DETAILED ACTION
This Office Action is in response to claims filed on 11/12/2025.
Claims 1-20 are pending.
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 .
Response to Arguments
Applicant’s arguments, see page 1 of applicant's remarks, filed 11/12/2025, with respect to claim objections of 7 and 14 have been fully considered and are persuasive. The objection of 06/18/2025 has been withdrawn.
Applicant's arguments filed 11/12/2025 have been fully considered but they are not persuasive. Applicant argues in substance:
Applicant respectfully asserts that the pending claims recite limitations that cannot practically be performed in the human mind, and, as such, do not recite a mental process (as alleged by the Office). As an initial matter, independent claim 1 includes several recited actions that’s are performed by a processor executing instructions. Further, the recited actions performed by a processor executing instruction include features that cannot practically be performed in the human mind, including the processor-implemented creation, segmenting, determining, and transmitting. . . recommendations to a provisioning system.
With respect to point (a), Examiner respectfully disagrees. Applicant sets forth that the claims cannot practically be performed in the human mind. In particular Applicant sets forth that the claims explicitly necessitate the use of computing components (e.g., a non-transitory storage medium and a processor to receive and execute instructions) to perform the alleged judicial exception, and therefore the claims do not recite a mental process. However, MPEP § 2106.04(a)(2)(III) states “Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental process performed on a computer. As the Federal Circuit has explained “[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind.” Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be “performed by humans without a computer”)”. That is, even though the instant claims recite limitations as being performed by a computing apparatus, if the underlying limitation can be performed mentally or with pen and paper, the use of generic computing components does not limit the claim from being performed by a human, mentally or with a physical aid.
Argument has not been found to be persuasive.
In particular, the pending claims recite “improvements to the function of a computer or to any other technology or technological field,” where the “any technology or technological field” is the field hardware and software provisioning. That is, the claims do not broadly cover all hardware or software provisioning but, rather, are directed to specific improvements that involve, for example, determining an optimal computing device and optimal software based on a profile and transmitting those recommendations to a provisioning system. As noted in paragraph [0006] of the present application, the disclosed techniques improve current issues with the one-size fits all approach where the computing device for a new employee, for example, does not match the specific job role and does not have the appropriate tools for the job installed. This ameliorates the issue of new employees having to identify the required software and install it themselves or with the help of colleagues or tech support.
With regard to point (b), Applicant, in substance, argues that even if the pending claims are directed to the purported abstract idea, the subject matter of the claims are integrated into a practical application such that is eligible under 35 U.S.C. § 101. Examiner respectfully disagrees.
To integrate an abstract idea into a practical application, the claims must apply or use the abstract idea in a manner that imposes a meaningful limit on the claim scope, such that the claims reflect a technological solution to a technological problem (see MPEP § 2106.05(f)). When view as a whole, the claims merely perform an abstract idea using generic computing components as tools to apply the abstract idea. The claims further recite additional elements of generic computing functionality at a high level of abstraction, without specifying any technical implementation that meaningfully limits the claim scope.
Specifically, the limitations of claim 1 reciting “create a knowledge base based in part of the usage data”, “determine an optimal computing device recommendation based on the profile”, and “determine an optimal software application recommendation based on the profile” do not recite any technical implementation that would exclude a reasonable interpretation encompassing mere observation, evaluation, judgement and opinion, of all which can be practically performed in the human mind. The limitations, along with the additional elements, are recited at a high level of abstraction and are not tied to any particular machine, data structure, or any non-conventional processing technique.
Argument has not been found to be persuasive.
Furthermore, evening assuming for the pure sake of argument that the pending claims are directed to an abstract idea as alleged by the Office without integrating into a practical application, the pending claims recite “significantly more” than a mere abstract idea. For example, as noted above, the claims are directed to an improvement in computer-related technology, which supports a finding of “significantly more” under Step 2B of the Alice inquiry (see, e.g., November Memo, pp. 2-3, discussing indications that a claim is directed to an improvement in computer-related technology, which render a claim eligible for patent protection).
With regard to point (b) and (c), Applicant further recites paragraph [0006] of the instant specification as evidence for support of both integration into practical application and significantly more than the abstract idea. However, while paragraph [0006] describes the perceived problem and advantages over the prior systems, the claims as drafted do not recite how such improvement is achieved. Even if the subject matter described in paragraph [0006] were explicitly incorporated into the claims, the claim would remain ineligible because paragraph [0006] merely describes the result, solution, or outcome from application of the judicial exception with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result is described (see MPEP § 2106.05(f)(1)).
Accordingly, for the reasons set forth above, the pending claims are direct to a judicial exception and are not integrated practical application or are significantly more than the judicial exception, and therefore remain ineligible under 35 U.S.C. § 101. Please see the detailed analysis in the rejection below regarding full subject matter eligibility of the amended independent and dependent claims.
Argument has not been found to be persuasive.
As illustrated above, Morita determines an optimal time for a device to be replace or repaired. Morita simply provides a recommendation for when a current device should be replaced. Instead of providing a recommended computing device, Morita simply provides timing for repairing or replacing a computer. Morita does not determine a recommendation of an optimal computing device.
Further, the Office Action alleges that determining an optimal software application recommendation is disclosed in paragraphs [0077], [0083]-[0084] of Morita. However, paragraph [0077] merely discloses collecting data from a user’s current device, for example, from a desk ticket. And paragraph [0083]-[0084] discuss how the current device health score is determined (e.g., from service desk ticket data, and diminishing a 100% score over time based on usage, events, etc.). This is fundamentally different from determining an optimal software recommendation. There is not type of recommendation in Morita. Instead, it evaluates the current software on a computer and gives a health score. Morita does not “determine an optimal software application recommendation.” Accordingly, Morita does not disclose this element of claim 1. Therefore, claim 1 is not anticipated by Morita.
With respect to point (d), Examiner respectfully disagrees. Under broadest reasonable interpretation in light of the instant specification, the recitation of an “optimal computing device” may be reasonably interpreted as a device that best satisfies one or more operational rules or criteria. Support for this interpretation may be found in paragraph [0021] in the instant specification reciting “Statistically speaking, the computing device selected may be equivalent to the mode in the set of computing devices associated with the profile. Another implementation may include a rules-based approach to determine the mode of a number of features consistent with the majority of computing devices in the profile.” Under this interpretation, Morita reasonably teaches this limitation.
