DETAILED ACTION
This action is in response to the amendments filed on July 6th, 2026. A summary of this action:
Claims 1, 3-21 have been presented for examination.
Claims not rejected under § 102/103. See the Oct. 2024 Final Action at 2-3 for rationale on why.
Claims 1, 3-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mathematical concept and a mental process without significantly more.
This action is Final
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/Amendments
Regarding the § 101 Rejection
Maintained, updated as necessitated by amendment.
Prior positions maintained by Examiner for the remarks submitted in the previous responses.
With respect to the prong 1 remarks, these remarks are generally conclusory and do not address the detailed analysis of the ordered combination in the rejection, including what particular elements/limitation were identified as abstract, the BRI of them in view of the specification, the rationale on how a person may readily mentally perform them, nor do they address that some elements in the claim were additional to the abstract idea (i.e. not part of the abstract idea the claim is directed to), and analyzed as such.
With respect to the prong 2 remarks, regarding Ex Parte Desjardins, the claims and specification convey no improvement to optimization technology as alleged, e.g. there are no improvements to the genetic algorithm, or to the k-means clustering algorithm, etc. Rather, the specification conveys these are all generic and used in their ordinary capacity.
Furthermore, people readily have long mentally done optimization problems, including for building designs, e.g. the Washington monument. To simply break a complex optimization problem down to simpler ones (¶ 8) is still abstract, even in building design, e.g. an architect designs the building initially, then passes off the frame design, and other parts of the building design that require loading calculations, to a structural engineer professionally licensed to do such a task, then to a civil engineer to do piping, electrical, and other utility routing, etc.
In other words, the alleged improvement is in the abstract idea itself. See MPEP § 2106.04(II)(A)(2): “RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"); Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself.").”
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mathematical concept and a mental process without significantly more.
Step 1
Claim 1 is directed towards the statutory category of a process.
Claim 11 is directed towards the statutory category of an article of manufacture.
Claim 20 is directed towards the statutory category of an apparatus.
Claims 11 and 20, and the dependents thereof, are rejected under a similar rationale as representative claim 1, and the dependents thereof.
Step 2A – Prong 1
The claims recite an abstract idea of both a mental process and mathematical concept.
See MPEP § 2106.04: “...In other claims, multiple abstract ideas, which may fall in the same or different groupings, or multiple laws of nature may be recited. In these cases, examiners should not parse the claim. For example, in a claim that includes a series of steps that recite mental steps as well as a mathematical calculation, an examiner should identify the claim as reciting both a mental process and a mathematical concept for Step 2A Prong One to make the analysis clear on the record.”
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility.
The mathematical concept recited in claim 1 is:
executing at least one unsupervised K-means clustering algorithm to perform one or more first clustering operations based on a plurality of directions associated with a plurality of edges that are included in the set of edges and that correspond to different respective beams to determine a plurality of sets of direction clusters; - math calculations in textual form, akin to those in example 47, claim 3. See the explanation of claim 3, including page 25: “The clustering could be performed using the k-means algorithm either as described in the disclosure or in other ways known to a person having ordinary skill in the art.” Then page 26: “Step (c) requires clustering the embeddings by a k-means clustering algorithm, which is a mathematical calculation”
To clarify on the BRI of the instant claim, ¶ 161: “As persons skilled in the art will recognize, K-means clustering refers to a type of well-known unsupervised learning algorithms that generate a pre-determined number of clusters.”
…
determining a set of weighted equations based on the set of edges and a first base direction included in the first plurality of base directions; - determining math equations/relationships in textual form. To clarify on the BRI, ¶ 173, incl.: “…For instance, in some embodiments, each of the weighted equations is specified in the format of "Ax+ By+ C = 0."…”
…
executing the at least one unsupervised K-means clustering algorithm to perform one or more second clustering operations based on the set of weighted equations to determine an equation cluster set list associated with the first base direction; - math calculations in textual form, akin to those in example 47, claim 3. See the explanation of claim 3, including page 25: “The clustering could be performed using the k-means algorithm either as described in the disclosure or in other ways known to a person having ordinary skill in the art.” Then page 26: “Step (c) requires clustering the embeddings by a k-means clustering algorithm, which is a mathematical calculation”
To clarify on the BRI of the instant claim, ¶ 161: “As persons skilled in the art will recognize, K-means clustering refers to a type of well-known unsupervised learning algorithms that generate a pre-determined number of clusters.”
wherein the iterative sizing application generates a first computer-aided design and a first building objective value associated with the first frame grid based on the frame system specification, and the iterative sizing application transmits the first building objective value to the frame specification application, and wherein the frame specification application processes the first building objective value to generate an additional frame system specification – math calculations in textual form, with a desired result, but for mere instructions to do it on a computer - see ¶¶ 41-43 incl: “…Values of the objective function 134 are also referred to herein collectively as "objective values" and individually as an "objective value." In some embodiments, the structural design application 120 attempts to maximize the objective function 134. In some other embodiments, the structural design application 120 attempts to minimize the objective function 134…”, ¶¶ 68-70, then ¶¶ 75-76 incl.: “…To initiate each subsequent design optimization iteration, the iterative optimization application 172( 1) inputs the building objective value 186( 1) generated by the iterative sizing application 180 during the prior design optimization iteration into the frame specification application 170. In response, the frame specification application 170 inputs the building objective value 186( 1) into the genetic algorithm. The genetic algorithm re-determines the left frame counts and the right frame counts…Instead, the frame specification application 180 configures the genetic algorithm to iteratively and collectively optimize Boolean values for each of the potential frame locations across the potential frame locations sets based on the building objective value 186(1) associated with the prior design optimization iteration (if any)…”; also see ¶ 78: “In some embodiments, the iterative sizing application 180 defines and iteratively solves a nested optimization problem to optimize the sizing of the beams and the columns included in the current structural design based on the constraints 132 and the objective function 134 while taking into account gravity and the building wind load(s).”; and ¶ 30: “To solve the overall optimization design problem, the structural design application 120 executes an overall design flow that dynamically self-adjusts based on results generating while solving the constituent optimization problems.”
