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 .
Status of the Claims
Claims 1-4, 6-10, 12-15, and 17-23 are all the claims pending in the application.
Claims 1-3, 8, and 18 are amended.
Claims 5, 11, and 16 are cancelled.
Claims 21-23 are new.
Claims 1-4, 6-10, 12-15, and 17-23 are rejected.
The following is a Final Office Action in response to amendments and remarks filed Dec. 17, 2025.
Response to Arguments
Regarding the 101 rejections, the rejections are maintained for the following reasons. Applicant asserts the claims reflect an improvement because the use of multiple filters allows for quickly analyzing data across an entire organization. Examiner respectfully does not find this assertion persuasive because claiming the improved speed or efficiency inherent with applying the abstract idea on a computer does not provide a sufficient inventive concept, see MPEP 2106.05(f)(2) (discussing Intellectual Ventures I LLC v. Capital One Bank (USA)). Accordingly the 101 rejections are maintained, please see below for the complete rejections of the claims as amended.
Regarding the 103 rejections, the rejections are maintained for the following reasons. Applicant assert the rejections should be withdrawn because the cited references do not teach multiple filters. Examiner respectfully does not find this assertion persuasive because Gao explicitly teaches using multiple filters, see Gao ¶[0069] and Fig. 3A. Accordingly the 103 rejections are maintained, please see below for the complete rejections of the claims as amended.
Please note, the limitations of the new claims 21-23 are not taught by the previously cited references. Please see below for the new references cited in the 103 rejections of claims 21-23.
In response to arguments in reference to any other depending claims that have not been individually addressed, all rejections made towards these dependent claims are maintained due to a lack of reply by Applicant in regards to distinctly and specifically pointing out the supposed errors in Examiner's prior office action (37 CFR 1.111). Examiner asserts that Applicant only argues that the dependent claims should be allowable because the independent claims are unobvious and patentable over the prior art.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-4, 6-10, 12-15, and 17-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Under Step 1 of the patent eligibility analysis, it must first be determined whether the claims are directed to one of the four statutory categories of invention. Applying Step 1 to the claims it is determined that: claims 1, 4, 6-9 and 21 are directed to a process; and claims 2, 3, 10, 12-15, 17-20, 22 and 23 are directed to a machine. Therefore, we proceed to Step 2.
Independent Claims
Under Step 2A Prong 1 of the patent eligibility analysis, it must be determined whether the claims recite an abstract idea that falls within one or more designated categories or “buckets” of patent ineligible subject matter that amount to a judicial exception to patentability.
The independent claims recite an abstract idea. Specifically, the independent claims recite an abstract idea in the limitations (emphasized):
…receive, via a user interface, a selection of criteria to generate a scheme for a dimension of an entity according to a level of granularity;
obtain, by the computer system, and using the cloud computing architecture configured to aggregate data associated with computing resources provided to devices in accordance with a plurality of models, a benchmark for the dimension by:
execute a function configured for the cloud computing architecture on access, based on the plurality of disparate systems, criteria of a second dimension similar to the dimension of the entity, the plurality of disparate systems including a human resource database, a payroll database, and a benefits system database; and
generate, using a neural network function, the benchmark for the second dimension according to the criteria of the second dimension and the level of granularity;
obtain a metric based on information of employees for the dimension of the entity;
identify that the metric does not satisfy the benchmark by comparing the benchmark for the second dimension against the metric;
generate responsive to the metric not satisfying the benchmark, the scheme with data aggregated from the disparate systems to adjust the metric to satisfy the benchmark based on the selection of criteria for the dimension of the entity;
generate a plurality of filters with the user interface comprising at least two of: a first filter configured with a first interactive graphical user element corresponding to a slide rule; a second filter configured with a second interactive graphical user element capable of adjusting a level of granularity with which to compare benchmarks, and a third filter configured with a third graphical user interface element configured to select a record associated the dimension of the entity and a fourth graphical user interface element capable of providing a display including the benchmark for the dimension of the entity;
generate responsive to the generation of the scheme, a second user interface within the user interface to display the plurality of filters indicating the generated scheme and to adjust the metric associated with the entity at the level of granularity; and
transmit for display on a display device coupled with the computer system, the generated second user interface with the plurality of filters.
