DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This action is made final.
Claims 1-9 filed on 04/22/2026 have been reviewed and considered by this office action.
Claims 1-8 have been amended.
Claim 9 has been newly added.
Response to Arguments
Applicant’s amended claims, filed 04/22/2026, have overcome the rejection under 35 U.S.C. § 112.
Regarding the rejection of claim 1 under 35 U.S.C. § 103, applicant argues that Kansha fails to teach steps b) and e). Examiner respectfully disagrees.
Claim 1 recites, in relevant part, that from the provisionally selected data records, the computer definitively selects, in accordance with a predetermined second distance criterion, a predetermined second number (n2) of data records (D) in which the first actual variables (I1) and the second actual variables (I2) display a distance from the first and second expected values (El, E2) that is as small as possible. Kansha teaches this refining selection. In particular, Kansha first describes a just-in-time learning procedure in which relevant data samples in the database are searched to match query data by a nearest-neighborhood criterion. This initial search corresponds to the provisional selection of data records. Kansha then further discloses that, after similarity values are computed, candidate relevant data sets are constructed for each candidate value l within a predetermined range from kmin to kmax. For each such candidate value, Kansha selects the l most relevant data records corresponding to the largest similarity values. Kansha then performs a leave-one-out cross-validation test, calculates validation error, and determines the optimal l* as the value giving the smallest validation error. The final predicted output is then calculated using the data set corresponding to the optimal l*.
Thus, Kansha does not merely select records once and stop. Kansha first identifies relevant/provisional records by nearest-neighborhood similarity, and then refines the selection by evaluating candidate relevant data sets and selecting the optimal number l* of records based on the smallest validation error. The finally used l* data set corresponds to the claimed definitively selected second number of data records. Therefore, Kansha’s procedure includes a further refinement and definitive selection of the records actually used in the local model. Accordingly, applicant’s arguments are not persuasive since the cited prior art describes the limitations in these claims.
For at least these reasons, the rejection is still deemed proper and has been maintained.
Claim Objections
Claim 1 is objected to because of the following informalities:
Claim 1 recites the limitation “to perform the another technical process.” There is insufficient antecedent basis for this limitation in the claim. The limitation will be interpreted to recite “to perform the another cycle of the technical process.”
Appropriate correction is required.
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 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1-6 are directed to a process. Claims 7 and 8 are directed to a machine or an article of manufacture.
With respect to claim 1:
2A Prong 1: The claim recites an abstract idea. Specifically:
a) wherein by utilizing a model of the plant and of the technical process the computer ascertains, on the basis of specified reference values (R) for first target variables (Z1) of the technical process, first expected values (E1) for first actual variables (I1) of the technical process, so that the first target variables (Z1) attain the reference values (R) as far as possible (Mental process – ascertaining expected values for actual variables of a technical process is an evaluation that can be practically performed in the human mind, or by a human using a pen and paper as a physical aid – see MPEP § 2106.04(a)(2)(III))
d) wherein on the basis of the specified reference values (R) for the first target variables (Z1) and on the basis of the first expected values (E1) the computer ascertains second expected values (E2) for the second actual variables (I2) (Mental process – ascertaining expected variables on the basis of reference and expected values is an evaluation that can be practically performed in the human mind, or by a human using a pen and paper as a physical aid – see MPEP § 2106.04(a)(2)(III))
f) wherein on the basis of the definitively selected data records (D) for another cycle of the technical process that is yet to be executed the computer ascertains set values (S) for the second target variables (Z2), so that the first target variables (Z1) attain the reference values (R) as far as possible (Mental process – ascertaining set values for target variables is an evaluation that can be practically performed in the human mind, or by a human using a pen and paper as a physical aid – see MPEP § 2106.04(a)(2)(III))
2A Prong 2: The additional elements recited in the claim do not integrate the abstract idea into a practical application, individually or in combination.