In paragraphs [0077] and [0083]-[0084], Morita reasonably teaches collection and evaluation of a user’s device with respect to a plurality of sub-components including device data, performance data, age data, persona match score, and reported hardware and software issues. As such, Morita discloses applying weighting parameters to the data associated with the device in order to determine and generate a device refresh recommendation. That is, a device refresh recommendation that is generated based on such weighted data and criteria reasonably aligns with a recommendation of an optimal computing device, as the refreshed device is selected to fulfill the identified operational needs presented by the evaluation. The recommendation reflects that the refreshed device is best suited to fulfill the criteria associated with the user.
The rationale set forth above with respect to claim 1 applies equally to dependent claims 2-10.
Argument has not been found to be persuasive.
Without acquiescing to the propriety of the rejection, and only to advance prosecution, claim 11 is amended. Amended claim 11 recites, “determine a percentage likeness of the user software application usage to one of the two software application profiles, based on the comparison; and transmit a job profile recommendation comprising the percentage likeness of the user software application to the third-party system, based on the comparison.”
Morita and Korzunov, individually or in combination, fail to teach or suggest the elements of amended claim 11. For example, neither Morita nor Korzunov determine a percentage likeness of the user software application usage to one of the two software application profiles. Accordingly, the combination fails to teach or suggest each and every element of amended claim 11.
With respect to point (e), Examiner respectfully disagrees. The amendment does not add subject matter that distinguishes over the applied prior art. Specifically, Korzunov reasonably teaches the limitations in figure 3 and paragraphs [0068]-[0070] in the specification. The reference discloses that a profile module determines a particular user’s application usage information which involves statistical analysis of the usage. This use profile may then be matched with one or more application profiles involving the comparison of the user’s usage to the best matching application profile which would involve comparison with an affinity metric to the user’s application usage profile. Under the broadest reasonable interpretation, the reference discloses the deployment of an application for a user with respect to a user profile which reasonably meets the newly amended limitation.
Accordingly, the prior art continues to teach the amended limitation and the rejection is maintained. Argument has not been found to be persuasive.
Applicant’s arguments with respect to claims 16-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception, is directed to that judicial exception, an abstract idea, as it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided by the 2019 Patent Eligibility guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Step 1: Claims 1-5 are directed to systems and fall within the statutory category of machines; Claims 6-10 are directed to methods and fall within the statutory category of processes; and Claims 11-15 are directed to non-transitory computer readable mediums and fall within the statutory category of articles of manufacture. Therefore, “Are the claims to a process, machine, manufacture, or composition of matter?” Yes.
In order to evaluate the Step 2A inquiry “Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?” we must determine, at Step 2A Prong 1, whether the claim recites a law of nature, a natural phenomenon or an abstract idea and further whether the claim recites additional elements that integrate the judicial exception into a practical application.
Step 2A Prong 1:
Claim 1: The limitation of “create a knowledge base based on a profile,” as drafted, is a process that, but for the recitation of the generic computing components, under its broadest reasonable interpretation, covers performance of the limitation of the mind. For example, a person can mentally observe structured and unstructured data, evaluate qualities or attributes of the data, and make judgements about how to organize the data, with or without the use of pencil and paper, according to a mental framework or predefined ontology.
Further, the limitation of “determine an optimal computing device recommendation based on the profile,” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation of the mind. For example, “determine” in the context of this claim broadly encompasses a person observing qualities or attributes of relevant input, such as metrics, signals, or conditions, and mentally evaluate, with or without the use of pencil paper, using such attributes to identify an optimal selection from a set of possible selections.
Further still, the limitation of “determine an optimal software application recommendation based on the profile,” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation of the mind. For example, “determine” in the context of this claim is used in a manner substantially similar to its use in the limitation recited above and therefore the same mental reasoning is applied here.
Therefore, Yes, claim 1 recites judicial exceptions.
The claims have been identified to recite judicial exceptions, Step 2A Prong 2 will evaluate whether the claims are directed to the judicial exception.
Step 2A Prong 2:
Claim 1: The judicial exception is not integrated into practical application. In particular, the claims recite the following additional elements – “a non-transitory computer readable storage medium” and “a processor to retrieve and execute instructions on the storage medium” which are merely recitations of generic computing components or other machinery merely as tools apply the abstract idea (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Further, the claims recite the following additional elements – “segment the knowledge base based on a profile” which is recitation of mere instructions to apply the abstract idea (see MPEP § 2106.05(f)). Therefore, the “segment” function is cited at such a high level of generality that these additional elements do not integrate a judicial exception into practical application. Moreover, the claims recite the following additional elements – “receive user usage data from telemetry agent” and “transmit the optional computing device recommendation and the optimal software application recommendation to a provisioning system” which is recitation of insignificant extra-solution activity amounting to mere data gathering and outputting (see MPEP § 2106.05(g)). This element will be further analyzed below at step 2B with regard to being Well-Understood, Routine, and Conventional.
Therefore, “Do the claims recite additional elements that integrate the judicial exception into practical application?” No, these additional elements do not integrate the abstract idea into practical application and they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
After having evaluated the inquires set forth in Step 2A Prong 1 and 2, it has concluded that claim 1 not only recite a judicial exception but the claim is directed to the judicial exception has not been integrated into practical application.
Step 2B:
Claim 1: The claims do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than generic computing components or other machinery as tools to apply the abstract idea and no more than mere instructions to apply the abstract idea which do not amount to significantly more than the abstract idea. Moreover, the recitation of insignificant pre-solution data gathering activity is also Well-Understood, Routine, and Conventional. See MPEP § 2106.05 (d)(I) “2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity.” The evidentiary requirement referenced here is found in MPEP § 2106.07 (a)(III) “(B) A citation to one or more of the court decisions discussed in MPEP § 2106.05 (d), subsection II, as noting the well-understood, routine, and conventional nature of the additional element(s).” See MPEP § 2106.05(d)(II) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g. at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data.” That is, in the instant claims these limitations merely receive data which is Well-Understood, Routine, and Conventional.