Also, ¶ 190: “For instance, in some embodiments, the grid specification engine 490 implements the genetic algorithm that includes, without limitation, B different design variables representing the ranked equation cluster set lists 468. In the same or other embodiments, the genetic algorithm determines the fitness of each combination of the design variables based on the building objective values 186 associated with the structural designs 188 generated based on the combination of the design variables.” – see ¶ 206 as well.
As a point of clarity, the genetic algorithm in the disclosure, unrecited in this claim with no express basis for it in the claim itself, is merely a generic genetic algorithm being invoked to perform the abstract idea, with no asserted improvement to the genetic algorithm itself. See ¶ 134: “For instance, in some embodiments, the multi-floor optimizer 290 executes any number and/or types of genetic algorithms, any number and/or types of harmony search algorithms, any number and/or types of integer optimization algorithms, or any combination thereof to generate the gravity designs 148.” – also see ¶ 218, and elsewhere, i.e. the specification conveys no details on this genetic algorithm itself and what steps it performs itself, but rather is merely using a generic genetic algorithm do the math calculations in textual form.
Under the broadest reasonable interpretation, the claim recites a mathematical concept – the above limitations are steps in a mathematical concept such as mathematical relationships, mathematical formulas or equations, and mathematical calculations. If a claim, under its broadest reasonable interpretation, is directed towards a mathematical concept, then it falls within the Mathematical Concepts grouping of abstract ideas. In addition, as per MPEP § 2106.04(a)(2): “It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989). See, e.g., SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163, 127 USPQ2d 1597, 1599 (Fed. Cir. 2018)”
See MPEP § 2106.04(a)(2).
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility.
The mental process recited in claim 1 is:
A computer-implemented method for generating one or more frame grids for a structural system of a building, the method comprising: - an intended use, which may be mentally performed such as by an evaluation with pen and paper, but for the mere instructions to do it on a computer.
To clarify on the BRI of “frame grid”, ¶ 62: “Each of the frame grids 158(1 )-158(N) includes, without limitation, any number of sets of grid lines (not shown), where each set of grid lines is associated with a different direction. Together, the grid lines specify the allowed locations of the frames of the structural system of the building. For explanatory purposes only, the frame grids 158(1)-158(M) are also referred to herein individually as "the frame grid 158" and collectively as "the frame grids 158” – in other words, this is, at a high level of abstraction, the abstract idea of a person drawing a custom grid with custom grid lines for use in making architectural drawings of a building. See Fletcher, Rachel. "An American Vision of Harmony: Geometric Proportions in Thomas Jefferson’s Rotunda at the University of Virginia." Nexus Network Journal 5 (2003) as discussed below which describes Thomas Jefferson’s performance of such a mental process, including the physical aids he used in the mental process.
In other words, the focus of the claimed advance is the generation of, at a high degree of abstraction, custom graph paper (the frame grids) for building design, but on a computer and using a computer as a tool. Such an abstract idea of using custom graph paper for construction/architectural drawings well predate the invention of the computer (i.e. see Fletcher).
generating a set of edges, wherein each edge in the set of edges corresponds to a different respective beam that is specified in a first computer-aided design and is connected to at least one column specified in the first computer-aided design; - a mental process, but for the mere instructions to do it on a computer.
To clarify, see ¶ 62 as discussed above, then see ¶ 63: “The edge set includes, without limitation, any number of edges (not shown), where each edge corresponds to a beam that is connected to at least one column.” And ¶ 155: “…For each of the gravity designs 148, the grid generation application 150 adds the beams (not shown) that are attached to at least one of the columns (not shown) to the edge set 402 as edges (not shown). Accordingly, the edge set 402 includes, without limitation, any number of edges that each corresponds to a different beam. Each of edges is associated with both a direction and a length.”
A person, e.g. a structural engineer, or an architect for the Empire State Building, would readily be able to observe a design of a building’s structural system, e.g. on the display of a computer or by observing blueprints or similar such drawings of the system, or print-outs from a computer, or by walking through a building under construction and observing the locations of the beams and columns in the building. For example, the person mentally observes a row of columns and associated beams (e.g. floor beams).
The person then proceeds to draw out the edges using pen and paper, or write down a table to tabulate the results of their observations, e.g. a table of rows of beams, wherein each beam has a column entry for a direction and length, or do both, as part of the mental observation, or as a mental evaluation/judgement based on the results of their observation. In this mental process, the person would readily be able to also draw the edges representing the beams corresponding to at least one column, e.g. for each room in a building with columns, the person draws out the edges to represent the beams, and marks with “X” the column locations.