Additional elements:
b) wherein from a large number of data records (D) known to the computer, which comprise—in each instance for a single cycle of the technical process—the first target variables (Z1) and second target variables (Z2), the first actual variables (I1) and second actual variables (I2), the computer provisionally selects, in accordance with a predetermined first distance criterion, a predetermined first number (n1) of data records (D) in which the first actual variables (I1) display a distance from the first expected values (E1) that is as small as possible (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
c) wherein the first target variables (Z1) are disjunct from the second target variables (Z2), and the first actual variables (I1) are disjunct from the second actual variables (I2) (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
e) wherein from the provisionally selected data records (D) the computer definitively selects, in accordance with a predetermined second distance criterion, a predetermined second number (n2) of data records (D) in which the first actual variables (I1) and the second actual variables (I2) display a distance from the first and second expected values (E1, E2) that is as small as possible (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
g) wherein the ascertained set values (S) are sent to the control device to perform the another technical process (Insignificant extra-solution activity – outputting values to an operator represents post-solution activity – see MPEP § 2106.05(g))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
b) wherein from a large number of data records (D) known to the computer, which comprise—in each instance for a single cycle of the technical process—the first target variables (Z1) and second target variables (Z2), the first actual variables (I1) and second actual variables (I2), the computer provisionally selects, in accordance with a predetermined first distance criterion, a predetermined first number (n1) of data records (D) in which the first actual variables (I1) display a distance from the first expected values (E1) that is as small as possible (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
c) wherein the first target variables (Z1) are disjunct from the second target variables (Z2), and the first actual variables (I1) are disjunct from the second actual variables (I2) (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
e) wherein from the provisionally selected data records (D) the computer definitively selects, in accordance with a predetermined second distance criterion, a predetermined second number (n2) of data records (D) in which the first actual variables (I1) and the second actual variables (I2) display a distance from the first and second expected values (E1, E2) that is as small as possible (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
g) wherein the ascertained set values (S) are sent to the control device to perform the another technical process (Insignificant extra-solution activity – outputting values to an operator represents post-solution activity – see MPEP § 2106.05(g))
Therefore, claim 1 is ineligible.
With respect to claim 2:
2A Prong 2: The additional elements recited in the claim do not integrate the abstract idea into a practical application, individually or in combination.
Additional elements:
wherein the computer accepts the reference values (R) from the operator (Insignificant extra-solution activity (mere data gathering) – see MPEP § 2106.05(g))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
wherein the computer accepts the reference values (R) from the operator (Insignificant extra-solution activity (mere data gathering) – see MPEP § 2106.05(g))
Therefore, claim 2 is ineligible.
With respect to claim 3:
2A Prong 2: The additional elements recited in the claim do not integrate the abstract idea into a practical application, individually or in combination.
Additional elements:
wherein the computer firstly accepts a selection of the first target variables (Z1) as such from the operator and only then accepts the reference values (R) for the first target variables (Z1) from the operator (Insignificant extra-solution activity (mere data gathering) – see MPEP § 2106.05(g))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
wherein the computer firstly accepts a selection of the first target variables (Z1) as such from the operator and only then accepts the reference values (R) for the first target variables (Z1) from the operator (Insignificant extra-solution activity (mere data gathering) – see MPEP § 2106.05(g))
Therefore, claim 3 is ineligible.
With respect to claim 4:
2A Prong 2: The additional elements recited in the claim do not integrate the abstract idea into a practical application, individually or in combination.
Additional elements:
wherein between accepting the selection of the first target variables (Z1) as such and accepting the reference values (R) for the first target variables (Z1) the computer ascertains ranges of values, arising on the basis of the data records (D), for the first target variables (Z1), and outputs the ranges of values arising to the operator (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
wherein between accepting the selection of the first target variables (Z1) as such and accepting the reference values (R) for the first target variables (Z1) the computer ascertains ranges of values, arising on the basis of the data records (D), for the first target variables (Z1), and outputs the ranges of values arising to the operator (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
Therefore, claim 4 is ineligible.
With respect to claim 5:
2A Prong 2: The additional elements recited in the claim do not integrate the abstract idea into a practical application, individually or in combination.
Additional elements:
wherein the computer outputs at least the first actual variables (I1) of the first number (n1) of data records (D) to the operator, and the computer eliminates individual data records (D) from the first number (n1) of data records (D), so that the eliminated data records (D) are disregarded in the course of ascertaining the definitively selected data records (D) (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
wherein the computer outputs at least the first actual variables (I1) of the first number (n1) of data records (D) to the operator, and the computer eliminates individual data records (D) from the first number (n1) of data records (D), so that the eliminated data records (D) are disregarded in the course of ascertaining the definitively selected data records (D) (Insignificant extra-solution activity (selecting a particular data source or type of data to be manipulated) – see MPEP § 2106.05(g))
Therefore, claim 5 is ineligible.