These limitations recites an abstract idea because these limitation encompass commercial or legal interactions. These limitations encompass commercial or legal interactions because these limitations encompass marketing or sales activities or behaviors; business relations (i.e., market research). That is, these limitations encompass assessing salaries of employees to determine their relative levels of pay (e.g., relative to comparable employees in the same city) to determine appropriate salaries (e.g., for new employees). Claims that encompass commercial or legal interactions fall within the “Certain Methods of Organizing Human Activity”. Claims 1-3 recite an abstract idea.
Under Step 2A Prong 2 of the patent eligibility analysis, it must be determined whether the identified, recited abstract idea includes additional elements that integrate the abstract idea into a practical application.
The additional elements of the independent claims do not integrate the abstract idea into a practical application. The independent claims recite the additional elements (emphasized):
…receive, via a user interface, a selection of criteria to generate a scheme for a dimension of an entity according to a level of granularity;
obtain, by the computer system, and using the cloud computing architecture configured to aggregate data associated with computing resources provided to devices in accordance with a plurality of models, a benchmark for the dimension by:
execute a function configured for the cloud computing architecture on access, based on the plurality of disparate systems, criteria of a second dimension similar to the dimension of the entity, the plurality of disparate systems including a human resource database, a payroll database, and a benefits system database; and
generate, using a neural network function, the benchmark for the second dimension according to the criteria of the second dimension and the level of granularity;
obtain a metric based on information of employees for the dimension of the entity;
identify that the metric does not satisfy the benchmark by comparing the benchmark for the second dimension against the metric;
generate responsive to the metric not satisfying the benchmark, the scheme with data aggregated from the disparate systems to adjust the metric to satisfy the benchmark based on the selection of criteria for the dimension of the entity;
generate a plurality of filters with the user interface comprising at least two of: a first filter configured with a first interactive graphical user element corresponding to a slide rule; a second filter configured with a second interactive graphical user element capable of adjusting a level of granularity with which to compare benchmarks, and a third filter configured with a third graphical user interface element configured to select a record associated the dimension of the entity and a fourth graphical user interface element capable of providing a display including the benchmark for the dimension of the entity;
generate responsive to the generation of the scheme, a second user interface within the user interface to display the plurality of filters indicating the generated scheme and to adjust the metric associated with the entity at the level of granularity; and
transmit for display on a display device coupled with the computer system, the generated second user interface with the plurality of filters.
These additional elements do not integrate the abstract idea into an practical application for the following reasons. First, the additional elements of receiving selection criteria and transmitting and displaying the second user interface, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements encompass a generic computer function of receiving and displaying data (e.g. receiving user input and outputting results of an analysis), see MPEP 2106.05(f)(2) (noting the use of computers in their ordinary capacity to receive, store, or transmit data does not integrate a judicial exception into a practical application).
Second, the additional elements of the obtaining steps being performed by a computer system, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic components, see MPEP 2106.05(f).
Third, the additional elements of the various steps being performed using cloud computing architecture, as claimed, when considered individually or in combination, The additional elements of applying a first machine learning model, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are only a general link to a field of use or technological environment, see MPEP 2106.05(h) (discussing Affinity Labs). That is, although these additional elements do limit the use of the abstract idea, this type of limitation merely confines the use of the abstract idea to a particular technological environment (cloud computing) and does not integrate the abstract idea into a practical application or add an inventive concept to the claims.
Fourth, the additional elements of using a neural network, when considered individually or in combination, do not integrate the abstract idea into a practical application because the use of the neural network is recited sufficiently broadly and generally such that it amounts to no more than mere instructions to apply the exception, see MPEP 2106.05(f).
Fifth, the additional elements of generating the filters with an interactive graphical user element corresponding to a slide rule, the second interactive graphical user element capable of adjusting a level of granularity, and the third filter to select a record, and a fourth graphical user interface element displaying the bench mark for the dimension, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are only using software to tailor information and provide it to a user, which is no more than mere instructions to apply the exception, see MPEP 2106.05(f) (discussing Intellectual Ventures I LLC v. Capital One Bank (USA)).
