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 Office Action is responsive to Applicant's amendment filed on 11 November 2025. Applicant’s amendment on 11 November 2025 amended Claims 1, 3, 5, 6, 10, 14-17, 19, 20, 23 and 24. Currently Claims 1-11, 13-20 and 22-24 are pending and have been examined. Claim 12 and 25 was previously canceled, claim 21 was never presented. The Examiner notes that the 101 is maintained.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 10 November 2025 has been entered.
Response to Arguments
Applicant's arguments filed 11 November 2025 have been fully considered but they are not persuasive.
The Applicant argues on pages 16-18 that “if claim 1 is directed to an abstract idea under Step 2A Prong 2, which Applicant is not herein conceding, the claims recite significantly more through specific technological implementations that provide computer functionality improvements. First, the claim recites "accessing a database, by the computing system processor and based on the initiation of the work session, to identify the multiple active conversation items occurring in the two or more communications simultaneously received from the one customer on the two or more communication channels. The claim also recites the steps of "identifying, by the computing system processor based on the multiple active conversation items, a work session channel type based on how synchronous each channel type is, wherein a voice channel type is more synchronous than a messaging channel type, and the messaging channel type is more synchronous than a mail channel type;" The claim also recites the additional steps of "assigning, by computing system processor, the identified work session channel type to the work session associated with the conversation, wherein the assigned channel type corresponds to a most synchronous channel type among the channel types within the conversation;"
These additional steps tie the live, real-time monitoring of multiple active conversation items across different channels to the processor's ability to make a decision on how synchronous the channel is based on a live, real-time communication monitoring. Based on how synchronous the channel is, the system assigns the channel to the work session. These steps add meaningful limitations to the abstract idea of "identifying and deriving workforce management data" and therefore add significantly more to the abstract idea than mere computer implementation. The claim, when taken as a whole, does not simply describe the step of receiving, identifying, tagging, tracking, and deriving workforce management data, but combines the steps of live, real- time communication monitoring for making a decision on how synchronous the channel. By this, the claim goes beyond the mere concept of simply identifying and deriving workforce management data using a computer. For all of these reasons, Applicant submits that independent claim 1 recites eligible subject matter. Similar reasoning applies to the § 101 rejection of independent claims 15 and 26. Thus, claims 15 and 26 also recite eligible subject matter. Given that the rest of the claims depend from one of these independent claims, all of the claims recite eligible subject matter. Accordingly, Applicant respectfully requests withdrawal of the § 101 rejection”.
The Examiner respectfully disagrees.
In response to the arguments the Examiner notes that the Applicant’s argument that the claims do not recite a judicial exception under Step 2A Prong One, relying on USPTO Example 39 involving neural network training for facial detection. However, this reliance is misplaced because Example 39 is distinguishable from the present claims in material respects that affect the eligibility analysis.
The claims recite at least two categories of abstract ideas enumerated in MPEP 2106.04(a)(2): (1) mental processes and (2) certain methods of organizing human activity, for the purpose of the examination the Examiner focused on the analysis with respect to mental process. Specifically, the claims recite: receiving an IT incident notification; retrieving and generating data structures representing IT incidents and remediation tasks; correlating the data structures; selecting remediation tasks based on evaluation of probabilities; generating an ordering of tasks; identifying skills associated with tasks; correlating automation tools with skills through text analysis and similarity comparisons; and generating a workflow of remediation tasks. These steps describe the fundamental activities of collecting information, analyzing relationships between data elements, evaluating options based on criteria, organizing tasks in a sequence, and creating a plan or workflow - all of which are mental processes that can be performed in the human mind, albeit with difficulty. See MPEP 2106.04(a)(2)(III) (mental processes include concepts performed in the human mind including observation, evaluation, judgment, and opinion). The use of generic computer components and a trained machine learning model to perform these mental processes does not avoid recitation of the abstract idea. See, e.g., CyberSource Corp. v. Retail Decisions, Inc., methods that can be performed by human thought alone, or by a person using pen and paper, are abstract ideas even when performed by a computer).
Additionally, the claims recite organizing human activity by coordinating and scheduling work tasks (IT remediation tasks) to be performed by various resources (automation tools and site reliability engineers). This falls within the "managing personal behavior or relationships or interactions between people" and "managing commercial or legal interactions" groupings of abstract ideas. See MPEP 2106.04(a)(2)(III).
Contrary to Applicant's assertion, the claims DO recite mathematical concepts. Claim 1 explicitly recites "evaluation of probabilities," "modeling text...as embeddings," and "performing similarity analysis, based on the embeddings." These are mathematical concepts as defined in MPEP 2106.04(a)(2)(I), which includes mathematical relationships, formulas, equations, and calculations. The fact that the claim does not use mathematical notation or explicitly recite a formula does not mean mathematical concepts are not recited when the claim describes mathematical operations such as probability evaluation, vector embeddings, and similarity analysis (which inherently involves mathematical distance measures or other quantitative comparisons).
Applicant's argument that the steps "cannot practically be performed in the human mind" misapprehends the legal standard. The test is not whether the steps are practical or efficient to perform mentally, but whether the claim limitations, considered individually and in combination, recite subject matter that falls within the judicial exception categories. Claims directed to abstract ideas do not become eligible merely because they are implemented using complex technology or performed more efficiently by a computer. As the Federal Circuit explained in Synopsys, Inc. v. Mentor Graphics Corp., "We have previously cautioned that courts 'must be careful to avoid oversimplifying the claims' by looking at them generally and failing to account for the specific requirements of the claims." However, the converse is also true - adding complexity through computational implementation does not necessarily transform an abstract idea into something concrete. The claims here describe receiving information about IT incidents, analyzing that information using various data structures and correlations, making decisions about which remediation tasks to perform and in what order based on evaluation criteria, and generating a workflow - these are fundamentally mental processes of information analysis and workflow planning, which humans regularly perform (though perhaps not at the same speed or scale).
Furthermore, the USPTO's August 4, 2025 Memorandum on Subject Matter Eligibility reminds Examiners to evaluate "whether the technological limitations are being used as a tool to improve the recited judicial exception (e.g., automating a manual business process) or whether the claim as a whole provides an improvement to technology or a technical field." Here, the machine learning model and other technological components are being used as tools to automate and improve the efficiency of the abstract idea of IT incident analysis and workflow generation, rather than providing a technological improvement to computer functionality itself. This is similar to the situation in Recentive Analytics, Inc. v. Fox Corp., where the court held that "steps incidental to automating an abstract idea were not sufficient to confer eligibility."
The distinction from Example 39 is critical. In Example 39, the claim was directed to a specific training methodology for neural networks to detect faces - the focus was on improving the technical process of facial detection itself, which is a technological improvement in computer vision. The claim did not recite the abstract idea of "identifying faces" but rather recited specific technical details about how to train a neural network with particular architectural features and training data to achieve better facial detection. In contrast, the present claims are directed to the abstract idea of analyzing IT incident information and generating workflows for remediation - the machine learning model is merely a tool used to perform this abstract organizational and analytical task more efficiently. The claims do not purport to improve how machine learning models function, how computers operate, or how IT infrastructure operates at a technical level; rather, they use existing technology (ML models, graph data structures, NLP) to automate the mental process of incident response planning.