Therefore, “Do the claims recite additional elements that amount to significantly more than the judicial exception?” No, these additional elements, alone o combination, do not amount to significantly more than the judicial exception.
Having concluded analysis within the provided framework, Claim 1 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 2, it recites additional elements of “wherein the profile corresponds to a job family” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 2 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 2 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 2 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 3, it recites additional elements of “wherein the optimal software application recommendation corresponds to a set of software applications commonly used by the job family” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 3 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 3 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 3 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 4, it recites additional elements of “the instructions to segment comprise instructions to group the job family from the knowledge base exclusive of a user node” which is recitation of mere instructions to apply the abstract idea (see MPEP § 2106.05(f)). Therefore, the “group” function is cited at such a high level of generality that these additional elements do not integrate a judicial exception into practical application. Claim 4 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 4 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 4 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 5, it recites additional elements of “wherein the usage data corresponds to a software usage pattern of a user” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 5 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 5 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 5 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 6, the above analysis is incorporate herein by substantial similarity to claim 1 as it applies equally to claim 6 except that in claim 6 recites additional abstract ideas and elements not included in claim 1: “creating a profile based on the correlation,” as drafted, is a process that, but for that recitation of generic computing components, under the broadest reasonable interpretation, covers a performance of the limitation in the mind. For example, a person can mentally observe behaviors, characteristics, or attributes of a person or organization and mentally associate such behavior or attributes to an identified pattern, thereby establishing a profile. Further, the claim recites additional elements of “receiving a job family from a third-party system” which is recitation of insignificant extra-solution activity amounting to mere data gathering (see MPEP § 2106.05(g)) and is also Well-Understood, Routine, and Conventional. See MPEP § 2106.05 (d)(I) “2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity.” The evidentiary requirement referenced here is found in MPEP § 2106.07 (a)(III) “(B) A citation to one or more of the court decisions discussed in MPEP § 2106.05 (d), subsection II, as noting the well-understood, routine, and conventional nature of the additional element(s).” See MPEP § 2106.05(d)(II) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g. at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data.” That is, in the instant claims these limitations merely receive and transmit data, respectively, which is Well-Understood, Routine, and Conventional. Further still, the claim recites additional elements of “correlating the usage data, the job family, and a user based on the knowledge base” which is recitation of mere instructions to apply the abstract idea (see MPEP § 2106.05(f)). Therefore, the “correlating” function is cited at such a high level of generality that these additional elements do not integrate a judicial exception into practical application. Claim 6 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 6 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 6 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 7, the above analysis is incorporated herein by substantial similarity to claim 2 as it applies equally to claim 7. Claim 7 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 7 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 7 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 8, the above analysis is incorporated herein by substantial similarity to claim 3 as it applies equally to claim 8. Claim 8 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 8 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 8 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 9, the above analysis is incorporated herein by substantial similarity to claim 4 as it applies equally to claim 9. Claim 9 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 9 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 9 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 10, the above analysis of claim is incorporated herein by substantial similarity to claim 5 as it applies equally to claim 10. Claim 10 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 10 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 10 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 11, it recites additional abstract idea recitation of “compare the user software application usage data to the first software application profile and the second application profile,” and “determine a percentage likeness of the user software application usage to one of the two software application profiles, based on the comparison,” as drafted, are processes that, but for that recitation of generic computing components, under the broadest reasonable interpretation, covers a performance of the limitation in the mind. For example, “compare” in the context of the claim broadly encompasses a person mentally observing data and mentally evaluating such data with known, identified patterns to inform a mental decision. Further, for example, “determine” in the context of this claim broadly encompasses a person observing qualities or attributes of relevant input, such as metrics, signals, or conditions, and mentally evaluate, with or without the use of pencil paper, using such attributes to perform an evaluation. Further the claim recites additional elements of “extract a first software application profile from a knowledge base, where the first software application profile corresponds to the first profile job” and “extract a second software application profile from the knowledge base, wherein the second application profile corresponds to the second job profile” which are recitations of mere instructions to apply the abstract idea (see MPEP § 2106.05(f)). Therefore, the “extract” function is cited at such a high level of generality that these additional elements do not integrate a judicial exception into practical application. Further still, the claim recites additional elements of “receive user software application usage data from telemetry agent,” “receive a first job profile and a second job profile from a third-party system,” and “transmit a job profile recommendation comprising the percentage likeness of the user software application to the third-party system, based on the comparison” which are recitations of insignificant extra-solution activity amounting to mere data gathering and outputting (see MPEP § 2106.05(g)) and is also Well-Understood, Routine, and Conventional. See MPEP § 2106.05 (d)(I) “2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity.” The evidentiary requirement referenced here is found in MPEP § 2106.07 (a)(III) “(B) A citation to one or more of the court decisions discussed in MPEP § 2106.05 (d), subsection II, as noting the well-understood, routine, and conventional nature of the additional element(s).” See MPEP § 2106.05(d)(II) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g. at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data.” That is, in the instant claims these limitations merely receive and transmit data, respectively, which is Well-Understood, Routine, and Conventional. Claim 11 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 11 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 11 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 12, it recites additional elements of “wherein the job profile recommendation corresponds to a promotion” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 12 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 12 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 12 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 13, it recites additional elements of “wherein the user software application usage data corresponds to a set of software applications utilized by a user and a duration the use executes each of the set of software applications” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 13 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 13 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 13 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 14, it recites additional elements of “wherein the first software application profile comprises a first set of common application utilized in the first job profile” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 14 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 14 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 14 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 15, the above analysis is incorporated herein by substantial similarity to claim 14 as it applies equally to claim 15. Claim 15 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 15 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 15 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 16, it recites additional elements of “wherein the processor receives hardware information of a computing device from the telemetry agent” which are recitations of insignificant extra-solution activity amounting to mere data gathering (see MPEP § 2106.05(g)) and is also Well-Understood, Routine, and Conventional. See MPEP § 2106.05 (d)(I) “2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity.” The evidentiary requirement referenced here is found in MPEP § 2106.07 (a)(III) “(B) A citation to one or more of the court decisions discussed in MPEP § 2106.05 (d), subsection II, as noting the well-understood, routine, and conventional nature of the additional element(s).” See MPEP § 2106.05(d)(II) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g. at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data.” That is, in the instant claims these limitations merely receive data which is Well-Understood, Routine, and Conventional. Further, the claim recites additional element of “the hardware information comprising a processor model, installed memory, graphics adapter, display resolution and type, peripherals, and network connection” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 16 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 16 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 16 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 17, it recites additional elements of “comprising information about the operating system, applications installed, and applications used including frequency and duration” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 17 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 17 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 17 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 18, it recites additional elements of “wherein the knowledge base corresponds to a defined ontology utilized to store complex structured and unstructured information” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 18 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 18 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 18 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 19, it recites additional elements of “wherein the optimal computing device is a statistical mode in a set of computing devices associated with the profile or a mode of a number of features consistent with a majority of computing devices in the profile” which is merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 19 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 19 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 19 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regard to claim 20, it recites additional elements of “wherein the optimal computing device recommendation comprises a primary and secondary computing device recommendation” and “the primary computing device recommendation is different from the secondary computing device recommendation” which are merely recitation of field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Claim 20 does not recite any additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 20 fails both Step 2A prong 2, thus the claim is directed to a judicial exception as it has not been integrated into practical application and fails Step 2B as not amounting to significantly more. Therefore, Claim 20 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 20 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The following language is unclear:
With regard to claim 20, lines 1-2, recites “wherein the optimal computing device recommendation comprises a primary and secondary computing device recommendation.” It is unclear from the context of the claim to ascertain if the first and secondary computing device recommendations correspond to recommendations generated for two distinct recommendations or alternative recommendations of a single recommendation request. For purposes of examination, the examiner will reasonably interpret the limitation as two distinct recommendations for separate devices.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 5, and 16-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Morita et al. Pub. No. US 2019/0138964 A1 (hereinafter Morita).
With regard to claim 1, Morita teaches a system comprising ([0028], The present invention may be a system):
a non-transitory computer readable storage medium ([0028], and/or a computer program product at any possible technical detail of integration);
a processor to retrieve and execute instructions on the storage medium, the instructions to ([0028], The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention):
receive user usage data from telemetry agent ([0075], Still referring to FIG. 4, the device monitoring server 122 may comprise one or more servers that collect and store structured monitoring data about each user device 110a-n. For example, the device monitoring severs 122 may comprise a server running SysTrack® software, or similar monitoring software, that collects data related to application usage, application performance, application faults, application latency, resource utilization, …, etc.);
create a knowledge base based on a profile; ([0079], According to aspects of the invention, the refresh server 105 is configured to utilize a cognitive computing system 130 (knowledge base) to analyze the unstructured data obtained from the at least one unstructured data source 119. In embodiments, the cognitive computing system 130 comprises one or more servers that are programmed to apply at least one of natural language understanding (NLU), semantic text analysis, and machine learning techniques to analyze the unstructured data to extract meaning from the unstructured data)
segment the knowledge base based on a profile; ([0089], Still referring to FIG. 5, in accordance with aspects of the invention, the refresh server 105 determines the device health score 525 in the manner described herein, e.g., by obtaining unstructured data and unstructured data, classifying the unstructured data, normalizing each component of the structured and the classified unstructured data, and using a scoring function to determine the device health score based on the normalized data. As described herein, the scoring function may take into account user-defined weightings of the data and/or profile inputs that define, for example, a device role for the device and a persona role for a user of the device. For example, the scoring function may include priority data such as a device role parameter and a persona role parameter, and values for these parameters may be defined by the admin for each of the user devices 110a-n)
determine an optimal computing device recommendation based on the profile; ([0017], The present invention generally relates to computer device management and, more particularly, to determining optimal device refresh cycles and device repairs through cognitive analysis of unstructured data and device health scores … In embodiments, a system is configured to determine an optimal time to refresh (e.g., replace) a computer device, which may be ahead or behind the traditional time-based lifecycle replacement date. In this manner, implementations of the invention provide a novel approach to determining a device refresh recommendation)
determine an optimal software application recommendation based on the profile ([0077, [0083], [0084], In embodiments, the business layer 145 is configured such that each user device 110a-c starts with a device health score of 100%, and this device health score diminishes over time with usage, events, etc. Moreover, the business layer 14 is configured to: provide recommendation of when to initiate device refreshes; utilize predictive analytics to device those device most likely to experience failure based on hardware characteristics where data is available; utilize predictive analysis to identify those device most likely to experience issues with software failures where a new device would resolve; avoid disruption to critical business functions (when data is available); identify those devices that have security gaps and issues and should be replaced (e.g., tied to operating systems and inability to upgrade, etc.); and identify those devices that have compliance gaps and issues (e.g., lack of encryption on device due to age, OS, etc.));
transmit the optimal computing device recommendation and the optimal software application recommendation to a provisioning system ([0087], According to aspects of the invention, the refresh server 105 provides data to the admin device 115 in the form of user interfaces, such as those shown in FIGS. 5 and 6, which are described in greater detail herein. The refresh server 105 may be configured to generate a user interface that displays details associated with a single one of the use device 110a-n and its determined device health score, e.g., as depicted in FIG. 5. The refresh server 105 may be configured to generate a user interface that simultaneously displays plural determined device health scores for plural device 110a-n, e.g., as depicted in FIG. 6).
With regard to claim 5, Morita teaches the system of claim 1 wherein the usage data corresponds to a software usage pattern of a user ([0075], the device monitoring server 122 may comprises one or more servers that collect and store structured monitoring data about each user device 110a-n … that collects data related to application usage).
With regard to claim 16, Morita teaches wherein the processor receives hardware information of a computing device from the telemetry agent ([0098], As shown in FIG. 7, at step 705 the refresh server 106 extracts service desk data. This step may comprise, for example, obtaining unstructured data from the unstructured data source 119 as described with respect to FIG. 4. In embodiments, this step includes extract hardware … related ticket data), the hardware information comprising a processor model, installed memory, graphics adapter, display resolution and type peripherals, and network connection ([0075], the device monitoring server 122 may comprise one or more servers that collect and store structured monitoring data … that collects data related to … average memory usage, average CPU usage, hours powered on, CPU utilization, memory utilization, network bandwidth per application; [0077], hardware issues (e.g., general device issues, battery issues, memory issues, keypad issues) … and non-device issues (e.g., accessory issues, etc.)).