The independent claims further recite “by a computer system comprising one or more processors coupled with memory”, a “non-transitory computer readable storage media including instructions” and “one or more processors coupled with memory, the one or more processors”. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components. Claims 1-3 are directed to an abstract idea.
Under Step 2B of the patent eligibility analysis, the additional elements are evaluated to determine whether they amount to something “significantly more” than the recited abstract idea (i.e., an innovative concept).
The independent claims do not include additional elements 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 mere instructions to apply the exception and a general link to a field of use. Mere instructions to apply an exception using generic computer components cannot and a general link to a field of use provide an inventive concept. Claims 1-3 are not patent eligible.
Dependent Claims
The dependent claims are rejected under 35 USC 101 as directed to an abstract idea for the following reasons.
Claims 4, 10, and 15 recite the additional elements of providing a notification via text or email. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements encompass a generic computer function of sending data (e.g. sending data using communication software), see MPEP 2106.05(f)(2) (noting the use of computers in their ordinary capacity to receive, store, or transmit data does not integrate a judicial exception into a practical application).
Claims 6, 12, and 17 recite the additional elements of filtering based on a menu selection. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional element are no more than using software to tailor information and provide it to a user, which is not more than mere instructions to apply the exception, see MPEP 2106.05(f) (discussing Intellectual Ventures I LLC v. Capital One Bank (USA)).
Claims 7, 13, and 18 recite the same abstract idea as the independent claims because providing alerts in response to an update of a benchmark is a part of performing market research (e.g., notifying changes in the research).
Claims 8, 14, and 19 recite the same abstract idea as the independent claims because determining a benchmark or a second dimension is a part of performing market research (e.g., identifying multiple, relevant metrics like salaries and bonuses).
Claims 9 and 20 recite the same abstract idea as the independent claims because scoring and estimating a benchmark and using the estimate make recommendations (e.g., estimating regional salaries to make recommendations) is a part of performing market research on salaries.
Claims 9 and 20 further recite the additional elements of generating a third user interface to display a second report. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements encompass a generic computer function of sending data (e.g. sending data for display), see MPEP 2106.05(f)(2) (noting the use of computers in their ordinary capacity to receive, store, or transmit data does not integrate a judicial exception into a practical application).
Claims 21-23 recite the same abstract idea as the independent claims because updating the benchmark based on selections of the claimed inputs and recalculating the benchmark based on changes to the input is a part of performing market research (e.g., determining a benchmark based for varying parameters).
Claims 21-23 further recite the additional elements of receiving a selection and generating a graphical representation of benchmarks. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements encompass a generic computer function of receiving and sending data (e.g. receiving user input and displaying outputs), see MPEP 2106.05(f)(2) (noting the use of computers in their ordinary capacity to receive, store, or transmit data does not integrate a judicial exception into a practical application).
Claims 21-23 further recite the additional elements of using the neural network. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the use of the neural network is recited sufficiently broadly and generally such that it amounts no more than mere instructions to apply the exception, see MPEP 2106.05(f).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim(s) 1-4, 6-8, 10, 12-15, and 17-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kuhn et al., US Pub. No. 2005/0192823, herein referred to as “Kuhn” in view of Borgen et al, US Pat. No. 8,494,929, herein referred to as “Borgen”, further in view of Gao et al, Pub. No. 2019/0079957, herein referred to as “Gao”.