With respect to claim 6:
2A Prong 2: The additional elements recited in the claim do not integrate the abstract idea into a practical application, individually or in combination.
Additional elements:
wherein the computer-executes steps b) to e) again after the first-time execution of step e), wherein the computer bases the renewed execution of steps b) to e) upon the first actual variables (I1), as first expected values (E1), of that data record (D) of the second number (n2) of data records (d) which have displayed the smallest distance from the first expected values (E1) in the course of the execution of step e), which has already taken place (Adding insignificant extra-solution activity to the judicial exception – see MPEP § 2106.05(g))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
wherein the computer-executes steps b) to e) again after the first-time execution of step e), wherein the computer bases the renewed execution of steps b) to e) upon the first actual variables (I1), as first expected values (E1), of that data record (D) of the second number (n2) of data records (d) which have displayed the smallest distance from the first expected values (E1) in the course of the execution of step e), which has already taken place (Performing repetitive calculations has been deemed a well‐understood, routine, and conventional function – see MPEP § 2106.05(d)(ll))
Therefore, claim 6 is ineligible.
With respect to claim 7:
2A Prong 2: The additional elements recited in the claim do not integrate the abstract idea into a practical application, individually or in combination.
Additional elements:
A computer program product comprising a non-transitory computer-readable medium having recorded thereon machine code which is capable of being processed by a computer, the processing of the machine code by the computer resulting in the execution of an optimization method as claimed in claim 1 (Mere recitation of a generic computer component – see MPEP § 2106.05(b)(I))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
A computer program product comprising a non-transitory computer-readable medium having recorded thereon machine code which is capable of being processed by a computer, the processing of the machine code by the computer resulting in the execution of an optimization method as claimed in claim 1 (Mere recitation of a generic computer component – see MPEP § 2106.05(b)(I))
Therefore, claim 7 is ineligible.
With respect to claim 8:
2A Prong 2: The additional elements recited in the claim do not integrate the abstract idea into a practical application, individually or in combination.
Additional elements:
A computer programmed with a computer program to execute an optimization method as claimed in claim 1 (Mere recitation of a generic computer component – see MPEP § 2106.05(b)(I))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
A computer programmed with a computer program to execute an optimization method as claimed in claim 1 (Mere recitation of a generic computer component – see MPEP § 2106.05(b)(I))
Therefore, claim 8 is ineligible.
With respect to claim 9:
2A Prong 2: The additional elements recited in the claim do not integrate the abstract idea into a practical application, individually or in combination.
Additional elements:
wherein the plant is a steel product plant or an aluminum product plant (Generally linking the use of a judicial exception to a particular technological environment or field of use – see MPEP § 2106.05(h))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
wherein the plant is a steel product plant or an aluminum product plant (Generally linking the use of a judicial exception to a particular technological environment or field of use – see MPEP § 2106.05(h))
Therefore, claim 9 is ineligible.
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.
Claims 1 and 6-9 are rejected under 35 U.S.C. 103 as being unpatentable over Kansha et al. (Kansha, Yasuki, and Min-Sen Chiu. “Adaptive generalized predictive control based on JITL technique.” Journal of Process Control 19, no. 7 (2009): 1067-1072.), herein Kansha, in view of Breuer (DE 10 2020 201 215 A1) (Note: a machine translation is used for mapping, attached to this action).