With regard to claim 17, Morita teaches wherein the processor receives software information of the computing device from the telemetry agent agent ([0098], As shown in FIG. 7, at step 705 the refresh server 106 extracts service desk data. This step may comprise, for example, obtaining unstructured data from the unstructured data source 119 as described with respect to FIG. 4. In embodiments, this step includes extract … software related ticket data), comprising information about the operating system, applications installed, and applications used including frequency and duration ([0075], the device monitoring server 122 may comprise one or more servers that collect and store structured monitoring data … that collects data related to application usage, application performance, application faults … errors logged in in the operating system, power average, time since the specified system’s installation, clock speed, memory type, OS install date; [0077], software issues (e.g., operating system, business applications, communication applications, etc.)).
With regard to claim 18, Morita teaches wherein the knowledge base corresponds to a defined ontology utilized to store complex structured and unstructured information ([0020], In embodiments, the scoring function is based on parameters that correspond to categories of structured data that is obtained from at least one structured data source. In embodiments, the refresh system also obtains unstructured data from at least one unstructured data source, and analyzes the unstructured data using cognitive computing techniques to classify the unstructured data into one or more of the categories of the scoring function.).
With regard to claim 19, Morita teaches wherein the optimal computing device is a statistical mode in a set of computing devices associated with the profile or a mode of number of features consistent with a majority of computing devices in the profile ([0083], The components and/or sub-components may correspond to parameters of the scoring function as described herein. In embodiments, a weighting may be configured for each component, and this weighting is utilized by the scoring function into the calculation of the sub-component and overall device health score. The device health scores for plural user devices 110a-n are then used in conjunction with logical sorting and processing of devices under management to provide a recommendation and prioritized list devices to be refreshed).
With regard to claim 20, Morita teaches wherein the optimal computing device recommendation comprises a primary and secondary computing device recommendation, and the primary computing device recommendation is different from the secondary computing device recommendation ([0115],The method may further comprise ranking the hardware device and a second hardware device based on the overall health of the hardware device and an overall health of a second hardware device, and providing a recommendation for the hardware device and the second hardware device based on the ranking).
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 for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 2, 4, 6, 7, 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Morita in view of April et al. Pub. No. US 2011/0015958 A1 (hereinafter April).
With regard to claim 2, Morita does not explicitly teach that a profile corresponds to a job family.
April teaches the system of claim 1 wherein the profile corresponds to a job family ([0057], A forecast of talent requirements given likely business scenarios may be defined, translating business plans into a specific workforce profile or staffing plan – number of positions, types of skills, timing, location, etc. – and identifying those factors that could change the required profile so that contingency plans can be developed; [0078], Attributes associated with each employee may include their level within the organization, which may be defined generically for the entire organization or by defined career paths by job family).
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of April with the teachings of Morita in order to provide a system that teaches a profile corresponding to a job family. The motivation for applying April teaching with Morita teaching is to provide a system that allows for role-based policies and business plans to be implemented tailored to a user’s occupation in an organization thereby enabling predictive workforce planning (April, [0078]-[0079]). Morita and April are analogous art directed towards resource planning. Therefore, it would have been obvious for one of ordinary skill in the art to combine April with Morita to teach the claimed invention in order to provide relevant policies by incorporating defined, role-based patterns.
With regard to claim 4, Morita teaches the system of claim 2, the instructions to segment comprise instructions to group … from the knowledge base ([0089], Still referring to FIG. 5, in accordance with aspects of the invention, the refresh server 105 determines the device health score 525 in the manner described herein, e.g., by obtaining structured data and unstructured data, classifying the unstructured data, normalizing each component of the structured and the classified unstructured data, and using a scoring function to determine the device health score based on the normalized data)
Morita teaches the instructions to segment comprising instructions to group data from the knowledge base. However, Morita does not explicitly teach the grouped data from the knowledge base comprise the job family exclusive of user node data.
April teaches the job family … exclusive of a user node ([0059], In some embodiments, a workforce requirement module may define specific job requirements (e.g., knowledge/skills/abilities, education and experience, certifications). The requirements may be taken from existing job descriptions or job postings. FIG. 4 illustrates an example table 400 of workforce requirements for an engineering services company, although this may take a variety of forms in other embodiments; [0060], Column 1 410 includes the different job categories (i.e., job families, job types, roles, etc.) to be included in the workforce planning simulation … The number and type of requirements may depend on each organization, and various combinations may be accommodated).
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of April with the teachings of Morita in order to provide a system that teaches instructions to segment knowledge base exclusive of a user node comprises instructions to group the job family. The motivation for applying April teaching with Morita teaching is to provide a system that allows for role-based segmentation of knowledge, enabling the system to organize and retrieve data relevant to a particular job family (April, FIG. 4 and [0059]). Morita and April are analogous art directed towards resource planning. Therefore, it would have been obvious for one of ordinary skill in the art to combine April with Morita to teach the claimed invention in order to provide a system with the capabilities to structure data in accordance to occupational roles enabling the creation of job family specific policies.