Regarding claim 1, Kuhn teaches:
receiving, by a computer system comprising one or more processors coupled with memory, via a user interface, a selection of criteria to generate a scheme for a dimension of an entity (receives selections of employment data sources to compare employment data, ¶[0065]; see also e.g., ¶¶[0035], [0077], [0078] discussing processors, memory and user interfaces);
obtaining, by the computer system, a benchmark for the dimension by: executing, by the computer system, a function on access, from disparate systems, criteria of a second dimension similar to the dimension of the entity (compares compensation with similar employment positions at other companies, based on data obtained from survey data, ¶[0067]);
the plurality of disparate systems including a human resource database (employee database, Fig. 1, ref. chars. 42 and 50; see also ¶¶[0032]-[0034] discussing Fig. 1)
a payroll database (company compensation databased, ¶[0035] and Fig. 1, ref. char. 58),
and a benefits system database (computer system includes information on benefits, ¶¶[0033]-[0034]);
and generating, by the computer system, the benchmark for the second dimension according to the criteria of the second dimension (determines average salaries ranges provided by other companies, ¶¶[0051]-[0052], [0068]);
obtaining, by the computer system, a metric based on information of employees for the dimension of the entity (collects employee information, ¶[0033]);
identifying, by the computer system, that the metric does not satisfy the benchmark by comparing the benchmark for the second dimension against the metric (compares compensation of user with others, e.g. compares employee base pay to 25th percentile base salaries for similar position, ¶¶[0038], [0046]-[0047])
generating, by the computer system, responsive to the metric not satisfying the benchmark, the scheme with data aggregated from the disparate systems to adjust the metric to satisfy the benchmark based on the selection of criteria for the dimension of the entity (adjusts compensation based on comparison to other salaries, ¶[0035])
However Kuhn does not teach but Borgen does teach:
generate a scheme for a dimension of an entity according to a level of granularity (compensation report is based on average salary in the same city, Col. 3, l. 53 - Col. 4, l. 5)
generating, by the computer system, the benchmark for the second dimension according to the criteria of the second dimension and the level of granularity (compensation report is based on average salary in the same city, Col. 3, l. 53 - Col. 4, l. 5)
adjusting a level of granularity with which to compare benchmarks (aggregated data may be clustered based on location (e.g., same city, state, etc.) Col. 7, ll. 21-37)
and generating, by the computing system, responsive to the generation of the scheme, a second user interface within the user interface to display the filter indicating the generated scheme and to adjust the metric associated with the entity at the level of granularity (notifies employer when salary range is above or below the suggested range, Col. 7, l. 39 – Col. 8, l. 8).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the compensation monitoring of Kuhn with the salary advisor of Borgen because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have recognized users of Kuhn (e.g., human resource managers) would likely not only be interested in monitoring compensation but also would be interested in advice for their compensation rates and accordingly would have modify Kuhn to provide salary advice (e.g., as taught by Borgen).
However the combination of Kuhn and Borgen does not teach but Gao does teach:
and using the cloud computing architecture configured to aggregate data associated with computing resources provided to devices in accordance with a plurality of models (system is implemented via cloud computing and performs the various functions using a set of remote models, ¶¶[0065], [0093]);
a function configured for the cloud computing architecture on access, based on the plurality of disparate systems (various apparatuses in system are implemented via cloud computing , ¶¶[0065], [0093]; see also ¶¶[0029]-[0031], [0037] discussing information on various entities and Fig. 1 showing accessing various systems);
using a neural network (performs analysis using neural network, ¶¶[0004], [0034])
generating, by the computer system, a plurality of filters with the user interface comprising at least two of: a first filter configured with a first interactive graphical user element corresponding to a slide rule (GUI enables filtering data in visualizations and searches, ¶¶[0060], [0075], [0088], and visualizations are adjusted with a slider interface element, ¶¶[0069], [0073]; see also Fig. 3A showing multiple filters),
a second filter configured with a second interactive graphical user element capable of adjusting a level of granularity with which to compare benchmarks (granularity may be specified using user-interface elements including a number of options for selecting the time interval spanned, ¶[0069]; see also Fig. 3A showing multiple filters)
and a third filter configured with a third graphical user interface element configured to select a record associated the dimension of the entity (visualizations are updated based position of cursor, ¶¶[0070], [0074] and Fig. 3A);
and a fourth graphical user interface element capable of providing a display including the benchmark for the dimension of the entity (visualizations include various benchmarks like mean, minimum, etc., ¶¶[0070], [0072] and Fig. 3A);
generating, by the computer system, responsive to the generation of the scheme, a second user interface within the user interface to display the plurality of filters indicating the generated scheme (GUI enables filtering data in visualizations and searches, ¶¶[0060], [0075], [0088], and visualizations are adjusted with a slider interface element, ¶¶[0069], [0073]; see also Fig. 3A showing multiple filters);
and transmitting, by the computer system, for display on a display device coupled with the computer system, the generated second user interface with the plurality of filters (graphical user interface is provided, ¶[0067]; see also ¶[0089] and Fig. 6 discussing display device);
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the compensation monitoring and salary advisor of Kuhn and Borgen with the cloud computing and neural network of Gao because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have modified the analysis in Kuhn and Borgen to use cloud computing and a neural network in situations where such concepts are advantageous (e.g., when scaling and flexibility is desired and when there is sufficient data to benefit from the use of neural networks).