Regarding claim 1, Kansha teaches a method of operating a plant in the basic-materials industry with a computer and a control device which controls the execution of a technical process cyclically, time and time again (Page 1068, Section 2.1: “When the next query data is available, a new local model will be built by repeating the aforementioned procedure”),
a) wherein by utilizing a model of the plant and of the technical process the computer ascertains, on the basis of specified reference values (R) (Page 1068, Section 2.1: “r(k+i) is the future set-point”) for first target variables (Z1) of the technical process (Page 1068, Section 2.1: “Suppose that the present database of JITL consists of N process data (y(i), xi)i=1-N, given a query data xq”), first expected values (E1) for first actual variables (I1) of the technical process (Page 1068, Section 2.1: “y(k+i/k) is the prediction of the future process output at the (k+i)th sampling instant in the prediction horizon Np”), so that the first target variables (Z1) attain the reference values (R) as far as possible (Page 1068, Section 2.1: “(ii) a low-order local model is built based on the relevant data; and (iii) model output is calculated based on the local model and the current query data. When the next query data is available, a new local model will be built by repeating the aforementioned procedure”),
b) wherein from a large number of data records (D) known to the computer, which comprise—in each instance for a single cycle of the technical process—the first target variables (Z1) and second target variables (Z2), the first actual variables (I1) and second actual variables (I2), the computer provisionally selects, in accordance with a predetermined first distance criterion, a predetermined first number (n1) of data records (D) in which the first actual variables (I1) display a distance from the first expected values (E1) that is as small as possible (Page 1068, Section 2.1: “(i) relevant data samples in the database are searched to match the query data by some nearest neighborhood criterion”),
d) wherein on the basis of the specified reference values (R) for the first target variables (Z1) and on the basis of the first expected values (E1) the computer ascertains second expected values (E2) for the second actual variables (I2) (Page 1068, Section 2.1: “(ii) a low-order local model is built based on the relevant data; and (iii) model output is calculated based on the local model and the current query data. When the next query data is available, a new local model will be built by repeating the aforementioned procedure”),
e) wherein from the provisionally selected data records (D) the computer definitively selects, in accordance with a predetermined second distance criterion, a predetermined second number (n2) of data records (D) in which the first actual variables (I1) and the second actual variables (I2) display a distance from the first and second expected values (E1, E2) that is as small as possible (Page 1068, Section 2.1: “After all si are computed by Eq. (3), for each l ϵ [kmin kmax], where kmin and kmax are the pre-specified minimum and maximum numbers of relevant data, the relevant data set (yl , Φl) is constructed by selecting the l most relevant data (yi, xi) corresponding to the largest si to the lth largest si “),
f) wherein on the basis of the definitively selected data records (D) for another cycle of the technical process that is yet to be executed the computer ascertains set values (S) for the second target variables (Z2), so that the first target variables (Z1) attain the reference values (R) as far as possible (Page 1069, Section 2.2: “Δu is computed by solving the quadratic optimization problem of Eq. (17) subject to the constraints given in Eq. (8) and only Δu(k) is implemented into the process”), and
g) wherein the ascertained set values (S) are sent to the control device to perform the another technical process (Page 1068, Section 2.2: “the aim of the proposed JITL-based GPC design is to find the optimal future control actions that drive the future process output to track the reference trajectory as closely as possible in the presence of system constraints and disturbances”; Page 1069, Section 2.2: “Δu is computed by solving the quadratic optimization problem of Eq. (17) subject to the constraints given in Eq. (8) and only Δu(k) is implemented into the process”).
Kansha does not explicitly teach “c) wherein the first target variables (Z1) are disjunct from the second target variables (Z2), and the first actual variables (I1) are disjunct from the second actual variables (I2).”
Breuer teaches c) wherein the first target variables (Z1) are disjunct from the second target variables (Z2), and the first actual variables (I1) are disjunct from the second actual variables (I2) ([0007]: “the target values of a selected plant parameter, calculated at time n, for a selected group of individual units of the industrial plant or for a temporal sequence of selected process steps at an individual unit of the industrial plant, are summarized or grouped into an old pattern, wherein the target values of the individual pattern are functionally related to each other; and that, to calculate the new target value for the at least one plant parameter at time n+ 1, the old pattern is fed to the process model as an input variable, and only the target values of the plant parameter of the old pattern are recalculated and grouped in the form of a new pattern. Any existing target values for other system parameters will be kept constant during the recalculation”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the method of Kansha to incorporate the teachings of Breuer so as to include the first target variables (Z1) being disjunct from the second target variables (Z2), and the first actual variables (I1) being disjunct from the second actual variables (I2). Doing so would allow the optimization problem to be solved with the aim of reducing computational effort while preserving accuracy ([0008]: “The solution according to the invention to the above-mentioned problem, i.e., the significant reduction of the computing power required to solve the optimization problem, is achieved according to the invention by expressly not calculating the influence of all possible actuators on a target variable, but only by recalculating the target values of a single selected plant parameter for a selected group of individual units of the industrial plant with regard to solving the optimization problem. This significantly reduces the required computational effort and also makes it possible to calculate the target values for the selected system parameter in real time with sufficient accuracy to solve the optimization problem”).
Regarding claim 6, Kansha in view of Breuer teaches the method as claimed in claim 1.