With regard to claim 6, Morita teaches a method comprising ([0028], The present invention may be …, a method):
receiving user usage data from a telemetry agent ([0075], Still referring to FIG. 4, the device monitoring server 122 may comprise one or more servers that collect and store structured monitoring data about each user device 110a-n. For example, the device monitoring severs 122 may comprise a server running SysTrack® software, or similar monitoring software, that collects data related to application usage, application performance, application faults, application latency, resource utilization, …, etc.);
…
creating a knowledge base based in part of the usage data ([0107], At step 815, the refresh system obtains unstructured data about the at least one computer device. In embodiments, step 815 comprises the refresh server 105 obtaining unstructured data about the user devices 110a-n from the at least one unstructured data source 119, e.g., as described with respect to FIG. 4) …;
correlating the usage data, …, and a user based on the knowledge base ([0109], At step 825, the refresh system normalizes and correlates the data. In embodiments, the refresh serves 105 normalizes each data item obtained at steps 805, 810, and 820, e.g., by assigning a 0-100 score to the data item, e.g., as described with respect to FIG. 4. In embodiments, the refresh server 105 also correlates the data items obtained at steps 805, 810, and 820 into components (or parameters) of the scoring function that is used to determine the device health score of the user devices);
creating a profile based on the correlation ([0110], At step 830, the refresh system determines a device health score for the at least one computer device based on the normalized and correlated data from step 830. In embodiments, the refresh server 105 determines a respective device health score for each one of the user device 110a-n in the manner described with respect to FIG. 4);
determining an optimal computing device recommendation based on the profile ([0017], The present invention generally relates to computer device management and, more particularly, to determining optimal device refresh cycles and device repairs through cognitive analysis of unstructured data and device health scores … In embodiments, a system is configured to determine an optimal time to refresh (e.g., replace) a computer device, which may be ahead or behind the traditional time-based lifecycle replacement date. In this manner, implementations of the invention provide a novel approach to determining a device refresh recommendation);
determining an optimal software application recommendation based on the profile ([0077, [0083], [0084], In embodiments, the business layer 145 is configured such that each user device 110a-c starts with a device health score of 100%, and this device health score diminishes over time with usage, events, etc. Moreover, the business layer 14 is configured to: provide recommendation of when to initiate device refreshes; utilize predictive analytics to device those device most likely to experience failure based on hardware characteristics where data is available; utilize predictive analysis to identify those device most likely to experience issues with software failures where a new device would resolve; avoid disruption to critical business functions (when data is available); identify those devices that have security gaps and issues and should be replaced (e.g., tied to operating systems and inability to upgrade, etc.); and identify those devices that have compliance gaps and issues (e.g., lack of encryption on device due to age, OS, etc.)); and
transmitting the optimal computing device recommendation and the optimal software application recommendation to a provisioning system ([0087], According to aspects of the invention, the refresh server 105 provides data to the admin device 115 in the form of user interfaces, such as those shown in FIGS. 5 and 6, which are described in greater detail herein. The refresh server 105 may be configured to generate a user interface that displays details associated with a single one of the use device 110a-n and its determined device health score, e.g., as depicted in FIG. 5. The refresh server 105 may be configured to generate a user interface that simultaneously displays plural determined device health scores for plural device 110a-n, e.g., as depicted in FIG. 6).
Morita teaches a method for generating optimal computing device and software application recommendation to a provisioning system. However, Morita does not explicitly teach receiving job family data from a third-party system, creating a knowledge base based in part of using job family data or the correlation of such data.
April teaches receiving a job family from a third-party system ([0047], Workforce planning system 300 may include externalities module 325. Externalities module 325 may be configured to identify externalities such as economic factors that may have an impact on employee decision to remain with a company, practices an organization may adopt, and/or the ability of an organization to recruit new employees merely by way of example)
creating a knowledge base based in part of the … the job family ([0055], Tools and templates may be provided for data collection, external data to support model assumptions (Examiner notes: such model can include a knowledge base) (e.g., correlation between a specific practice and the corresponding retention rates based on demographics), recruiting channel effectives in recruiting employees with specific attributes (job family), guidance in determining relevant inputs to the model, and seasoned judgment in the formulation of components of the model which are more subjective, either by nature or due to the lack of historical data when the model is first developed; [0072], This model may be populated with available published data on common channels (e.g., universities, job sites, etc.), but parameters related to effectiveness and cost will vary by organization, so the model will be enhanced by historical company-specific data);
correlating … the job family ([0069], Some embodiments may determine the impact (correlation) of each practice on an employee’s behavior based on relevant employee attributes (job family) … Historical data, external benchmark data and anecdotal data, and informed judgment as to the expected impact of different practices on employees with specific attributes may be considered)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of April with the teachings of Morita in order to provide a method that teaches job family data contributing to the creation of a knowledge base and profiles associated. The motivation for applying April teaching with Morita teaching is to provide a method that allows for the enabling of simulations and optimization technologies to be used to manage human capital, thereby optimizing for the best allocation of resources to enable the achievement of specific goals (April, [0032]). Morita and April are analogous art directed towards resource planning. Therefore, it would have been obvious for one of ordinary skill in the art to combine April with Morita to teach the claimed invention in order to provide a method that enables predictive planning and optimization of resources based on job families.
With regard to claim 7, April teaches the method of claim 6 wherein the profile corresponds to a job family ([0057], A forecast of talent requirements given likely business scenarios may be defined, translating business plans into a specific workforce profile or staffing plan – number of positions, types of skills, timing, location, etc. – and identifying those factors that could change the required profile so that contingency plans can be developed; [0078], Attributes associated with each employee may include their level within the organization, which may be defined generically for the entire organization or by defined career paths by job family) which is substantially similar to claim 2, and therefore rejected with similar rationale.
Examiner notes: It would be obvious for one of ordinary skill in the art to recognize that claim 7 is being substantially recited again as a method for the system of claim 2.
With regard to claim 9, the method of claim 6, the creating further comprising grouping … from the knowledge base ([0110], At step 830, the refresh system determines a device health score for the at least one computer device based on the normalized and correlated data from step 830. In embodiments, the refresh server 105 determines a respective device health score for each one of the user device 110a-n in the manner described with respect to FIG. 4)
Morita teaches creating comprising grouping data from the knowledge base. However, Morita does not explicitly teach the grouped data from the knowledge base comprise the job family exclusive of user node data.
April teaches the job family … exclusive of a user node ([0059], In some embodiments, a workforce requirement module may define specific job requirements (e.g., knowledge/skills/abilities, education and experience, certifications). The requirements may be taken from existing job descriptions or job postings. FIG. 4 illustrates an example table 400 of workforce requirements for an engineering services company, although this may take a variety of forms in other embodiments; [0060], Column 1 410 includes the different job categories (i.e., job families, job types, roles, etc.) to be included in the workforce planning simulation … The number and type of requirements may depend on each organization, and various combinations may be accommodated) which is substantially similar to claim 4, and therefore rejected with similar rationale.