For these reasons, the claims do recite judicial exceptions under Step 2A Prong One, and the analysis must proceed to Step 2A Prong Two to determine whether the judicial exceptions are integrated into a practical application. The Examiner will address whether the claims integrate the recited judicial exceptions into a practical application in a separate section of this Office Action, but notes that Applicant has not presented arguments directed to Step 2A Prong Two or Step 2B at this time. The rejection is therefore maintained.
The remaining Applicant's arguments filed 11 November 2025 have been fully considered but they are moot in view of new grounds of rejection as necessitated by amendment.
Examiner’s Note
The Examiner notes that no claim 21 was filed in this application. Claims 1-20 and 22-25 are presented for examination.
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 1-11, 13-20 and 22-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter because the claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. The claim(s) 1-11, 13-20 and 22-24 is/are directed to the abstract idea of the collection of information technology incident information and analyzing the data to provide remediation tasks and workflows. The claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more than the judicial exception itself. Claim(s) (1-11, 13-20 and 22-24) is/are directed to an abstract idea without significantly more.
Step 1
Regarding Step 1 of the Subject Matter Eligibility Test for Products and Processes (from the January 2019 §101 Examination Guidelines), claim(s) (1-11, 13-19, 22, and 23) is/are directed to a method, claim(s) (20) is/ are directed to a computer readable medium, and claims(s) (24) is/are directed to an apparatus and therefore the claims recite a series of steps and, therefore the claims are viewed as falling in statutory categories.
Step 2A Prong 1
The claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) a mental process. Specifically, the independent claims 1-20 and 22-25 recite a mental process: as drafted, the claim recites the limitation of generating IT remediation tasks and workflows which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a processor nothing in the claim precludes the determining step from practically being performed in the human mind. For example, but for the processor language, the claim encompasses the user manually collecting information regarding an IT incident and determining a tasks and workflow to remediate the incident. The mere nominal recitation of a generic processor does not take the claim limitation out of the mental processes grouping. It has been established by ongoing guidance that claims that contain a generic processor are still viewed as mental process when they contain limitations that can practically be performed in the human mind, however this is different for instance when the human mind is not equipped to perform the claim limitations (network monitoring, data encryption for communication, and rendering images). Therefore, these limitations are viewed a mental process. Additionally, with regard to the instant application the Examiner has reviewed the disclosure and determined that the underlying claimed invention is described as a concept that is performed in the human mind and/or with the aid of a pen and paper, and thus it is viewed that the applicant is merely claiming that concept performed 1) on a generic computer, 2) in a computer environment or 3) is merely using a computer as a tool to perform the concept, and therefore is considered to recite a mental process.
Note to the Applicant per the 2019 October Guidance: The 2019 PEG sets forth a test that distills the relevant case law to aid in examination, and does not attempt to articulate each and every decision. As further explained in the 2019 PEG, the Office has shifted its approach from the case-comparison approach in determining whether a claim recites an abstract idea and instead uses enumerated groupings of abstract ideas. The enumerated groupings are firmly rooted in Supreme Court precedent as well as Federal Circuit decisions interpreting that precedent. By grouping the abstract ideas, the 2019 PEG shifts examiners’ focus from relying on individual cases to generally applying the wide body of case law spanning all technologies and claim types. In sum, the 2019 PEG synthesizes the holdings of various court decisions to facilitate examination.
Step 2A Prong 2
Specifically, the determined judicial exception is not integrated into a practical application because (select one the generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer and additionally that data receiving, retrieving, extracting, and executing steps required to use the correlation do not add a meaningful limitation to the method as they are insignificant extra-solution activity (including post solution activity).
The claim recites the additional element(s): that a processor is used to perform both the generating and correlating steps. The processor in both steps is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data (collection of information technology incident information and analyzing the data to provide remediation tasks and workflows). This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
The claim recites the additional element(s): receiving IT incident notification, retrieving knowledge data structure, extracting one or more IT remediation tasks, generating at least one knowledge graph, executing a first correlation operation, generation a first correlation, executing a second correlation, and performing similarity analysis and executing the generated IT incident remediation task workflow performs the generating step. The receiving, retrieving, generating, extracting, and executing steps are recited at a high level of generality (i.e., as a general means of gathering IT incident information for use in the generating and correlating steps), and amounts to mere data management, which is a form of insignificant extra-solution activity. The processor that performs the generating and correlating steps are also recited at a high level of generality, and merely automates the generating and correlating steps. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component (the processor).
The Examiner has further determined that the claims as a whole does not integrate a judicial exception into a practical application in order to provide an improvement in the functioning of a computer or an improvement to other technology or technical field. It has been determined that based on the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. It has not been provided clearly in the disclosure that the alleged improvement would be apparent to one of ordinary skill in the art, but is instead in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art, and therefore does not improve the technology. Second, in the instance, which in this case it is not clear that the specification sets forth an improvement in technology, the claim must not reflect the disclosed improvement (the claims must include components or steps of the invention that provide the improvement described in the specification).
Note to the Applicant from the October 2019 Guidance: Generally, examiners are not expected to make a qualitative judgment on the merits of the asserted improvement. If the examiner concludes the disclosed invention does not improve technology, the burden shifts to applicant to provide persuasive arguments supported by any necessary evidence to demonstrate that one of ordinary skill in the art would understand that the disclosed invention improves technology. Any such evidence submitted under 37 C.F.R. § 1.132 must establish what the specification would convey to one of ordinary skill in the art and cannot be used to supplement the specification. For example, in response to a rejection under 35 U.S.C. § 101, an applicant could submit a declaration under § 1.132 providing testimony on how one of ordinary skill in the art would interpret the disclosed invention as improving technology and the underlying factual basis for that conclusion.
For further clarification the Examiner points out that the claim(s) 1-11, 13-20 and 22-24 recite(s) receiving IT incident notification, retrieving knowledge data structure, extracting one or more IT remediation tasks, generating an IT remediation task, executing a correlation operation, executing the generated IT incident remediation task workflow, and generating an IT remediation workflow which are viewed as an abstract idea in the form of a mental process. This judicial exception is not integrated into a practical application because the use of a computer for receiving, generating, executing, and generating which is the abstract idea steps of valuing an idea (the collection of information technology incident information and analyzing the data to provide remediation tasks and workflows) in the manner of “apply it”.
Thus, the claims recite an abstract idea directed to a mental process (i.e. to the collection of information technology incident information and analyzing the data to provide remediation tasks and workflows). Using a computer to obtaining, classifying, quantifying, generation, identifying, and determining the data resulting from this kind of mental process merely implements the abstract idea in the manner of “apply it” and does not provide 'something more' to make the claimed invention patent eligible. The claimed limitations of a computing device are not constraining the abstract idea to a particular technological environment and do not provide significantly more.
The collection of information technology incident information and analyzing the data to provide remediation tasks and workflows would clearly be to a mental activity that a company would go through in order to decide how to mitigate IT incidents based on an analysis of the collected data regarding the incident. The specification makes it clear that the claimed invention is directed to the mental activity data gathering and data analysis to determine how to manage an IT incident:
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’.
The dependent claims do not remedy these deficiencies.