Kansha further teaches wherein the computer-executes steps b) to e) again after the first-time execution of step e), wherein the computer bases the renewed execution of steps b) to e) upon the first actual variables (I1), as first expected values (E1), of that data record (D) of the second number (n2) of data records (d) which have displayed the smallest distance from the first expected values (E1) in the course of the execution of step e), which has already taken place (Page 1068, Section 2.1: “When the next query data is available, a new local model will be built by repeating the aforementioned procedure”).
Regarding claim 7, Kansha teaches a computer program product comprising a non-transitory computer-readable medium having recorded thereon machine code which is capable of being processed by a computer (Page 1071, Section 3.1: “it is noted that the computational time for the proposed GPC design is about 0.1 min in our PC with specification of 2.4 GHz CPU and 1 GB RAM, which is much smaller than the sampling time. Given the fast computational time, the proposed JITL-based GPC design is feasible to be implemented in industrial control systems”), the processing of the machine code by the computer resulting in the execution of the method as claimed in claim 1 (see claim 1 rejection).
Regarding claim 8, Kansha teaches a computer programmed with a computer program to execute the method (Page 1071, Section 3.1: “it is noted that the computational time for the proposed GPC design is about 0.1 min in our PC with specification of 2.4 GHz CPU and 1 GB RAM, which is much smaller than the sampling time. Given the fast computational time, the proposed JITL-based GPC design is feasible to be implemented in industrial control systems”) as claimed in claim 1 (see claim 1 rejection).
Regarding claim 9, Kansha in view of Breuer teaches the method as claimed in claim 1.
Kansha does not explicitly teach “wherein the plant is a steel product plant or an aluminum product plant.”
Breuer further teaches wherein the plant is a steel product plant or an aluminum product plant ([0001]: “The invention relates to a method for operating an industrial plant, in particular in the metallurgical industry, in which at least one process takes place for producing or processing a workpiece, in particular a slab of steel”).
Claims 2 and 3 are rejected under 35 U.S.C. 103 as being unpatentable over Kansha, in view of Breuer (DE 10 2020 201 215 A1), and in view of Adelman et al. (US 6,591,225 B1).
Regarding claim 2, Kansha in view of Breuer teaches the method as claimed in claim 1.
Kansha and Breuer do not explicitly teach “wherein the computer accepts the reference values (R) from the operator.”
Adelman further teaches wherein the computer accepts the reference values (R) from the operator (FIGS. 6A-6D and Col. 8, Lines 24-28: “Grid 603 of FIG. 6B illustrates the display of reference values for all the components. In this example, only the plant, gas turbine, and steam turbine components have reference variables. The user uses this grid to change the values of the reference variables”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the method of Kansha in view of Breuer to incorporate the teachings of Adelman so as to include the computer accepting the reference values (R) from the operator. Doing so would allow a user to specify a configuration of a plant with the aim of optimizing performance (Col. 2, Lines 24-39: “The optimization system allows a user (e.g., plant manager, engineer, and plant operator) to specify the configuration (current or desired) of the power plant. The optimization system adjusts the equations based on this configuration by either modifying the equations themselves or by setting variables that are used by the equations… Once a user has specified a value or range of values of various factors, then the optimization system analyzes the equations to arrive at a set of operating conditions that will result in optimal performance. Optimal performance may be evaluated in various ways such as maximization of overall profit of the power plant”).
Regarding claim 3, Kansha in view of Breuer and Adelman teaches the method as claimed in claim 2.
Kansha and Breuer do not explicitly teach “wherein the computer firstly accepts a selection of the first target variables (Z1) as such from the operator and only then accepts the reference values (R) for the first target variables (Z1) from the operator.”
Adelman further teaches wherein the computer firstly accepts a selection of the first target variables (Z1) as such from the operator (FIGS. 5A-5C and Col. 8, Lines 7-12: “The optimization system displays dialog box 503 after the user has selected the plant component and the modeling constants variable type. The optimization system displays the available modeling constants in area 504, and the modeling constants that are currently selected to be exposed in area 505”) and only then accepts the reference values (R) for the first target variables (Z1) from the operator (FIGS. 6A-6D and Col. 8, Lines 24-28: “Grid 603 of FIG. 6B illustrates the display of reference values for all the components. In this example, only the plant, gas turbine, and steam turbine components have reference variables. The user uses this grid to change the values of the reference variables”).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Kansha, in view of Breuer (DE 10 2020 201 215 A1), Adelman et al. (US 6,591,225 B1), and Paquette et al. (US 2016/0055221 A1).