Examiner notes: It would be obvious for one of ordinary skill in the art to recognize that claim 9 is being substantially recited again as a method for the system of claim 4.
With regard to claim 10, Morita teaches the method of claim 6, wherein the usage data corresponds to a software usage pattern of a user ([0075], the device monitoring server 122 may comprises one or more servers that collect and store structured monitoring data about each user device 110a-n … that collects data related to application usage).
Claims 3 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Morita in view of April as applied to claim 2 and 6 above, respectively, and further in view of Cao et al. Pub. No. US 2016/0373377 A1 (hereinafter Cao).
With regard to claim 3, the combination does not explicitly teach the claim.
Cao teaches the system of claim 2 wherein the optimal software application recommendation corresponds to a set of software applications commonly used by the job family ([0052], For instance, activity by the use may be monitored/tracked/obtained across one or more cloud environments. As such, if the user is actively using a specific resource on a first virtual machine of a cluster but not on other virtual machines of the cluster, then aspects of the disclosure could use such asset activity data to make informed decisions (e.g., relative to looking at each virtual machine individually when installing an application). For example, a single developer/administrator (job families) could be monitored/tracked across a group of instances involved in a group of web applications (set of applications) to determine for new virtual machine ‘which applications are needed when.’ (commonly associated with the job families) Accordingly, a group of user may have different types of virtual machines with different software/licenses loaded in different orders (e.g., an accountant as compared with a programmer)).
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Cao with the teachings of Morita and April in order to provide a system that teaches an optimal software application recommendation corresponds to a set of software application used by the job family. The motivation for applying Cao teaching with Morita and April teaching is to provide a system that allows for recommendations that are optimal in both functionality and occupationally relevant providing performance benefits directed to speed, flexibility, responsiveness and resource usage (Cao, [0015]). Morita, April, and Cao are analogous art directed towards resource planning and allocation. Therefore, it would have been obvious for one of ordinary skill in the art to combine Cao with Morita and April to teach the claimed invention in order to provide optimal recommendations in accordance to a job family to achieve system efficiency improvements of proper deployments.
With regard to claim 8, Cao teaches the method of claim 6 wherein the optimal software application recommendation corresponds to a set of software applications commonly used by the job family ([0052], For instance, activity by the use may be monitored/tracked/obtained across one or more cloud environments. As such, if the user is actively using a specific resource on a first virtual machine of a cluster but not on other virtual machines of the cluster, then aspects of the disclosure could use such asset activity data to make informed decisions (e.g., relative to looking at each virtual machine individually when installing an application). For example, a single developer/administrator (job families) could be monitored/tracked across a group of instances involved in a group of web applications (set of applications) to determine for new virtual machine ‘which applications are needed when.’ (commonly associated with the job families) Accordingly, a group of user may have different types of virtual machines with different software/licenses loaded in different orders (e.g., an accountant as compared with a programmer)) which is substantially similar to claim 3, and therefore rejected with similar rationale.
Examiner notes: It would be obvious for one of ordinary skill in the art to recognize that claim 8 is being substantially recited again as a method for the system of claim 3.
Claims 11, 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over Morita et al. Pub. No. 2019/0138964 A1 (hereinafter Morita) in view of Korzunov Pub. No. US 2021/0191701 A1 (hereinafter Korzunov).
With regard to claim 11, Morita teaches a non-transitory computer readable medium comprising instructions executable by a processor to ([0028], The present invention may be … a computer program product … The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention):
receive user software application usage data from telemetry agent ([0075], Still referring to FIG. 4, the device monitoring server 122 may comprise one or more servers that collect and store structured monitoring data about each user device 110a-n. For example, the device monitoring severs 122 may comprise a server running SysTrack® software, or similar monitoring software, that collects data related to application usage, application performance, application faults, application latency, resource utilization, …, etc.);
However, Morita does not explicitly teach extraction of software application profiles corresponding to job profiles, comparing the usage data to the application profiles, and recommending a job profile to the third-party system.
Korzunov teaches receive a first job profile and a second job profile from a third-party system ([0062], In some embodiments, the monitoring system 106 is external to application system 102, Therefore, the deployment engine 108 may request and receive usage information about an application or user from an external source. In some cases, the application system 102 may supplement usage information about an application with externally provided usage information; [0085], A user profile categories one or more users by their usage information. That is, a user profile may be associated with a single user or multiple users where each of the multiple users have the same or similar usage information in at least one dimension or metric);
extract a first software application profile from a knowledge base, where the first software application profile corresponds to the first job profile ([0064], At step 310 the profile module creates an application profile. An application profile defines different ways of using the same application. The application profiles can be associated with user profiles are used to determine (as described below) one or more application deployments; [0089], In one example embodiment, the deployment module may determine a range of potential user profiles based on application profiles. The deployment engine can then select the user profile in the range of potential user profile that best matches a user; [0090], In this example, the potential user profiles are AP1, AP2, AP3. AP1 has an average CPU usage of 30% over the relevant period and has an average memory usage of 50% over the same period. AP2 has an average CPU usage of 15% over the relevant period and has an average memory usage of 20% over the same period)
extract a second software application profile from the knowledge base, wherein the second application profile corresponds to the second job profile ([0091], If a user were determined to have a user profile with an average CPU usage of 20% and an average memory average CPU usage of 20% and an average memory usage of 20%, then the deployment engine would determine which of the potential user profiles best match this specific usage. In this case, it is likely that AP2 would be the best match as it has similar CPU usage and memory usage characteristics);
compare the user software application usage data to the first software application profile and the second application profile ([0019], In some embodiments, the deployment engine is configured to assign/match a user to a particular application profile based on the user’s individual usage data, That is, the deployment engine receives user usage data or characteristics of user usage are analyzed to produce user usage data, and a determination made by the deployment engine as to which application profile matches the user usage data. The user usage data typically has similar usage patterns to at least one application profile. If not, the deployment engine can use a default application profile; [0069], The deployment engine 108 can then determine 328 an application profile of the software application. This may be based on matching one or more user profiles (or user usage information) to one or more application profiles and determining the best match. For example, each user profile may be associated with an application profile);
determine a percentage likeness of the user software application usage to one of the two software application profiles, based on the comparison (FIG. 3, 326 Determine a user profile based on user usage information, 328 Determine an application profile based on the user profile; [0068], At step 326, the profile module 110 determines a user profile based on the user usage information. A user profile is information about a user that indicates what use cases of an application the user utilizes. This may involve statistical analysis of the usage information to determine which use cases are used frequently or infrequently); and
transmit a job profile recommendation comprising the percentage likeness of the user software application ([0069], The deployment engine 108 can then determine 328 an application profile of the software application. This may be based on matching one or more user profiles (or user usage information) to one or more application profiles and determining the best match) to the third-party system, based on the comparison ([0070], Once the application profile 328 has been determined, the deployment engine 108 can deploy 330 the application for the user. Deployment as a general term refers to the activities that make software available for use by a given user. Given this, different versions of the application might be deployed into production (that is for public use) for different users).