Claims 2, 3, 5, 8, 10, 11, 13-17, and 22 recite limitations which further limit the claimed analysis of data.
Claims 6, 7, 19, and 23 recites limitations directed to claim language viewed insignificantly extra solution activity.
Using a computer to perform the data processing as claimed is merely implementing the abstract idea in the manner of “apply it” and does not provide significantly more. Additionally with respect to the Berkheimer the Examiner points out that the steps of the claim are viewed to be to nothing more than spell out what it means to apply it on a computer and cannot confer patent-eligibility as there are no additional limitations beyond applying an abstract idea, restricted to a computer. As the claims are merely implementing the abstract idea in the manner of “Apply It” the need for a Berkheimer analysis does not apply and is not required. With respect to the currently filed claims the implementing steps can be found in Werth which discloses how the claims alone and in combination are viewed to be well understood, routine and conventional based on point 3 of the Berkheimer memo and subsequent evidence, complying with and providing evidence.
Claims 4, 9, and 18 recites limitations directed to claim language viewed non-functional data labels.
Thus, the problem the claimed invention is directed to answering the question based on the collection of information technology incident information and analyzing the data to provide remediation tasks and workflows. This is not a technical or technological problem but is rather in the realm of IT remediation problem solving and therefore an abstract idea.
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed with respect to Step 2A Prong Two, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. This is the case because in order for the claims to be viewed as significantly more the claims must incorporate the integral use of a machine to achieve performance of a method, in contrast to where the machine is merely an object on which the method operates, which does not provide significantly more in order for a machine to add significantly more, it must play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly. Whether its involvement is extra-solution activity or a field-of-use, i.e., the extent to which (or how) the machine or apparatus imposes meaningful limits on the claim. Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more. Additionally, another consideration when determining whether a claim recites significantly more is whether the claim effects a transformation or reduction of a particular article to a different state or thing. "[T]ransformation and reduction of an article ‘to a different state or thing’ is the clue to patentability of a process claim that does not include particular machines. All together the above analysis shows there is not improvement in computer functionality, or improvement to any other technology or technical field. The claim is ineligible.
With respect to the Berkheimer as noted above the same analysis applies to the 2B where the claims are viewed as applying it and as such no further analysis is required. However, with respect to the claims that are viewed as extra solution or post solution activity the Examiner notes that the claims are viewed as well-understood, routine, and conventional because a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s). An appropriate publication could include a book, manual, review article, or other source that describes the state of the art and discusses what is well-known and in common use in the relevant industry.
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’. Specifically, the dependent claims do not remedy these deficiencies of the independent claims.
With respect to the legal concept of prima facie case being a procedural tool of patent examination, which allocates the burdens going forward between the examiner and the applicant. MPEP § 2106.07 discusses the requirements of a prima facie case of ineligibility. In particular, the initial burden was on the Examiner and believed to be properly provided as to explain why the claim(s) are ineligible for patenting because of the above provided rejection which clearly and specifically points out in accordance with properly providing the requirement satisfying the initial burden of proof based on the Guidance from the United States Patent and Trademark Office and the burden now shifts to the applicant.
Therefore, based on the above analysis as conducted based on the Guidance from the United States Patent and Trademark Office the claims are viewed as a court recognized abstract idea, are viewed as a judicial exception, does not integrate the claims into a practical application, and does not provide an inventive concept, therefore the claims are ineligible.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent may not be obtained through the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 1-6, 8-11, 14-20, and 22-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (U.S. Patent Publication 2023/0132465 A1) (hereafter Kumar) in view of Werth et al. (U.S. Patent Publication 2013/0103973 A1) (hereafter Werth).
Referring to Claim 1, Kumar teaches a method comprising:
receiving an information technology (IT) incident notification specifying an IT incident (see; par. [0027] of Kumar teaches receiving IT incident or tickets (i.e. notification)).
retrieving at least one IT topology graph data structure associated with at least one IT resource, of an IT infrastructure, corresponding to the IT incident (see; par. [0027] of Kumar teaches a digital record of the IT incident or evet with all relevant information what happen (i.e. incident)).
generating at least one knowledge graph data structure comprising nodes corresponding to IT incidents and IT remediation tasks and edges representing relationships between the IT incidents and the IT remediation tasks (see; par., [0027] of Kumar teaches a knowledge graph is created, par. [0046]-[0048] including nodes and matrix of nodes based on skills related to incidents)
executing at least one first correlation operation that correlates the at least one IT topology graph data structure with the at least one knowledge graph data structure (see; par. [0094] of Kumar identifying the link (i.e. correlation) between incidents and resolution in an IT environment and par. [0027] a knowledge graph is created).
generating, based on results of the at least one first correlation operation, an ordering of one or more IT remediation tasks for handling the IT incident (see; par. [0027] of Kumar teaches assigning automatically the person skilled workers to perform the needed fix of the determined ticket that has necessary tasks to be performed).
executing at least one second correlation operation by modeling the text corresponding to IT remediation task descriptions and automation tool descriptions (see; par. [0043] of Kumar teaches performing on analysis (i.e. correlate) that models the topic of the skill necessary to fix the task (i.e. remediation) from previous tickets (i.e. corresponding) to the current problem, par. [0049] while also modeling language to understand the skill and issues).
wherein the at least one second correlation operation correlates at least one automated tool catalog data structure with the IT remediation task skill set (see; par. [0025] of Kumar teaches historical skills (i.e. tools) to handle the task).
wherein the text corresponding to the IT remediation task descriptions and the automation tool descriptions are modeled as embeddings (see; par. [0049]-[0050] of Kumar teaches taxonomy of terms (i.e. task descriptions) and skill to fix (i.e. automate description) are generated and embedded).
wherein the executing further comprises performing similarity analysis, based on the embeddings, between the text corresponding to the IT remediation task descriptions and the automation tool descriptions (see; par. [0095] of Kumar teaches an example of understanding the similarity between the task (i.e. remediation task) and, par. [0006] auto routing to a identified agent having necessary skill score (i.e. tool description)).
Kumar does not explicitly disclose the following limitation, however,
Werth teaches generating an IT incident remediation task workflow, based on the ordering of the one or more IT remediation tasks, the IT remediation task skill set and results of the at least one second correlation operation (see; par. [0117]-[0118] of Werth teaches generating tasks to fulfill the service level attributes and selecting the technology with the correct level of skill),
generating an IT remediation task skill set at least by identifying one or more skills in a plurality of predetermined skills that are associated with the one or more IT remediation tasks (see; par. [0117]-[0118] of Werth teaches dispatching remediation tasks and assigning correct technicians with proper skill sets to handle the tasks), and
automatically executing the generated IT incident remediation task workflow on the at least one IT resource (see; par. [0275] of Werth teaches automatically generating a workflow to manage remediation tasks with respect to information technical support).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose generating an IT incident remediation task workflow, based on the ordering of the one or more IT remediation tasks, the IT remediation task skill set and results of the at least one second correlation operation, generating an IT remediation task skill set at least by identifying one or more skills in a plurality of predetermined skills that are associated with the one or more IT remediation tasks, and automatically executing the generated IT incident remediation task workflow on the at least one IT resource.