In addition, many building have beams in multiple directions, e.g. perpendicular beams in the floor, wherein a person would readily be able to observe this visually in the manner discussed above. Furthermore, for a simple room/area, e.g. a room with 5 columns and a small number of beams, e.g. a gazebo, a person would readily be able to do this purely mentally by making a mental observation and then mentally visualizing just the beams and the columns that they observe.
executing at least one unsupervised K-means clustering algorithm to perform one or more first clustering operations based on a plurality of directions associated with a plurality of edges that are included in the set of edges and that correspond to different respective beams to determine a plurality of sets of direction clusters; determining a first plurality of base directions based on a first set of direction clusters having a highest ranking among the plurality of sets of direction clusters;- a mental process, but do it on a computer - ¶¶ 63: “As described in greater detail below in conjunction with Figure 4, in some embodiments, the grid generation application 150 implements any number and/or types of unsupervised clustering techniques to generate the frame grids 158.”, and ¶¶ 161-163: “More specifically, in some embodiments, the direction clustering engine 420 includes, without limitation, K-means clustering algorithms 424(1 )-424(0) and a cluster set ranking engine 430. Each of the K-means clustering algorithms 424(1 )-424(0) is a different instance of a K-means clustering algorithm 424 (not explicitly shown) that implements K-means clustering. As persons skilled in the art will recognize, K-means clustering refers to a type of well-known unsupervised learning algorithms that generate a pre-determined number of clusters.” And ¶ 177: “As used herein, an edge is approximately parallel to the base direction 438 when a direction associated with the edge is within a tolerance amount of the base direction 438 (e.g. within 3 degrees of the base direction 438.)” And ¶¶ 166-167: “…In response, the cluster set ranking engine 430 performs any number and/or type of ranking and/or filtering operations on the direction cluster sets 428(1 )-428(0) to generate the ranked direction cluster set list 408…. In some embodiments, the cluster set ranking engine 430 includes, without limitation, an elbow method heuristic 432. The elbow method heuristic 432 is based on the elbow method. As persons skilled in the art will recognize, the elbow method refers to a well-known type of technique for determining an optimal number of clusters (i.e., value of K) into which a set of points can be clustered.
This is a mental process, but for the mere instructions to do it on a computer, as the claim places no restriction on how the clustering is implemented, and the instant disclosure merely describes the use of “well-known” algorithms for implementing these steps.
To clarify, and continuing the above example, the person has a set of drawings and/or tables representing the edges and their associated directions (e.g. a rough sketch of the gird of the beams, and/or a tabular representation of this information).
To clarify, by continuing the above example, the structural engineer may mentally observe their drawings and/or table to observe the directions of the various edges representing beams in the drawing, and then mentally evaluate these edges to cluster (e.g. group) the edges into various clusters (e.g. groups) based on their direction, for example evaluating that a first set of edges are north-to-south, forming a first direction cluster; and evaluating a second set of edges are east-to-west, forming a second direction cluster (and other mental evaluations, such as northwest to southeast, etc.)
Then the structural engineer mentally judges the different clusters to determine a first plurality of base directions, e.g. mentally evaluating the direction clusters to determine the number of edges in each cluster, and then judging the direction clusters based on the number of edges in each cluster, e.g. judging that because a majority of beams are in clusters with a north to south direction, or similar directions (e.g. north-northwest to south-southeast), that these clusters should have a highest rating/ranking. From this judgement, they then mentally judge that the base directions of the blueprints (e.g. orientation of the blueprints) should range from north-northwest to south-southeast, to north-northeast and south-southeast, wherein most of the edges are in the base direction of north-to-south.
To clarify on this, see the July 2024 Subject Matter Eligibility Examples, page 16: “…Next, clustering is performed using a k-means clustering algorithm…”, page 21: “Regarding step (d), the claim does not place any limits on how the embedding vectors are partitioned into clusters corresponding to the different sources. The clustering could be performed using a k-means algorithm as indicated in the disclosure or any other algorithm known to a person of ordinary skill in the art.” Then page 22: “…The claim places no limits on how this partitioning is performed. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example, “partitioning . . . into clusters” encompasses a human arbitrarily selecting groups of vectors and mentally assigning them to clusters…” and page 26: “Step (c) requires clustering the embeddings by a k-means clustering algorithm, which is a mathematical calculation”
determining a set of weighted equations based on the set of edges and a first base direction included in the first plurality of base directions; - a mental evaluation/judgment/observation, such as with the assistance of pen and paper, but for the mere instructions to do it on a computer.. Continuing with the above example, the structural engineer may mentally judge/evaluate the edges to determine a subset of edges (which correspond to beams) in the north-to-south based direction, or do this via a mental observation.
In doing so, the engineer may readily determine a set of simple weighted equations based on such edges and base directions, e.g. “Ax+ By+ C = 0."” (¶ 173) – which the Examiner notes that this is a simple re-arrangement of the equation of a line, i.e. y = mx+b (m being the slope; b being the y-intercept). The simple re-arrangement is y=mx+b = (-Ax-C)/B => -Ax/B – C/B, i.e. -A/B = m; -C/B = b.
executing the at least one unsupervised K-means clustering algorithm to perform one or more second clustering operations based on the set of weighted equations to determine an equation cluster set list associated with the first base direction;- a mental process of clustering, akin to what is described above, wherein the person then, after having performed the clustering by a mental process, then evaluates/judges the results of the clusters so as to draw the first set of grid lines with the first base direction, but for the mere instructions to do it on a computer.