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Korzunov with the teachings of Morita in order to provide a computer readable medium that teaches application profiles corresponding to job profiles, comparison to usage data, and recommendations based on the comparison. The motivation for applying Korzunov teaching with Morita teaching is to provide a non-transitory computer readable medium that allows for customization of application deployment associated with a particular profile (Korzunov [0005]), enabling the general benefits of improved resource efficiency and alignment (Korzunov, [0036]). Morita and Korzunov are analogous art directed towards monitoring arrangements of configurations and resource deployment. Therefore, it would have been obvious for one of ordinary skill in the art to combine Korzunov with Morita to teach the claimed invention in order to provide optimal deployments of tailored to users based on their usage patterns and job relevance.
With regard to claim 13, Morita teaches the computer readable medium of claim 11 wherein the user software application usage data corresponds to a set of software applications utilized by a user and a duration of the user executes each of the set of software applications ([0075], For example, the device monitoring server 122 may comprise a serve running SysTrack® software, or similar monitoring software, that collects data related to application usage, application performance, application faults, application latency, resource utilization, hard drive usage percent, number of hard drive errors, average memory usage (over a duration), average CPU usage (over a duration), hours powered on, CPU utilization, memory utilization, network bandwidth consumed per application, errors logged in the operating system, power average, time since the specified system’s installation, clock speed, memory type, OS install date, etc.).
With regard to claim 14, Korzunov teaches the computer readable medium of claim 11 wherein the first software application profile comprises a first set of common application utilized in the first job profile ([0089], In one example embodiment, the deployment module may determine a range of potential user profiles (job profiles) based on application profiles. The deployment engine can then select the user profile in the range of potential user profiles that best matches a user; [0090], In this example, the potential user profiles are AP1, AP2, AP3 (Application Profile ID, indicating plurality)… AP2 has an average CPU usage of 15% over the relevant period and has an average memory usage of 20% over the same period; [0091], If a user were determined to have a user profile with an average CPU usage of20% and an average memory usage of 20%, then the deployment engine would determine which of the potential user profiles best matches this specific usage. In this case, it is likely that AP2 would be the best match as it has similar usage and memory usage characteristics)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Kurzonov with the teachings of Morita in order to provide a computer readable medium that teaches software application profiles comprising applications utilized in a first job profile. The motivation for applying Kurzonov teaching with Morita teaching is to provide a computer readable medium that allows for improvement over monolithic deployment by enabling tailored deployments of applications in accordance to a user attribute, resulting in reduction of disk space and other computing resource utilization in monolithic deployment (Kurzonov, [0005]). Morita and Kurzonov are analogous art directed towards monitoring arrangements of configurations and resource deployment. Therefore, it would have been obvious for one of ordinary skill in the art to combine Kurzonov with Morita to teach the claimed invention in order to provide an efficient deployment method that enables user-specific provisioning of relevant applications.
With regard to claim 15, Korzunov teaches the computer readable medium of claim 14, wherein the second software application profile comprises a second set of common applications utilized in the second job profile ([0089], In one example embodiment, the deployment module may determine a range of potential user profiles (job profiles) based on application profiles. The deployment engine can then select the user profile in the range of potential user profiles that best matches a user; [0090], In this example, the potential user profiles are AP1, AP2, AP3 (Application Profile ID, indicating plurality). AP1 has an average CPU usage of 30% over the relevant period and has an average memory usage of 50% over the same period) which is substantially similar to claim 14, and therefore rejected with similar rationale.
Examiner notes: It would be obvious for one of ordinary skill in the art to recognize that claim 15 is being substantially recited again with a second software application profile utilized in a second job profile, as evidenced in Korzunov, [0090].
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Morita in view of Korzunov as applied to claim 11 above, and further in view of April et al. Pub. No. US 2011/0015958 (hereinafter April).
With regard to claim 12, the combination does not explicitly teach that the job profile recommendation corresponds to a promotion.
April teaches the computer readable medium of claim 11 wherein the job profile recommendation corresponds to a promotion ([0045], Workforce planning system 300 may include promotion and mobility module 320. Promotion and mobility module 320 may identify job descriptions that have not been assigned to at least one employee for one or more times periods; [0078], Some embodiments may consider how a workforce planning model may relate to the mobility of employees within the organization – promotions, job changes, location changes. Some embodiments may utilize a promotion and mobility module, such as promotion and mobility module 320 of system 300, as part of this process. Attributes associated with each employee may include their level within the organization which may be defined either generically for the entire organization or by defined career paths by job family. Using historic data on mobility, a probability table may be developed. This table may predict the likelihood that employees with various combinations of attributes will move within the organization during the planning timeframe).
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of April with the teachings of Morita and Koruznov in order to provide a computer readable medium that teaches job profile recommendations correspond to occupational promotion. The motivation for applying April teaching with Morita and Korzunov teaching is to provide a computer readable medium that allows for predictive planning of resources, aiding resource allocation decisions in an organization (April, [0087] and [0089]). Morita, Korzunov, and April are analogous art directed towards resource planning and allocation. Therefore, it would have been obvious for one of ordinary skill in the art to combine April with Morita and Koruznov to teach the claimed invention in order to provide predictive planning and allocation of resources with respect to occupational promotions and mobility within an organization.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/I.A.C./Examiner, Art Unit 2195
/Aimee Li/Supervisory Patent Examiner, Art Unit 2195