Werth discloses generating an IT incident remediation task workflow, based on the ordering of the one or more IT remediation tasks, the IT remediation task skill set and results of the at least one second correlation operation, generating an IT remediation task skill set at least by identifying one or more skills in a plurality of predetermined skills that are associated with the one or more IT remediation tasks, and automatically executing the generated IT incident remediation task workflow on the at least one IT resource.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar generating an IT incident remediation task workflow, based on the ordering of the one or more IT remediation tasks, the IT remediation task skill set and results of the at least one second correlation operation, generating an IT remediation task skill set at least by identifying one or more skills in a plurality of predetermined skills that are associated with the one or more IT remediation tasks, and automatically executing the generated IT incident remediation task workflow on the at least one IT resource as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Kumar in view of Werth dose not disclose the following limitation, however,
Loving teaches selecting, using a machine learning model, one or more IT remediation tasks for handling the IT incident, wherein the machine learning model is trained to select the one or more IT remediation tasks based at least in part on evaluation of probabilities that respective IT remediation tasks will be successfully performed using one or more automation tools from an automation tools catalog data structure (see; par. [0061] of Loving teaches a machine learning model that handles special remediation of errors and utilizes the percentage of success as a metric (i.e. probability of success) by automated tools utilizing a task library (i.e. catalog data structure)).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Loving teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth and Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Werth and Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Werth and Kumar fails to disclose selecting, using a machine learning model, one or more IT remediation tasks for handling the IT incident, wherein the machine learning model is trained to select the one or more IT remediation tasks based at least in part on evaluation of probabilities that respective IT remediation tasks will be successfully performed using one or more automation tools from an automation tools catalog data structure.
Loving discloses selecting, using a machine learning model, one or more IT remediation tasks for handling the IT incident, wherein the machine learning model is trained to select the one or more IT remediation tasks based at least in part on evaluation of probabilities that respective IT remediation tasks will be successfully performed using one or more automation tools from an automation tools catalog data structure.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Werth and Kumar selecting, using a machine learning model, one or more IT remediation tasks for handling the IT incident, wherein the machine learning model is trained to select the one or more IT remediation tasks based at least in part on evaluation of probabilities that respective IT remediation tasks will be successfully performed using one or more automation tools from an automation tools catalog data structure as taught by Loving since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar, Werth, and Loving teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 2, see discussion of claim 1 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches comprising executing at least one third correlation operation that correlates at least one site reliability engineer with at least one corresponding second skill in the IT remediation task skill set, wherein generating the IT incident remediation task workflow further comprises generating the IT incident remediation task workflow based results of the at least one third correlation operation (see; par. [0380] of Werth teaches onsite technician (i.e. engineer) correlates findings based on assigned tasks and generates or triggers any necessary changes, par. [0275] which includes assigning technicians to workflow as necessary, in par. [0154] in addition to possibly reassigning the task to a different qualified technician).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose comprising executing at least one third correlation operation that correlates at least one site reliability engineer with at least one corresponding second skill in the IT remediation task skill set, wherein generating the IT incident remediation task workflow further comprises generating the IT incident remediation task workflow based results of the at least one third correlation operation.
Werth discloses comprising executing at least one third correlation operation that correlates at least one site reliability engineer with at least one corresponding second skill in the IT remediation task skill set, wherein generating the IT incident remediation task workflow further comprises generating the IT incident remediation task workflow based results of the at least one third correlation operation.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar comprising executing at least one third correlation operation that correlates at least one site reliability engineer with at least one corresponding second skill in the IT remediation task skill set, wherein generating the IT incident remediation task workflow further comprises generating the IT incident remediation task workflow based results of the at least one third correlation operation as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 3, see discussion of claim 2 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar further discloses a method having the limitations of,
executing the at least one third correlation operation further comprises identifying one or more skill gaps, for the one or more skill gaps, wherein a skill gap is a skill in the IT remediation task skill set for which there is no automation tool that provides the skill (see; par. [0026] of Kumar teaches skill gap identification and training to address skills necessary by the agent to address IT issues).
Referring to Claim 4, see discussion of claim 3 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar further discloses a method having the limitations of,
the second skill is a skill associated with a skill gap of the one or more skill gaps, and wherein the third correlation operation is only performed with regard to skills associated with the one or more skill gaps (see; par. [0026] of Kumar teaches adjusting to different skilled individuals that can address the task including skill gaps).
Referring to Claim 5, see discussion of claim 3 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar further discloses a method having the limitations of,
determining for a corresponding IT remediation task associated with a skill associated with a skill gap of the one or more skill gaps,, whether a fallback IT remediation task is available that could be performed instead of the corresponding IT remediation task (see; par. [0026] of Kumar teaches adjusting to different skilled individuals that can address the task including skill gaps).
Kumar does not explicitly disclose the following limitation, however,
Werth teaches for each of the one or more skill gaps (see; par. [0117]-[0118] assigning a technician with correct skills, par. [0094] finding necessary technicians), and
in response to determining the fallback IT remediation task is available that could be performed instead of the corresponding IT remediation task, determining if an automation tool is available that provides a skill needed to perform the fallback IT remediation task (see; par. [0094] of Werth teaches a fallback remote worker completes the necessary task when the automated system is unable or the first technician is not capable to remediate the task, par. [0314] that works with the automated system to complete the necessary tasks, par. [0117]-[0118] assigning a technician with correct skills, par. [0094] finding necessary technicians), and
in response to determining that an automation tool is available that provides a skill needed to perform the fallback IT remediation task, replacing the corresponding IT remediation task with the fallback IT remediation task in the IT remediation task workflow and selecting the automation tool to perform the fallback IT remediation task in the IT remediation task workflow (see; par. [0094]-[0095] of Werth teaches a combination of automated systems and backup service technicians to perform the task where a fallback remote worker completes the necessary task when the automated system is unable or the first technician is not capable to remediate the task, par. [0275] including performing the necessary workflow).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose for each of the one or more skill gaps, in response to determining the fallback IT remediation task is available that could be performed instead of the corresponding IT remediation task, determining if an automation tool is available that provides a skill needed to perform the fallback IT remediation task, and in response to determining that an automation tool is available that provides a skill needed to perform the fallback IT remediation task, replacing the corresponding IT remediation task with the fallback IT remediation task in the IT remediation task workflow and selecting the automation tool to perform the fallback IT remediation task in the IT remediation task workflow.