Continuing with the above example, the structural engineer may further mentally observe their blueprints, and cluster the edges in the north-south direction to determine clusters associated with the distances between the edges (which correspond to beams), e.g. observing that a number of edges have approximately 18 inch spacing between the edges, they judge this to be a first cluster of edges, and then observing that there is a second set of edges in the subset that have a 36 inch spacing between the edges, so they judge this to be a second cluster of edges, and so on. From these groups, the engineer further mentally evaluates and the groups and determines that the majority of edges are in the 18 inch spacing and 36 inch spacing groups, so the engineer mentally judges to use north-to-south grid lines with minor grid lines having a spacing representative of 18 inches, and major grid lines having a spacing representative of 36 inches.
To clarify, ¶ 66: “…In some embodiments, each of the frame grids 158 includes a different combination of sets of grid lines for each of the base directions…”
In doing the above mental process, the engineer is readily able to cluster/group equations together into lists, e.g. a list of the equations for the lines of the beams (as discussed above, e.g. y=mx+b), wherein such a list would readily be able to be used to draw a frame grid, e.g. on paper in 2D, it would merely involve, for each equation, plotting the point “b” (the y-intercept), and plotting a second point based on the equation (e.g. let x=2, b= 2, m =1, solve for y), then using a ruler as a physical aid to trace out the line between the two points. This may also readily be done 3D on paper, by drawing out a 3D grid on the 2D paper (as engineers commonly do, and have long-done since at least the discovery of the cartesian coordinate system (the coordinate system with coordinates of x, y, and z)), or a computer may be used as a tool to implement this abstract idea.
generating a first frame grid for the structural system of the building based on a first plurality of grid lines that is associated with the equation cluster set list and a second plurality of grid lines that is associated with a second base direction included in the first plurality of base directions; – a mental process of mental evaluations/judgments/observations, such as with pen and paper, but for the mere instructions to do it on a computer. To clarify on the BRI of “frame grid”, ¶ 185: “Each of the frame grids 158 includes, without limitation, a different combination of B sets of grid lines, where each combination of B sets of grid lines includes a set of grid lines for each of the base directions 438(1 )-438(8). The grid specification engine 490 can generate the frame grids 158 in any technically feasible fashion.” – continuing the above, the engineer repeats the second clustering to determine a second plurality of grid lines in a second base direction, e.g. east-to-west, and then the engineer draws their frame grid using pen and paper. Graphing paper would be a valuable aid in doing this, as would a ruler, given they are drawing a grid.
Should they need to do multiple sets of grid lines in varying directions, they would readily be able to make each set on translucent paper for each direction, and layering them for each direction that they wish to later refer back to.
With respect to the equations, see the above discussion. In view of the specification, ¶ 173, as discussed above, this is merely drawing out lines based on a formula such as y=mx+B, the well-known formula for a straight line in an x-y coordinate system.
As a point of clarity, the Examiner notes that the claim places no limits on the simplicity of the building that this may be applied to, e.g. the above is all a mental process readily performable for a simple building, e.g. a dog house; and the Examiner also notes that buildings such as the Empire State Building were constructed well-before the invention of the computer based on architectural drawings, i.e. such a mental process is readily performable with a more complex building, although it may require a team of engineers to create the drawings, but such teams were presumably common for building design as numerous extremely complex buildings were designed and constructed without the aid of computers, e.g. the Empire State Building, the Cathedral of Notre Dame, etc.
Furthermore, in view of the Oct. 2019 PEG Appendix I, page 21, “e.g., scientists and engineers have been solving the Arrhenius equation in their minds since it was first proposed in 1889.”, the Examiner also notes that the mental process of making custom grids for use in architectural design predates the computer. See Fletcher, Rachel. "An American Vision of Harmony: Geometric Proportions in Thomas Jefferson’s Rotunda at the University of Virginia." Nexus Network Journal 5 (2003): 7-50. This discusses Thomas Jefferson’s design for the University of Virginia (see abstract), and see page 24: “Jefferson produced floor plans and elevations in ink on grid paper at a scale of 1˝= 10´, with each square on the grid equal to one square foot... Though not immediately apparent, Jefferson’s drawings contain pencil lines, erasures and other “hidden” markings that provide valuable information about the design process. In some instances, Jefferson scored or pricked the paper with guidelines, a common practice in eighteenth-century Virginia. Such lines and arcs, produced with a straightedge, compass or divider, offer insight into Jefferson’s methods for laying out building components; markings such as these can be observed on Jefferson’s original drawings or in high-resolution electronic images available through Electronic Collections at the University of Virginia Library [Jefferson 1995b]...” and page 33 including: “…Although he drafted his designs on graph paper, the plans do not generally conform to the whole number increments of the grid. Where he resorts to complex fractions, they are sometimes calculated to five or more decimal places [McLaughlin 1988, 82]. Furthermore, Jefferson drafted his plans with a drawing compass and ruling pen, sometimes scoring the paper with lines and arcs that served as geometric guidelines….”– and see the reproductions of Thomas Jefferson’s drawings for more clarity on this.
wherein a frame specification application within the iterative optimization application processes the first frame grid to generate a frame system specification… wherein the iterative sizing application generates a first computer-aided design and a first building objective value associated with the first frame grid based on the frame system specification, and the iterative sizing application transmits the first building objective value to the frame specification application, and wherein the frame specification application processes the first building objective value to generate an additional frame system specification - a mental trial-and-error process of routine design experimentation, but do it in a computer environment, e.g. the engineers observing the frame grid, and mentally judging how to optimize it (or optimize the design of a building drawn on it), and do this repeatedly in a mental trial-and-error process using physical aids, but do it on a computer with a generic genetic algorithm (see instant disclosure as discussed above for this) used as a tool to automate this. Scoring building designs is readily done mentally, with a simple scoring function, e.g. a simple rubric such as assigning a number of 1-5 for a plurality of objectives (e.g. aesthetics, cost, estimated time to build, etc.) and simple aggregations of the ratings with simple equations, e.g. an average or weighted average of the score.
