32, 35, 39-41, and 44-45 further describe the ticket details, ticket scoring, and the evaluation of worker performance. These claims could encompass a human person such as a supervisor/manager mentally with pen and paper receiving and processing work related input data (e.g. adjusting, determine, displaying details and performance) to determine priority, scoring, and assignment of tickets (i.e. tasks) to support staff. Assigning tickets (i.e. tasks), rewards, and/or penalties to support staff is considered acts of organizing human activities as the tickets provide instructions for support staff to follow and rewards/penalties are considered feedback given to support staff to reinforce and/or alter their behavior. Therefore, these limitations, under the broadest reasonable interpretation, fall within the abstract groupings of Mental Processes which include concepts performed in the human mind such as observations, evaluations, judgments, and opinions and Certain Methods of Organizing Human Activity which encompasses managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions. Mental Processes include claims directed to collecting information, analyzing it, and displaying certain results of the collection and analysis even if they are claimed as being performed on a computer. Certain Methods of Organizing Human Activity can encompass the activity of a single person (e.g. a person following a set of instructions), activity that involve multiple people (e.g. a commercial interaction), and certain activity between a person and a computer (e.g. a method of anonymous loan shopping). Therefore, claims 1, 3-4, 21-25, 28-32, 35, 39-41, and 44-45 are directed to an abstract idea and are not patent eligible.
Step 2A (2): This judicial exception is not integrated into a practical application. In particular, claims 1, 21, 28, 35, and 43 recite additional elements of “A computer-implemented method performed by one or more hardware processors (OOMHPs); an input component of a prioritization engine associated with the OOMHPs; a support program module associated with a support device; a processing component of the prioritization engine; wherein (A) the prioritization engine is communicatively coupled to one or more medical-information electronic data stores, of a plurality of medical-information electronic data stores, associated with the set of inputs, (B) the prioritization engine comprises the input component that accesses the set of inputs, the processing component utilizing an electronic machine-learning component (EMLC), and an output component utilizing an electronic interface associated with one or more support devices, and (C) the OOMHPs are associated with a plurality of program execution devices interconnected in a geographically dispersed configuration according to locations of the plurality of medical-information electronic data stores; allocating, via the OOMHPs; storing the ticket,…,at a queue of the support device; leveraging the EMLC by the processing component of the prioritization engine wherein leveraging of the EMLC (a) is initiated via the OOMHPs, and (b) generates via the EMLC..; stored at an electronic memory associated with the prioritization engine; transmitting, via the OOMHPs and the output component of the prioritization engine… to the electronic interface associated with the support device (claims 1, 21, and 28); one or more non-transitory media having computer-readable instructions that, when executed by one or more hardware processors (OOMHPs), cause the OOMHPs to perform a plurality of operations…; (claim 21), a system having one or more hardware processors (OOMHPs) configured to perform a plurality of operations…: (claim 28); …performed by applying at least one machine-learning electronic model that has been configured, via the one or more hardware processors, to perform the one or more operations (claim 35); and wherein a subset of the operations is performed by the plurality of program execution devices interconnected in the geographically dispersed configuration according to the locations of the plurality of medical- information electronic data stores (claim 43).”. These additional elements do not integrate the abstract idea into a practical application because the claims do not recite (a) an improvement to another technology or technical field and (b) an improvement to the functioning of the computer itself and (c) implementing the abstract idea with or by use of a particular machine, (d) effecting a particular transformation or reduction of an article, or (e) applying the judicial exception in some other meaningful way beyond generally linking the use of an abstract idea to a particular technological environment. These additional elements evaluated individually and in combination are viewed as computing and display devices that are used to perform the abstract idea of receiving and processing work related data to prioritize, score, and assign tickets and evaluate performance of support staff. Limitations that recite mere instructions to implement an abstract idea on a computer or merely uses a computer as a tool to perform an abstract idea are not indicative of integration into a practical application (see MPEP 2106.05(f)). Also, limitations that amount to merely indicating a field of use or technological environment (e.g. machine learning) in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application (see MPEP 2106.05(h)). Therefore, claims 1, 3-4, 21-25, 28-32, 35, 39-41, and 43-45 do not include individual or a combination of additional elements that integrate the judicial exception into a practical application and thus are not patent eligible.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Claims 1, 21, 28, 35, and 43 recite additional elements as stated above. These additional elements evaluated individually and in combination are viewed as mere instructions to apply or implement the abstract idea on a computer. The use of machine learning and trained models/algorithms are considered instructions to apply or implement a model on a computer. Applying an abstract idea on a computer and/or generally linking the use of the abstract idea to a particular technological environment does not integrate a judicial exception into a practical application or provide an inventive concept (see MPEP 2106.05(f) and (h)). Therefore, claims 1, 3-4, 21-25, 28-32, 35, 39-41, and 43-45 do not include individual or a combination of additional elements that are sufficient to amount to significantly more than the judicial exception and thus are not patent eligible.
Conclusion
The closest prior art(s) to the claimed invention include Bikumala et al. (US 2021/0240774 A1) “System and Method for Prioritization of Support Requests”, Erhart et al. (US 2014/0321633 A1) “Prioritization and Time Allocation by Customer Service Agents”, Grasso et al. (US 2013/0142322 A1) “System and Method for Enhancing Call Center Performance”, and Mujumdar et al. (US 11,741,405 B2) “Ticket-Agent Matching and Agent Skillset Development”. However, none of the prior art(s) alone or in combination teach the claimed invention as detailed in independent claims 1, 21, and 28.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure include FOR: Wozniak, M. (WO-2022261661-A1) “Dynamically Associated Predictive Digital Queues” and NPL: Y. Li and K. Katircioglu, "Measuring and Applying Service Request Effort Data in Application Management Services," 2013 IEEE International Conference on Services Computing, Santa Clara, CA, USA, 2013, pp. 352-359.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ayanna Minor whose telephone number is (571)272-3605. The examiner can normally be reached M-F 9am-5 pm.
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/A.M./Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624