Werth discloses for each of the one or more skill gaps, in response to determining the fallback IT remediation task is available that could be performed instead of the corresponding IT remediation task, determining if an automation tool is available that provides a skill needed to perform the fallback IT remediation task, and in response to determining that an automation tool is available that provides a skill needed to perform the fallback IT remediation task, replacing the corresponding IT remediation task with the fallback IT remediation task in the IT remediation task workflow and selecting the automation tool to perform the fallback IT remediation task in the IT remediation task workflow.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar for each of the one or more skill gaps, in response to determining the fallback IT remediation task is available that could be performed instead of the corresponding IT remediation task, determining if an automation tool is available that provides a skill needed to perform the fallback IT remediation task, and in response to determining that an automation tool is available that provides a skill needed to perform the fallback IT remediation task, replacing the corresponding IT remediation task with the fallback IT remediation task in the IT remediation task workflow and selecting the automation tool to perform the fallback IT remediation task in the IT remediation task workflow as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 6, see discussion of claim 5 above, while Kumar in view of Werth in further view of Loving teaches the method above, Werth further discloses a method having the limitations of:
Werth teaches in response to the automation tool not being available that provides the skill needed to perform the fallback IT remediation task, performing a lookup operation in a site reliability engineer data structure based on the skill needed to perform the fallback IT remediation task (see; par. [0334] of Werth teaches scripts are provided to a technicians so that they can remotely remediate if an automated solution is not possible (i.e. fall back remediation), par. [0128] using a lookup table to provide data), and
in response to identifying an entry for a site reliability engineer or a site reliability engineering team, in the site reliability engineer data structure, that provides the skill needed to perform the fallback IT remediation task, replacing the corresponding IT remediation task with the fallback IT remediation task in the IT remediation task workflow and selecting the site reliability engineer or site reliability engineering team to perform the fallback IT remediation task in the IT remediation task workflow (see; par. [0378] of Werth teaches determining if an automated repair is possible to fix a problem, par. [0115] where tasks requiring manual maintenance by a remote technician to perform new services based on need).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose in response to the automation tool not being available that provides the skill needed to perform the fallback IT remediation task, performing a lookup operation in a site reliability engineer data structure based on the skill needed to perform the fallback IT remediation task, and in response to identifying an entry for a site reliability engineer or a site reliability engineering team, in the site reliability engineer data structure, that provides the skill needed to perform the fallback IT remediation task, replacing the corresponding IT remediation task with the fallback IT remediation task in the IT remediation task workflow and selecting the site reliability engineer or site reliability engineering team to perform the fallback IT remediation task in the IT remediation task workflow.
Werth discloses in response to the automation tool not being available that provides the skill needed to perform the fallback IT remediation task, performing a lookup operation in a site reliability engineer data structure based on the skill needed to perform the fallback IT remediation task, and in response to identifying an entry for a site reliability engineer or a site reliability engineering team, in the site reliability engineer data structure, that provides the skill needed to perform the fallback IT remediation task, replacing the corresponding IT remediation task with the fallback IT remediation task in the IT remediation task workflow and selecting the site reliability engineer or site reliability engineering team to perform the fallback IT remediation task in the IT remediation task workflow.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar in response to the automation tool not being available that provides the skill needed to perform the fallback IT remediation task, performing a lookup operation in a site reliability engineer data structure based on the skill needed to perform the fallback IT remediation task, and in response to identifying an entry for a site reliability engineer or a site reliability engineering team, in the site reliability engineer data structure, that provides the skill needed to perform the fallback IT remediation task, replacing the corresponding IT remediation task with the fallback IT remediation task in the IT remediation task workflow and selecting the site reliability engineer or site reliability engineering team to perform the fallback IT remediation task in the IT remediation task workflow as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 8, see discussion of claim 1 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches executing natural language processing configured with an IT remediation task vocabulary of terms/phrases indicative of IT incidents on the at least one knowledge graph data structure (see; par. [0334] of Werth teaches utilizing scripts (i.e. natural language) to provide remediation tasks to technicians), and
identifying an ordered sequence of IT remediation tasks based on the natural language processing of the at least one knowledge graph data structure (see; par. [0153] of Werth teaches updating one or more tasks, par. [0334] using scripts (i.e. natural language) to provide remediation tasks).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose executing natural language processing configured with an IT remediation task vocabulary of terms/phrases indicative of IT incidents on the at least one knowledge graph data structure, and identifying an ordered sequence of IT remediation tasks based on the natural language processing of the at least one knowledge graph data structure.
Werth discloses executing natural language processing configured with an IT remediation task vocabulary of terms/phrases indicative of IT incidents on the at least one knowledge graph data structure, and identifying an ordered sequence of IT remediation tasks based on the natural language processing of the at least one knowledge graph data structure.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar executing natural language processing configured with an IT remediation task vocabulary of terms/phrases indicative of IT incidents on the at least one knowledge graph data structure, and identifying an ordered sequence of IT remediation tasks based on the natural language processing of the at least one knowledge graph data structure as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 9, see discussion of claim 8 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches at least one natural language document comprises, for each of the at least one IT resource, a corresponding knowledge article having portions describing IT incidents and portions describing IT remediation tasks for the IT incidents, and wherein the natural language processing comprises a sentence similarity processing between the IT remediation task vocabulary and the portions of the knowledge article (see; par. [0334] of Werth teaches scripts used to have a remote technician handle issues and remediation tasks to be addressed).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose at least one natural language document comprises, for each of the at least one IT resource, a corresponding knowledge article having portions describing IT incidents and portions describing IT remediation tasks for the IT incidents, and wherein the natural language processing comprises a sentence similarity processing between the IT remediation task vocabulary and the portions of the knowledge article.
Werth discloses at least one natural language document comprises, for each of the at least one IT resource, a corresponding knowledge article having portions describing IT incidents and portions describing IT remediation tasks for the IT incidents, and wherein the natural language processing comprises a sentence similarity processing between the IT remediation task vocabulary and the portions of the knowledge article.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar at least one natural language document comprises, for each of the at least one IT resource, a corresponding knowledge article having portions describing IT incidents and portions describing IT remediation tasks for the IT incidents, and wherein the natural language processing comprises a sentence similarity processing between the IT remediation task vocabulary and the portions of the knowledge article as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 10, see discussion of claim 1 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches executing the second correlation operation comprises performing natural language processing of automation tool descriptions in the automation tools catalog data structure to identify skills associated with automation tools and performing a sentence similarity analysis of the automation tool descriptions with the skills in the IT remediation task skill set (see; par. [0132] of Werth teaches selecting technicians with the right skills, par. [0334] and providing scripts to the technician to handle the issues, par. [0138] as well as modifications to the skills that are needed based on what is required to resolve or remediate the IT issue).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose executing the second correlation operation comprises performing natural language processing of automated tool descriptions in an automated tool catalog data structure to identify skills associated with automated tools and performing a sentence similarity analysis of the automated tool descriptions with the skills in the IT remediation task skill set.
Werth discloses executing the second correlation operation comprises performing natural language processing of automated tool descriptions in an automated tool catalog data structure to identify skills associated with automated tools and performing a sentence similarity analysis of the automated tool descriptions with the skills in the IT remediation task skill set.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar executing the second correlation operation comprises performing natural language processing of automated tool descriptions in an automated tool catalog data structure to identify skills associated with automated tools and performing a sentence similarity analysis of the automated tool descriptions with the skills in the IT remediation task skill set as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 11, see discussion of claim 2 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches executing the third correlation operation comprises processing one or more site reliability engineer (SRE) data structures specifying skills associated with different SREs or SRE teams and matching skills associated with different SREs or SRE teams with the IT remediation task skill set (see; par. [0132] and par. [0138]-[0139- of Werth teaches selecting technicians with the right skills and utilizing groups (i.e. teams) as necessary to handle the IT remediation task).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose executing the third correlation operation comprises processing one or more site reliability engineer (SRE) data structures specifying skills associated with different SREs or SRE teams and matching skills associated with different SREs or SRE teams with the IT remediation task skill set.