To further clarify, see ¶ 53 – the frame specification is merely specify frames for a building (e.g. the beams and columns of a building), something a person such as an architect or civil engineer is readily able to mentally do, e.g. using the frame grid (the custom grid lines) such as on custom graph paper, a person is readily able to observe/evaluate the frame grid and generate a frame specification for the building. The iterative sizing is then merely a mental trial-and-error process of a person generating a design of a building, but for the mere instructions to do it in a computer environment, and scoring the design with an objective function, e.g. evaluating that it has a 75% objective value, then evaluating how to improve the design in this mental trial-and-error process, so they generate another frame specification mentally (i.e. the columns and beams of the building).
As to the specifications discussion of doing this and taking into account vertical and lateral loads, this is no less abstract. Structural engineers have long done this mentally, e.g. to build buildings such as the Empire State building, the Chesapeake bay bridge, RFK stadium, etc.
The Examiner also notes such an abstract idea (when read in view of the disclosure) is also akin to a design competition to design a building, e.g. the Washington Monument, wherein engineers/teams of engineers competed against each other to create a plurality of designs for the Washington Monument, and a team of judges mentally judged which one was the best, and this is the one presently erected on the US National Mall. A brief history of this competition is discussed in Edwards, “The Washington National Monument – A National Contest for a National Monument”, Nov. 2020, The Unwritten Record, US National Archives, URL: unwritten-record(dot)blogs(dot)archives(dot)gov/2020/11/24/the-washington-national-monument-a-national-contest-for-a-national-monument/ - include seeing the various drawings resultant from the competition. To do so iteratively would simply be routine mental trial-and-error optimization, e.g. in Edwards Record Group 42 there is the “winning sketch of the Washington National Monument”, however this was not the finalized design as readily visibly apparent (e.g. there is no building at the bottom of the monument such as the one that was sketched), i.e. later iterations of the design removed such features. And such scoring is also presumably done in design competitions such as was done for the Washington Monument to ensure transparency into the judges final ratings.
Under the broadest reasonable interpretation, these limitations are process steps that cover mental processes including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of physical aids but for the recitation of a generic computer component. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the "Mental Process" grouping of abstract ideas. A person would readily be able to perform this process either mentally or with the assistance of physical aids. See MPEP § 2106.04(a)(2).
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility. In particular, with respect to the physical aids, see example # 45, analysis of claim 1 under step 2A prong 1, including: “Note that even if most humans would use a physical aid (e.g., pen and paper, a slide rule, or a calculator) to help them complete the recited calculation, the use of such physical aid does not negate the mental nature of this limitation.”; also see example # 49, analysis of claim 1, under step 2A prong 1: “Moreover, the recited mathematical calculation is simple enough that it can be practically performed in the human mind. Even if most humans would use a physical aid, like a pen and paper or a calculator, to make such calculations, the use of a physical aid would not negate the mental nature of this limitation.”
As such, the claims recite an abstract idea of a mental process and a math concept
Step 2A, prong 2
The claimed invention does not recite any additional elements that integrate the judicial exception into a practical application. Refer to MPEP §2106.04(d).
The following limitations are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f), including the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more”:
Claim 1: computer-implemented
Claim 11: One or more non-transitory computer readable media including instructions that, when executed by one or more processors, cause the one or more processors
Claim 20: A system comprising: one or more memories storing instructions; and one or more processors coupled to the one or more memories that, when executing the instructions, perform the steps of:
…computer-aided… - given the generality recited in the present claims, the recitations of the design being “computer-aided” are considered part of the mere instructions to do it on a computer, including the optimization steps. MPEP § 2106.05(f): “Intellectual Ventures I v. Capital One Fin. Corp., 850 F.3d 1332, 121 USPQ2d 1940 (Fed. Cir. 2017), the steps in the claims described "the creation of a dynamic document based upon ‘management record types’ and ‘primary record types.’" 850 F.3d at 1339-40; 121 USPQ2d at 1945-46. The claims were found to be directed to the abstract idea of "collecting, displaying, and manipulating data." 850 F.3d at 1340; 121 USPQ2d at 1946. In addition to the abstract idea, the claims also recited the additional element of modifying the underlying XML document in response to modifications made in the dynamic document. 850 F.3d at 1342; 121 USPQ2d at 1947-48. Although the claims purported to modify the underlying XML document in response to modifications made in the dynamic document, nothing in the claims indicated what specific steps were undertaken other than merely using the abstract idea in the context of XML documents. The court thus held the claims ineligible, because the additional limitations provided only a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words "apply it". 850 F.3d at 1341-42; 121 USPQ2d at 1947-48 (citing Electric Power Group., 830 F.3d at 1356, 1356, USPQ2d at 1743-44 (cautioning against claims "so result focused, so functional, as to effectively cover any solution to an identified problem"))”
Should it be found that the execution of the unsupervised K-means clustering algorithm is not part of the abstract idea, then these would be considered as part of the mere instructions to do it on the computer. ¶ 161: “As persons skilled in the art will recognize, K-means clustering refers to a type of well-known unsupervised learning algorithms that generate a pre-determined number of clusters.”