Regarding claim 4, the combination of Kuhn, Borgen, and Gao teaches all the limitation of claim 1 and Borgen further teaches:
providing, by the computer system, a notification to a computing device of the entity indicating the scheme adjust the metric, wherein the notification is at least one of a text message or an email (notifies via email employer when salary range is above or below the suggested range, Col. 7, l. 39 – Col. 8, l. 8).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the compensation monitoring of Kuhn with the salary advisor of Borgen because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have recognized users of Kuhn (e.g., human resource managers) would likely not only be interested in monitoring compensation but also would be interested in advice for their compensation rates and accordingly would have modify Kuhn to provide salary advice (e.g., as taught by Borgen).
Regarding claim 6, the combination of Kuhn, Borgen, and Gao teaches all the limitation of claim 1 and Kuhn further teaches:
wherein receiving the selection of criteria further comprises filtering the selection of criteria, in response to a selection of a menu displayed on the user interface (receives selections of employment data sources to compare employment data, ¶[0065]; see also ¶[0040] discussing menus in GUIs).
Regarding claim 7, the combination of Kuhn, Borgen, and Gao teaches all the limitation of claim 1 and Gao further teach:
generating, by the computer system, an alert via the second user interface, in response to an update to the benchmark according to the disparate systems (provides an alert when models are changed, ¶[0082]).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the compensation monitoring and salary advisor of Kuhn and Borgen with the change alerts of Gao because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have recognized the pay bands in Kuhn would likely change over time and accordingly would have modified Kuhn to alert the user when the pay bands change, e.g., as taught by Gao.
Regarding claim 8, the combination of Kuhn, Borgen, and Gao teaches all the limitation of claim 1 and Kuhn further teaches:
for each disparate system in the disparate systems according to the level of granularity: accessing a database associated with the disparate system to obtain criteria of the second dimension and data associated with the second dimension (receives company data from multiple company databases, ¶¶[0008], [0034]);
and calculating the benchmark using the criteria of the second dimension and the data (determines average salaries ranges provided by other companies, ¶¶[0051]-[0052], [0068]).
Regarding claims 2, 3, 10, 12-15, and 17-19, claims 2, 3, 10, 12-15, and 17-19, recite similar limitations as claims 1, 4, and 6-8 and accordingly are rejected for similar reasons as claims 1, 4, and 6-8 .
Claim(s) 9 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kuhn, Borgen, and Gao further in view of Warwick et al, Pub. No. 2021/0390511, herein referred to as “Warwick”.
Regarding claim 9, the combination of Kuhn, Borgen, and Gao teaches all the limitation of claim 1 and Kuhn further teaches:
identifying, by the computer system, that the metric does not satisfy the score (compares compensation of user with others, e.g. compares employee base pay to 25th percentile base salaries for similar position, ¶¶[0038], [0046]-[0047]);
generating, by the computer system responsive to the metric not satisfying the score, the scheme with data aggregated from the disparate systems to adjust the metric to satisfy the score based on the selection of criteria for the dimension of the entity (adjusts compensation based on comparison to other salaries, ¶[0035]);
However Kuhn does not teach but Borgen does teach:
a score indicating an estimation of the benchmark (uses suggested salaries instead of average salaries, Col. 3, ll. 53 – 67);
and generating, by the computer system responsive to the generation of the scheme, a third user interface within the user interface to display a second report indicating the generated scheme to adjust the metric associated with the entity at the level of granularity (notifies employer when salary range is above or below the suggested range, Col. 7, l. 39 – Col. 8, l. 8).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the compensation monitoring of Kuhn with the salary advisor of Borgen because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have recognized users of Kuhn (e.g., human resource managers) would likely not only be interested in monitoring compensation but also would be interested in advice for their compensation rates and accordingly would have modify Kuhn to provide salary advice (e.g., as taught by Borgen).