Werth discloses executing the third correlation operation comprises processing one or more site reliability engineer (SRE) data structures specifying skills associated with different SREs or SRE teams and matching skills associated with different SREs or SRE teams with the IT remediation task skill set.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar executing the third correlation operation comprises processing one or more site reliability engineer (SRE) data structures specifying skills associated with different SREs or SRE teams and matching skills associated with different SREs or SRE teams with the IT remediation task skill set as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 14, see discussion of claim 2 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches classifying the one or more skills in the plurality of predetermined skills as being one of a plurality of predetermined skill types, wherein the skill types comprise an action skill type, a monitor skill type, a fallback skill type, and a rollback skill type (see; par. [0378] of Werth teaches determining automation is not possible, par. [0115] and tasks requiring manual maintenance by remote technicians to perform the IT related remediation, par. [0167] and additionally designating skill sets in order to assign a technician to handle the tasks, par. [0117] where technicians have information regarding skill sets and knowledge to perform different tasks), and
generating the IT incident remediation task workflow comprises selecting, for each IT remediation task in the IT incident remediation task workflow, at least one automation tool or site reliability engineer based on a trained machine learning computer model that scores the at least one automation tool and at least one site reliability engineer based on results of the second correlation operation, results of the third correlation operation, a classification of skills associated with the at least one automation tool, and a classification of skills associated with the at least one site reliability engineer (see; par. [0281] of Werth teaches generating a workflow based on identifying a sequence of events that include identifying the next step or event to be performed by an application programs, person or tool and identifies who can perform it (i.e. skills), par. [0167] designating skill sets, par. [0122] using a learning algorithms (i.e. machine learning)).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose classifying the one or more skills in the plurality of predetermined skills as being one of a plurality of predetermined skill types, wherein the skill types comprise an action skill type, a monitor skill type, a fallback skill type, and a rollback skill type, and generating the IT incident remediation task workflow comprises selecting, for each IT remediation task in the IT incident remediation task workflow, at least one automation tool or site reliability engineer based on a trained machine learning computer model that scores the at least one automation tool and at least one site reliability engineer based on results of the second correlation operation, results of the third correlation operation, a classification of skills associated with the at least one automation tool, and a classification of skills associated with the at least one site reliability engineer.
Werth discloses classifying the one or more skills in the plurality of predetermined skills as being one of a plurality of predetermined skill types, wherein the skill types comprise an action skill type, a monitor skill type, a fallback skill type, and a rollback skill type, and generating the IT incident remediation task workflow comprises selecting, for each IT remediation task in the IT incident remediation task workflow, at least one automation tool or site reliability engineer based on a trained machine learning computer model that scores the at least one automation tool and at least one site reliability engineer based on results of the second correlation operation, results of the third correlation operation, a classification of skills associated with the at least one automation tool, and a classification of skills associated with the at least one site reliability engineer.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar classifying the one or more skills in the plurality of predetermined skills as being one of a plurality of predetermined skill types, wherein the skill types comprise an action skill type, a monitor skill type, a fallback skill type, and a rollback skill type, and generating the IT incident remediation task workflow comprises selecting, for each IT remediation task in the IT incident remediation task workflow, at least one automation tool or site reliability engineer based on a trained machine learning computer model that scores the at least one automation tool and at least one site reliability engineer based on results of the second correlation operation, results of the third correlation operation, a classification of skills associated with the at least one automation tool, and a classification of skills associated with the at least one site reliability engineer as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 15, see discussion of claim 14 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches the trained machine learning computer model scores the at least one automation tool and the at least one site reliability engineer based on a degree of matching of skills associated with the at least one automation tool and skills associated with the at least one site reliability engineer, and based on whether or not the at least one automation tool and the at least one site reliability engineer has a rollback skill or a fallback skill (see; par. [0122] of Werth teaches using learning algorithms (i.e. machine learning), par. [0127] to identify a metric used to identify a qualitative or quantitative aspect related to perform the service including a technician based on skills, [0378] in addition based on determining if automation is not possible, par. [0115] and tasks requiring manual maintenance by remote technicians to perform the IT related remediation).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose the trained machine learning computer model scores the at least one automation tool and the at least one site reliability engineer based on a degree of matching of skills associated with the at least one automation tool and skills associated with the at least one site reliability engineer, and based on whether or not the at least one automation tool and the at least one site reliability engineer has a rollback skill or a fallback skill.
Werth discloses the trained machine learning computer model scores the at least one automation tool and the at least one site reliability engineer based on a degree of matching of skills associated with the at least one automation tool and skills associated with the at least one site reliability engineer, and based on whether or not the at least one automation tool and the at least one site reliability engineer has a rollback skill or a fallback skill.
It would be obvious to one of ordinary skill in the art to include in the task management (system/method/apparatus) of Kumar the trained machine learning computer model scores the at least one automation tool and the at least one site reliability engineer based on a degree of matching of skills associated with the at least one automation tool and skills associated with the at least one site reliability engineer, and based on whether or not the at least one automation tool and the at least one site reliability engineer has a rollback skill or a fallback skill as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 16, see discussion of claim 15 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches selecting the at least one automation tool or site reliability engineer further comprises performing an exploratory orchestration operation at least by identifying, for one or more of the IT remediation tasks in the IT incident remediation task workflow, one or more fallback tasks based on the classification of the one or more skills in the plurality of predetermined skills, and generating alternative IT incident remediation task workflows comprising the one or more fallback tasks (see; par. [0378] of Werth teaches determining if automation is not possible, par. [0115] and tasks requiring manual maintenance by remote technicians to perform the IT related remediation, par. [0068]-[0069] where there is a performing of diagnostics (i.e. exploratory operation), par. [0121] and then assigning a technician with proper background, skills, knowledge, training and certification to handle the remediation),
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose selecting the at least one automation tool or site reliability engineer further comprises performing an exploratory orchestration operation at least by identifying, for one or more of the IT remediation tasks in the IT incident remediation task workflow, one or more fallback tasks based on the classification of the one or more skills in the plurality of predetermined skills, and generating alternative IT incident remediation task workflows comprising the one or more fallback tasks.