In addition, the Examiner also notes that the recitations of executing the K-means clustering algorithm and using a genetic algorithm are also readily considered as generally linking the abstract idea to a particular technological environment. MPEP § 2106.05(h): “The court identified the claimed concept of providing out-of-region access to regional broadcast content as an abstract idea, and noted that the additional elements limited the wireless delivery of regional broadcast content to cellular telephones (as opposed to any and all electronic devices such as televisions, cable boxes, computers, or the like). 838 F.3d at 1258-59, 120 USPQ2d at 1204. Although the additional elements did limit the use of the abstract idea, the court explained that this type of limitation merely confines the use of the abstract idea to a particular technological environment (cellular telephones) and thus fails to add an inventive concept to the claims. 838 F.3d at 1259, 120 USPQ2d at 1204” – to clarify on the genetic algorithm, see ¶ 134 and its listing of other algorithms that may be used. See ¶¶ 132 as well, see fig. 5 # 550 (to clarify, note its # 170 – see fig. 1 # 170, as compared to the outputs of # 168). Then see ¶ 75: “To initiate each subsequent design optimization iteration, the iterative optimization application 172( 1) inputs the building objective value 186( 1) generated by the iterative sizing application 180 during the prior design optimization iteration into the frame specification application 170. In response, the frame specification application 170 inputs the building objective value 186( 1) into the genetic algorithm.”
The recitations of “grid generation application”, “iterative optimization application”, “iterative sizing application”, and similar such terms are considered as part of the mere instructions to invoke a computer and generic computer components as a tool to perform the abstract idea.
With respect to the unrecited feature of the genetic algorithm in the disclosure: the genetic algorithm is part of the mere instructions to automate the abstract idea with a generic computer and commonplace software on the computer, e.g. see ¶ 134: “For instance, in some embodiments, the multi-floor optimizer 290 executes any number and/or types of genetic algorithms, any number and/or types of harmony search algorithms, any number and/or types of integer optimization algorithms, or any combination thereof to generate the gravity designs 148” – see the August 2025 memorandum, footnote 17 for Recentive Analytics, and see the listing of generic algorithms quoted in the opinion of Recentive. The instant disclosure conveys merely that any number/type of genetic algorithm may be used as tool to automate the mental process. To clarify, the disclosure does not convey any particular genetic algorithm let alone any particular manner in which it actually is implemented in this particular context (see MPEP § 2161(I) for Finisar Corp. v. DirecTV Grp., Inc., 523 F.3d 1323, 1340, 86 USPQ2d 1609, 1623 (Fed. Cir. 2008) for a definition of an algorithm), but rather merely describes it generically as a tool with intended/desired results produced by it.
Should it be found that the iterative optimization steps using the genetic algorithm are not part of the abstract idea, then the Examiner notes that these would be token post-solution activities to the abstract idea of the generation of the frame grid(s).
The transmitting steps of claim 1 are considered as a token extra-solution activities of mere data transmission. See MPEP § 2106.05(g).
A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. See MPEP § 2106.04(d).
MPEP 2106.04(II)(A)(2) “…Instead, under Prong Two, a claim that recites a judicial exception is not directed to that judicial exception, if the claim as a whole integrates the recited judicial exception into a practical application of that exception. Prong Two thus distinguishes claims that are "directed to" the recited judicial exception from claims that are not "directed to" the recited judicial exception…Because a judicial exception is not eligible subject matter, Bilski, 561 U.S. at 601, 95 USPQ2d at 1005-06 (quoting Chakrabarty, 447 U.S. at 309, 206 USPQ at 197 (1980)), if there are no additional claim elements besides the judicial exception, or if the additional claim elements merely recite another judicial exception, that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"); Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself."). For a claim reciting a judicial exception to be eligible, the additional elements (if any) in the claim must "transform the nature of the claim" into a patent-eligible application of the judicial exception, Alice Corp., 573 U.S. at 217, 110 USPQ2d at 1981, either at Prong Two or in Step 2B” and MPEP § 2106(I): “Mayo, 566 U.S. at 80, 84, 101 USPQ2dat 1969, 1971 (noting that the Court in Diamond v. Diehr found “the overall process patent eligible because of the way the additional steps of the process integrated the equation into the process as a whole,”” – and see MPEP § 2106.05(e).
To further clarify, MPEP § 2106.04(II)(A)(1): “Alice Corp., 573 U.S. at 216, 110 USPQ2d at 1980 (citing Mayo, 566 US at 71, 101 USPQ2d at 1965). Yet, the Court has explained that ‘‘[a]t some level, all inventions embody, use, reflect, rest upon, or apply laws of nature, natural phenomena, or abstract ideas,’’ and has cautioned ‘‘to tread carefully in construing this exclusionary principle lest it swallow all of patent law” See also Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335, 118 USPQ2d 1684, 1688 (Fed. Cir. 2016) ("The ‘directed to’ inquiry, therefore, cannot simply ask whether the claims involve a patent-ineligible concept, because essentially every routinely patent-eligible claim involving physical products and actions involves a law of nature and/or natural phenomenon").”
The claimed invention does not recite any additional elements that integrate the judicial exception into a practical application. Refer to MPEP §2106.04(d).