Regarding claim 4, Kansha in view of Breuer and Adelman teaches the method as claimed in claim 3.
Kansha, Breuer, and Adelman do not explicitly teach “wherein between accepting the selection of the first target variables (Z1) as such and accepting the reference values (R) for the first target variables (Z1) the computer ascertains ranges of values, arising on the basis of the data records (D), for the first target variables (Z1), and outputs the ranges of values arising to the operator.”
Paquette further teaches wherein between accepting the selection of the first target variables (Z1) as such and accepting the reference values (R) for the first target variables (Z1) the computer ascertains ranges of values, arising on the basis of the data records (D), for the first target variables (Z1), and outputs the ranges of values arising to the operator ([0011]: “The selection of variables and ranges for the variables can include defining a classifier protocol based on user input comprising selection of one or more predictive criteria. The classifier protocol can include a predictive model and a user-defined threshold, and a notification can be provided to a user of the data analysis application and/or to another user of the classifier protocol based on a prediction generated by the predictive model constrained by the background data set, the focus set, and the one or more predictive criteria”; [0109]: “User interaction with the application user interface can allow selection of variables and ranges for the variables based on visual displays of the effects on the range choices at 4706”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the method of Kansha in view of Breuer and Adelman to incorporate the teachings of Paquette so as to include between accepting the selection of the first target variables (Z1) as such and accepting the reference values (R) for the first target variables (Z1) the computer ascertaining ranges of values, arising on the basis of the data records (D), for the first target variables (Z1), and outputting the ranges of values arising to the operator. Doing so would allow suitable values to be output to an operator without the requiring the operator to have an understanding of the way the ranges were computed ([0009]: “Implementations of the current subject matter can support a variety of data analysis and visualization approaches, techniques, and the like, which can provide advantages in usability to analyses based on the EGAN schema or other related schema for analysis of large data sets. Via user interfaces and data handling techniques discussed herein, users can design and implement complicated data analyses and create visualizations to present the results of such analyses, without requiring an understanding the underlying schema, or programming techniques, or the like”).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Kansha, in view of Breuer (DE 10 2020 201 215 A1), and in view of Kim et al. (US 2018/0129369 A1).
Regarding claim 5, Kansha in view of Breuer teaches the method as claimed in claim 1.
Kansha and Breuer do not explicitly teach “wherein the computer outputs at least the first actual variables (I1) of the first number (n1) of data records (D) to the operator, and the computer eliminates individual data records (D) from the first number (n1) of data records (D), so that the eliminated data records (D) are disregarded in the course of ascertaining the definitively selected data records (D).”
Kim further teaches wherein the computer outputs at least the first actual variables (I1) of the first number (n1) of data records (D) to the operator, and the computer eliminates individual data records (D) from the first number (n1) of data records (D), so that the eliminated data records (D) are disregarded in the course of ascertaining the definitively selected data records (D) ([0086]: “The sampling of data in the data pane 315 is selected to provide valuable information to the user”; [0262]: “some implementations enable a user to select one or more data values for a column in the data pane, then right-click and choose 'keep only' or 'exclude.' This inserts a filter into the flow at the currently selected node. The system infers an expression to implement the filter, and the expression is saved”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the method of Kansha in view of Breuer to incorporate the teachings of Kim so as to include the computer-outputting at least the first actual variables (I1) of the first number (n1) of data records (D) to the operator, and the computer eliminating individual data records (D) from the first number (n1) of data records (D), so that the eliminated data records (D) are disregarded in the course of ascertaining the definitively selected data records (D). Doing so would allow an operator to filter data with the aim of disregarding irrelevant data records ([0002-0003]: “Some data sets are very large or complex, and include many data fields. Various tools can be used to help understand and analyze the data, including dashboards that have multiple data visualizations. However, data frequently needs to manipulated or massaged to put it into a format that can be easily used by data visualization applications… Data flow style systems focus the user on the operations and flow of the data through the system, which helps provide clarity on the overall structure of the job, and makes it easy for the user to control those steps. These systems, however, generally do a poor job of showing the user their actual data, which can make it difficult for users to actually understand what is or what needs to be done to their data”).
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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/M.I.K./Examiner, Art Unit 2117
/ROBERT E FENNEMA/Supervisory Patent Examiner, Art Unit 2117
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