Werth discloses selecting the at least one automation tool or site reliability engineer further comprises performing an exploratory orchestration operation at least by identifying, for one or more of the IT remediation tasks in the IT incident remediation task workflow, one or more fallback tasks based on the classification of the one or more skills in the plurality of predetermined skills, and generating alternative IT incident remediation task workflows comprising the one or more fallback tasks.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar selecting the at least one automation tool or site reliability engineer further comprises performing an exploratory orchestration operation at least by identifying, for one or more of the IT remediation tasks in the IT incident remediation task workflow, one or more fallback tasks based on the classification of the one or more skills in the plurality of predetermined skills, and generating alternative IT incident remediation task workflows comprising the one or more fallback tasks as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 17, see discussion of claim 1 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches generating the IT incident remediation task workflow comprise executing a trained machine learning computer tool on input features corresponding to the IT remediation task skill set, characteristics of the automation tools from the automation tools catalog, characteristics of site reliability engineers or site reliability engineering teams from a site reliability engineering data structure, the correspondence of the at least one automated tool with the at least one corresponding first skill, and the correspondence of at least one site reliability engineer with at least one corresponding second skill to score each automation tool and site reliability engineer or site reliability engineering team for performing each IT remediation task in the IT remediation task workflow (see; par. [0378] of Werth teaches determining if automation is not possible, par. [0115] and tasks requiring manual maintenance by remote technicians to perform the IT related remediation, par. [0068]-[0069] where there is a performing of diagnostics (i.e. exploratory operation), par. [0121] and then assigning a technician with proper background, skills, knowledge, training and certification to handle the remediation, par. [0122] using a learning algorithms (i.e. machine learning), par. [0127] and including using a metric of performing the service (tool and performance of the technician)).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose generating the IT incident remediation task workflow comprise executing a trained machine learning computer tool on input features corresponding to the IT remediation task skill set, characteristics of the automation tools from the automation tools catalog, characteristics of site reliability engineers or site reliability engineering teams from a site reliability engineering data structure, the correspondence of the at least one automated tool with the at least one corresponding first skill, and the correspondence of at least one site reliability engineer with at least one corresponding second skill to score each automation tool and site reliability engineer or site reliability engineering team for performing each IT remediation task in the IT remediation task workflow.
Werth discloses generating the IT incident remediation task workflow comprise executing a trained machine learning computer tool on input features corresponding to the IT remediation task skill set, characteristics of the automation tools from the automation tools catalog, characteristics of site reliability engineers or site reliability engineering teams from a site reliability engineering data structure, the correspondence of the at least one automated tool with the at least one corresponding first skill, and the correspondence of at least one site reliability engineer with at least one corresponding second skill to score each automation tool and site reliability engineer or site reliability engineering team for performing each IT remediation task in the IT remediation task workflow.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar generating the IT incident remediation task workflow comprise executing a trained machine learning computer tool on input features corresponding to the IT remediation task skill set, characteristics of the automation tools from the automation tools catalog, characteristics of site reliability engineers or site reliability engineering teams from a site reliability engineering data structure, the correspondence of the at least one automated tool with the at least one corresponding first skill, and the correspondence of at least one site reliability engineer with at least one corresponding second skill to score each automation tool and site reliability engineer or site reliability engineering team for performing each IT remediation task in the IT remediation task workflow as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 18, see discussion of claim 1 above, while Kumar in view of Werth in further view of Loving teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches selecting, for each IT remediation task in the IT remediation task workflow, at least one of an automation tool, site reliability engineer, or site reliability engineering team to perform the IT remediation task based on the scores (see; par. [0127] of Werth teaches selecting a technician that meets a desired metric (i.e. for a site engineer)).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose selecting, for each IT remediation task in the IT remediation task workflow, at least one of an automation tool, site reliability engineer, or site reliability engineering team to perform the IT remediation task based on the scores.
Werth discloses selecting, for each IT remediation task in the IT remediation task workflow, at least one of an automation tool, site reliability engineer, or site reliability engineering team to perform the IT remediation task based on the scores.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar selecting, for each IT remediation task in the IT remediation task workflow, at least one of an automation tool, site reliability engineer, or site reliability engineering team to perform the IT remediation task based on the scores as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 19, see discussion of claim 1 above, while Kumar in view of Werth in further view of Living teaches the method above, Kumar does not explicitly disclose a method having the limitations of, however,
Werth teaches the IT incident remediation task workflow comprises at least one first IT remediation task that has an associated automation tool assigned to perform the at least one first IT remediation task, and at least one second IT remediation task that has an associated site reliability engineer or site reliability engineering team assigned to perform the at least one second IT remediation task, and wherein automatically executing the generated IT incident remediation task workflow on the at least one IT resource comprises: (see; par. [0380] of Werth teaches onsite technician (i.e. engineer) correlates findings based on assigned tasks and generates or triggers any necessary changes, par. [0275] which includes assigning technicians to workflow as necessary, in par. [0154] in addition to possibly reassigning the task to a different qualified technician), and
for each first IT remediation task, automatically invoking the associated automation tool to execute operations to perform the first IT remediation task and awaiting an automation response indicating completion of the first IT remediation task by the associated automation tool (see; par. [0241] of Werth teaches an automated service or providing and transmitting information when complete), and
for each second IT remediation task, automatically transmitting an electronic communication to a computing device associated with the site reliability engineer or site reliability engineering team and awaiting a responsive communication from the computing device indicating completion of the second IT remediation task by the site reliability engineer or site reliability engineering team (see; par. [0275] of Werth teaches automatically transmitting an communication to a device associated with the technician and assigning the remediation task to par. [0127] a different technician with the correct skills).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar fails to disclose the IT incident remediation task workflow comprises at least one first IT remediation task that has an associated automation tool assigned to perform the at least one first IT remediation task, and at least one second IT remediation task that has an associated site reliability engineer or site reliability engineering team assigned to perform the at least one second IT remediation task, and wherein automatically executing the generated IT incident remediation task workflow on the at least one IT resource comprises: for each first IT remediation task, automatically invoking the associated automation tool to execute operations to perform the first IT remediation task and awaiting an automation response indicating completion of the first IT remediation task by the associated automation tool and for each second IT remediation task, automatically transmitting an electronic communication to a computing device associated with the site reliability engineer or site reliability engineering team and awaiting a responsive communication from the computing device indicating completion of the second IT remediation task by the site reliability engineer or site reliability engineering team.
Werth teaches the IT incident remediation task workflow comprises at least one first IT remediation task that has an associated automation tool assigned to perform the at least one first IT remediation task, and at least one second IT remediation task that has an associated site reliability engineer or site reliability engineering team assigned to perform the at least one second IT remediation task, and wherein automatically executing the generated IT incident remediation task workflow on the at least one IT resource comprises: for each first IT remediation task, automatically invoking the associated automation tool to execute operations to perform the first IT remediation task and awaiting an automation response indicating completion of the first IT remediation task by the associated automation tool and for each second IT remediation task, automatically transmitting an electronic communication to a computing device associated with the site reliability engineer or site reliability engineering team and awaiting a responsive communication from the computing device indicating completion of the second IT remediation task by the site reliability engineer or site reliability engineering team.
It would be obvious to one of ordinary skill in the art to include in the task management (system/method/apparatus) of Kumar t the IT incident remediation task workflow comprises at least one first IT remediation task that has an associated automation tool assigned to perform the at least one first IT remediation task, and at least one second IT remediation task that has an associated site reliability engineer or site reliability engineering team assigned to perform the at least one second IT remediation task, and wherein automatically executing the generated IT incident remediation task workflow on the at least one IT resource comprises: for each first IT remediation task, automatically invoking the associated automation tool to execute operations to perform the first IT remediation task and awaiting an automation response indicating completion of the first IT remediation task by the associated automation tool and for each second IT remediation task, automatically transmitting an electronic communication to a computing device associated with the site reliability engineer or site reliability engineering team and awaiting a responsive communication from the computing device indicating completion of the second IT remediation task by the site reliability engineer or site reliability engineering team as taught by Werth since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar and Werth teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Referring to Claim 20, Kumar in view of Werth in further view of Loving teaches a non-transitory computer-readable medium storing a set of instructions for wireless communication program product comprising a computer readable storage medium having a computer readable program. Claim 20 recites the same or similar limitations as those addressed above in claim 1, Claim 20 is therefore rejected for the same reasons as set forth above in claim 1.