Step 2B
The claimed invention does not recite any additional elements/limitations that amount to significantly more.
The following limitations are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f), including the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more”:
Claim 1: computer-implemented
Claim 11: One or more non-transitory computer readable media including instructions that, when executed by one or more processors, cause the one or more processors
Claim 20: A system comprising: one or more memories storing instructions; and one or more processors coupled to the one or more memories that, when executing the instructions, perform the steps of:
…computer-aided… - given the generality recited in the present claims, the recitations of the design being “computer-aided” are considered part of the mere instructions to do it on a computer, including the optimization steps. MPEP § 2106.05(f): “Intellectual Ventures I v. Capital One Fin. Corp., 850 F.3d 1332, 121 USPQ2d 1940 (Fed. Cir. 2017), the steps in the claims described "the creation of a dynamic document based upon ‘management record types’ and ‘primary record types.’" 850 F.3d at 1339-40; 121 USPQ2d at 1945-46. The claims were found to be directed to the abstract idea of "collecting, displaying, and manipulating data." 850 F.3d at 1340; 121 USPQ2d at 1946. In addition to the abstract idea, the claims also recited the additional element of modifying the underlying XML document in response to modifications made in the dynamic document. 850 F.3d at 1342; 121 USPQ2d at 1947-48. Although the claims purported to modify the underlying XML document in response to modifications made in the dynamic document, nothing in the claims indicated what specific steps were undertaken other than merely using the abstract idea in the context of XML documents. The court thus held the claims ineligible, because the additional limitations provided only a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words "apply it". 850 F.3d at 1341-42; 121 USPQ2d at 1947-48 (citing Electric Power Group., 830 F.3d at 1356, 1356, USPQ2d at 1743-44 (cautioning against claims "so result focused, so functional, as to effectively cover any solution to an identified problem"))”
Should it be found that the execution of the unsupervised K-means clustering algorithm is not part of the abstract idea, then these would be considered as part of the mere instructions to do it on the computer. ¶ 161: “As persons skilled in the art will recognize, K-means clustering refers to a type of well-known unsupervised learning algorithms that generate a pre-determined number of clusters.”
In addition, the Examiner also notes that the recitations of executing the K-means clustering algorithm and using a genetic algorithm are also readily considered as generally linking the abstract idea to a particular technological environment. MPEP § 2106.05(h): “The court identified the claimed concept of providing out-of-region access to regional broadcast content as an abstract idea, and noted that the additional elements limited the wireless delivery of regional broadcast content to cellular telephones (as opposed to any and all electronic devices such as televisions, cable boxes, computers, or the like). 838 F.3d at 1258-59, 120 USPQ2d at 1204. Although the additional elements did limit the use of the abstract idea, the court explained that this type of limitation merely confines the use of the abstract idea to a particular technological environment (cellular telephones) and thus fails to add an inventive concept to the claims. 838 F.3d at 1259, 120 USPQ2d at 1204” – to clarify on the genetic algorithm, see ¶ 134 and its listing of other algorithms that may be used. See ¶¶ 132 as well, see fig. 5 # 550 (to clarify, note its # 170 – see fig. 1 # 170, as compared to the outputs of # 168). Then see ¶ 75: “To initiate each subsequent design optimization iteration, the iterative optimization application 172( 1) inputs the building objective value 186( 1) generated by the iterative sizing application 180 during the prior design optimization iteration into the frame specification application 170. In response, the frame specification application 170 inputs the building objective value 186( 1) into the genetic algorithm.”
The recitations of “grid generation application”, “iterative optimization application”, “iterative sizing application”, and similar such terms are considered as part of the mere instructions to invoke a computer and generic computer components as a tool to perform the abstract idea.
With respect to the unrecited feature of the genetic algorithm in the disclosure: the genetic algorithm is part of the mere instructions to automate the abstract idea with a generic computer and commonplace software on the computer, e.g. see ¶ 134: “For instance, in some embodiments, the multi-floor optimizer 290 executes any number and/or types of genetic algorithms, any number and/or types of harmony search algorithms, any number and/or types of integer optimization algorithms, or any combination thereof to generate the gravity designs 148” – see the August 2025 memorandum, footnote 17 for Recentive Analytics, and see the listing of generic algorithms quoted in the opinion of Recentive. The instant disclosure conveys merely that any number/type of genetic algorithm may be used as tool to automate the mental process. To clarify, the disclosure does not convey any particular genetic algorithm let alone any particular manner in which it actually is implemented in this particular context (see MPEP § 2161(I) for Finisar Corp. v. DirecTV Grp., Inc., 523 F.3d 1323, 1340, 86 USPQ2d 1609, 1623 (Fed. Cir. 2008) for a definition of an algorithm), but rather merely describes it generically as a tool with intended/desired results produced by it.
Should it be found that the iterative optimization steps using the genetic algorithm are not part of the abstract idea, then the Examiner notes that these would be token post-solution activities to the abstract idea of the generation of the frame grid(s).
The transmitting steps of claim 1 are considered as a token extra-solution activities of mere data transmission. See MPEP § 2106.05(g). See MPEP § 2106.05(g). This is WURC in view of MPEP § 2106.05(d)(II).