However the combination of Kuhn, Borgen, and Gao does not teach but Warwick does teach:
a score for the disparate systems indicating an estimation of the benchmark (ranks sources of job data based on a statistical accuracy of data derived from the sources, ¶[0100] and Fig. 6).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the compensation monitoring and salary advisor of Kuhn, Borgen, and Gao with the assessing accuracy of job data sources, as taught by Warwick, because Warwick suggests doing so do address the fact that data in a job related source of data may be old or inaccurate, see MPEP 2143.I.G.
Regarding claim 20, claim 20 recites similar limitations as claim 9 and accordingly is rejected for similar reasons as claim 9.
Claim(s) 21-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kuhn and Borgen further in view of Hannebaum al, Pat. No. 10,782,864, herein referred to as “Hannebaum”.
Regarding claim 21, the combination of Kuhn, Borgen, and Gao teaches all the limitation of claim 1 and Kuhn further teaches:
adjust a geographic level of the level of granularity for the benchmark at the dimension of the entity, the geographic level including at least one of national, state, or regional, further comprising (aggregated data may be clustered based on location (e.g., same city, state, etc.) Col. 7, ll. 21-37):
generating, by the computer system, a graphical representation of benchmarks by geographic location at multiple levels of granularity (aggregated data may be clustered based on location (e.g., same city, state, etc.) Col. 7, ll. 21-37):,
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the compensation monitoring of Kuhn with the salary advisor of Borgen because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have recognized users of Kuhn (e.g., human resource managers) would likely not only be interested in monitoring compensation but also would be interested in advice for their compensation rates and accordingly would have modify Kuhn to provide salary advice (e.g., as taught by Borgen).
However the combination of Kuhn and Borgen does not teach but Gao does teach:
and updating, by the computer system, responsive to the selection via the second user interface, the benchmark (visualizations are updated based on selection of granularity, ¶[0080])
based on execution of the neural network with input corresponding to the selection of the at least one of the plurality of filters and the geographic level of granularity (statistical models include artificial neural networks, ¶[0034]);
and wherein values of the benchmark displayed are recalculated by the neural network responsive to changes in both the geographic level of granularity and the selection of the at least two filters (visualizations are updated based on selection of granularity, ¶[0080])
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the compensation monitoring and salary advisor of Kuhn and Borgen with the cloud computing and neural network of Gao because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have modified the analysis in Kuhn and Borgen to use cloud computing and a neural network in situations where such concepts are advantageous (e.g., when scaling and flexibility is desired and when there is sufficient data to benefit from the use of neural networks).
However the combination of Kuhn, Borgen and Gao does not teach but Hannebaum does teach:
wherein the second user interface includes a graphical user element that is configured to adjust (interface includes and first and second axis to be adjusted, Col. 8, ll. 26-63)
receiving, by the computer system via the second user interface, a selection of at least one of the plurality of filters and the geographic level of granularity for the benchmark (interface includes and first and second axis to be adjusted, Col. 8, ll. 26-63; see also Col. 4, ll. 26-33, Col. 5, ll. 30-44 discussing examples of variables for slider including location)
wherein the graphical representation is dynamically updated in real time based on user selection of at least two filters (filters based on selected adjustments, Col. 8, ll. 26-63),
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the neural network based compensation monitoring and salary advisor of Kuhn, Borgen and Gao with the multi-axis slider of Hannebaum because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have recognized users would be interested in compensation monitoring based on various parameters and accordingly would have modified the neural network based compensation monitoring and salary advisor of Kuhn, Borgen and Gao to allow adjustments for multiple input variables, e.g. as taught by Hannebaum.
Regarding claims 22 and 23, claims 22 and 23 recite similar limitations as claim 21 and accordingly is rejected for similar reasons as claim 21.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRENDAN S O'SHEA whose telephone number is (571)270-1064. The examiner can normally be reached Monday to Friday 10-6.
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/BRENDAN S O'SHEA/Examiner, Art Unit 3626