Referring to Claim 22, see discussion of claim 20 above, while Kumar in view of Werth in further view of Loving teaches the non-transitory computer-readable medium storing a set of instructions for wireless communication program product above Claim 22 recites the same or similar limitations as those addressed above in claim 2, Claim 22 is therefore rejected for the same or similar limitations as set forth above in claim 2.
Referring to Claim 23, see discussion of claim 22 above, while Kumar in view of Werth in further view of Loving teaches the non-transitory computer-readable medium storing a set of instructions for wireless communication program product above Claim 23 recites the same or similar limitations as those addressed above in claim 3, Claim 23 is therefore rejected for the same or similar limitations as set forth above in claim 3.
Referring to Claim 24, Kumar in view of Werth in further view of Loving teaches an apparatus. Claim 24 recites the same or similar limitations as those addressed above in claim 1, Claim 24 is therefore rejected for the same reasons as set forth above in claim 1, except for the following noted exception, however,
A memory configured to store a plurality of incident solution pairs and a processor configured (see; par. [0030] of Kumar teaches a processor and memory).
Claim 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (U.S. Patent Publication 2023/0132465 A1) (hereafter Kumar) in view of Werth et al. (U.S. Patent Publication 2013/0103973 A1) (hereafter Werth) in further view of Loving et al. (U.S. Patent Publication 2020/0410386 A1) in further view of CAI et al. (U.S. Patent Publication 2019/0347282 A1) (hereafter Cai).
Referring to Claim 7, see discussion of claim 1 above, while Werth in view of Kumar in further view of Loving teaches the method above, Werth in view of Kumar in further view of Loving does not explicitly disclose a method having the limitations of, however,
Cai teaches the IT topology graph data structure comprises nodes corresponding to IT resources and edges representing dependencies between IT resources, and wherein the retrieving the at least one IT topology graph comprises identifying the at least one IT resource by evaluating dependencies between IT resources associated with an IT resource corresponding to the IT incident notification based on the IT topology graph data structure (see; par. [0036] of Cai teaches retrieving a knowledge data structure that provides a the topology related to an IT incident, where the graph provides edges and nodes that provide the technology resource and the dependencies of the IT intendent).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Loving teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth and Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Cai teaches technology incident management platform and as it is comparable in certain respects to Kumar, Werth, and Loving which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar, Werth, and Loving discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar, Werth, and Loving fails to disclose the IT topology graph data structure comprises nodes corresponding to IT resources and edges representing dependencies between IT resources, and wherein the retrieving the at least one IT topology graph comprises identifying the at least one IT resource by evaluating dependencies between IT resources associated with an IT resource corresponding to the IT incident notification based on the IT topology graph data structure.
Cai teaches the IT topology graph data structure comprises nodes corresponding to IT resources and edges representing dependencies between IT resources, and wherein the retrieving the at least one IT topology graph comprises identifying the at least one IT resource by evaluating dependencies between IT resources associated with an IT resource corresponding to the IT incident notification based on the IT topology graph data structure.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kumar, Werth, and Loving the IT topology graph data structure comprises nodes corresponding to IT resources and edges representing dependencies between IT resources, and wherein the retrieving the at least one IT topology graph comprises identifying the at least one IT resource by evaluating dependencies between IT resources associated with an IT resource corresponding to the IT incident notification based on the IT topology graph data structure as taught by Cai since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar, Werth, Loving and Cai teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Claims 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over (U.S. Patent Publication 2023/0132465 A1) (hereafter Kumar) in view of Werth et al. (U.S. Patent Publication 2013/0103973 A1) (hereafter Werth) in further view of Loving et al. (U.S. Patent Publication 2020/0410386 A1) in further view of Hadar et al. (U.S. Patent Publication 2020/0177617 A1) (hereafter Hadar).
Referring to Claim 13, see discussion of claim 1 above, while Werth in view of Kumar in further view of Loving teaches the method above, Werth in view of Kumar in further view of Loving does not explicitly disclose the following limitations of, however,
Hadar teaches identifying one or more skills in a plurality of predetermined skills that are associated with the one or more IT remediation tasks comprises: identifying a subset of nodes in the IT remediation tasks knowledge graph data structure that correspond to the IT incident specified in the IT incident notification (see; par. [0050] of Hadar teaches identifying critical nodes to identify those that are based on remediation options to incidents), and
identifying the one or more skills based on characteristics of the subset of nodes in the IT remediation tasks knowledge graph data structure (see; par. [0046] of Hadar teaches one the IT threat has been determined provide possible impacts of remediation options (i.e. skills)).
The Examiner notes that Kumar teaches similar to the instant application teaches automated skill discovery, skill level computation, and intelligent matching using generated hierarchical skill paths. Specifically, Kumar discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks accordingly and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Werth teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Loving teaches providing hierarchy of support services via desktop and centralized service and as it is comparable in certain respects to Werth and Kumar which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Hadar teaches generating attack graphs in agile security platforms to mitigate a cyber security risk as a function of IT operations and as it is comparable in certain respects to Kumar, Werth and Loving which providing hierarchy of support services via desktop and centralized service as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kumar, Werth and Loving discloses matching skill that remediate an issue and tickets indicating incidents and assigning tasks. However, Kumar, Werth and Loving fails to disclose identifying one or more skills in a plurality of predetermined skills that are associated with the one or more IT remediation tasks comprises: identifying a subset of nodes in the IT remediation tasks knowledge graph data structure that correspond to the IT incident specified in the IT incident notification, and identifying the one or more skills based on characteristics of the subset of nodes in the IT remediation tasks knowledge graph data structure.
Hadar teaches identifying one or more skills in a plurality of predetermined skills that are associated with the one or more IT remediation tasks comprises: identifying a subset of nodes in the IT remediation tasks knowledge graph data structure that correspond to the IT incident specified in the IT incident notification, and identifying the one or more skills based on characteristics of the subset of nodes in the IT remediation tasks knowledge graph data structure.
It would be obvious to one of ordinary skill in the art to include in the task management (system/method/apparatus) of Kumar, Werth and Loving identifying one or more skills in a plurality of predetermined skills that are associated with the one or more IT remediation tasks comprises: identifying a subset of nodes in the IT remediation tasks knowledge graph data structure that correspond to the IT incident specified in the IT incident notification, and identifying the one or more skills based on characteristics of the subset of nodes in the IT remediation tasks knowledge graph data structure as taught by Hadar since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kumar, Werth, Spire and Cai teach the collecting and analysis of data in order to determine how manage incident remediation workflows and they do not contradict or diminish the other alone or when combined.
Conclusion
The prior art made of record and not relied upon considered pertinent to Applicant’s disclosure.
Chiverton et al. (U.S. Patent Publication 2008/0091498 A1) discloses a method of optimizing a workforce through the identification and segmentation of resources and job tasks.
Shrestha et al (U.S. Patent Publication 2022/0383229 A1) discloses a system for data center remediation scheduling.
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/SSS/
Patent Examiner, Art Unit 3623
/RUTAO WU/Supervisory Patent Examiner, Art Unit 3623