In addition, the use of grids in CAD technology is WURC in view of:
Sacks et al., “Parametric 3D modeling in building construction with examples from precast concrete”, 2004, § 2.2, including: “ However, exploitation of the power of this capability has evolved slowly, as knowledge of desired CAD system behavior has grown, and as the significant computing power required for the complex computations necessary to derive assemblies of shapes automatically has become more readily available. In order to define assemblies of shapes, people utilized additional capabilities: in addition to solid shapes, they relied on 2-D shapes for grid lines, dimensions and other construction elements [7]. Grid lines allowed definition of the location of solids relative to them (on or offset from grid intersections). Dimensions provided controls for varying the shapes of the primitives that that were added and subtracted to construct a solid model… Parametrics greatly expanded the ease of use of solid modeling… For building design, this means that instead of composing a building assembly as a collection of instances of typical parts with fixed geometry, the geometry of each part can be derived from the spatial relationships between it, its neighbors and the building grid. In this way, changes to any of the parameters defining grids or spacing can be propagated to all the parts automatically” – also see § 4.5: “A parametric building modeling system, as outlined up to this point, would provide all the functionality needed to quickly define a building design. For example, in the case of a precast concrete structure, a designer could establish a grid, select and insert building elements relative to the grid, size all the pieces, select and place connections, set reinforcing parameters for each part, layout external systems that intersect with precast pieces and so forth. The model can then be adjusted by changing parameter values at any level—any geometric adaptation required to maintain integrity is handled automatically by the system” For additional evidence, also see:
AutoDesk, “Video: Add Grid Lines”, accessed May 2024, URL: help(dot)autodesk(dot)com/view/RVT/2022/ENU/?guid=GUID-A529C10A-F22F-4919-A7B3-B1847A498004, section “Transcript”: “Grid lines are datums that are used as references or guidelines for a building model. Creating a framework of grid lines early in the project can help you as you develop your model. To place a grid line, on the Architecture tab, click Grid. On the draw panel, select the placement type. Grid lines can be straight segments or arc segments. The Multi-Segment tool lets you place a grid made up of more than one segment, such as a grid line with a small jog in it.”
Rose Barfield, “Grids in BricsCAD® BIM”, Blog Posting, Jan. 15th, 2019, URL: www(dot)bricsys(dot)com/en-us/blog/grids-in-bricscad-bim – see “The Basics” including “Once created grids are invaluable for creating complex designs.”
Gross, Mark D. "Grids in Design and CAD." Proceedings of Association for Computer Aided Design in Architecture (1991): 1-11. Abstract: “The grid is a useful device for expressing design rules about the placement of elements in a layout. By expressing position rules for elements in relation to a grid, a designer can organize decisions in a layout design problem systematically. Grids and placement rules offer a discipline that can help a designer work effectively to lay out complex designs, and it can also facilitate group design work” and § 1 ¶¶ 1-2 including: “The grid, one of the oldest architectural design tools, is a useful device for controlling the position of building elements. Grids have been and continue to be used in all manner of layout tasks from urban design to building construction (see figure 1) . A grid can help a designer control the positions of built and space elements, making the layout task more systematic. By determining positions of different building elements in relation to a grid or to a set of grids, the designer can specify design rules that describe a typology of physical forms…Most Computer-Assisted Drafting (CAD) programs offer a simple grid capability, where a designer can overlay a grid on a drawing, and can snap points and other graphic elements to the grid...” then see § 2: “In layout design a grid is most often used as an underlay to a drawing, to organize the positions of elements. The grid-size is chosen carefully. It is usually related to the dimensions of the spaces to be laid out or the components to be placed. For example, in laying out wood framing members in a stick-built dwelling, a 16" or 24" grid is useful because in that system 16" or 24" is the on-center spacing between studs and joists, and other components in the construction system are compatibly sized.” Then § 2.2: “Grids need not be square. More often than not the landscape, building system, or the directionality of the design itself suggests a rectangular grid. A common use of a rectangular grid is to position members of a directional structural system, for example the post and beam construction in figure 5.” – also see §§ 2.4-2.5
In addition, the optimization using genetic algorithms is also considered WURC, in view of:
Mangal, Mohit, and Jack CP Cheng. "Automated optimization of steel reinforcement in RC building frames using building information modeling and hybrid genetic algorithm." Automation in Construction 90 (2018): 39-57. See the abstract, then see § 2 ¶ 1 which discusses several works of prior art that used a “genetic algorithm” for optimization in building design
Kwak, Hyo-Gyoung, and Jieun Kim. "An integrated genetic algorithm complemented with direct search for optimum design of RC frames." Computer-Aided Design 41.7 (2009): 490-500. Abstract, then see § 1 ¶¶ 4-5; then see § 2 and its subsections
Caldas, Luisa Gama, and Leslie K. Norford. "A design optimization tool based on a genetic algorithm." Automation in construction 11.2 (2002): 173-184. § 1 second to last paragraph, then see § 4
Es-Haghi, Mohammad Sadegh, Aydin Shishegaran, and Timon Rabczuk. "Evaluation of a novel Asymmetric Genetic Algorithm to optimize the structural design of 3D regular and irregular steel frames." Frontiers of Structural and Civil Engineering 14 (2020): 1110-1130. Abstract, then see § 1 ¶¶ 2-5
Turrin, Michela, Peter Von Buelow, and Rudi Stouffs. "Design explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms." Advanced Engineering Informatics 25.4 (2011): 656-675. Abstract, then see § 6 ¶ 2 on page 662: “Among the stochastic techniques, they include evolutionary algorithms such as genetic algorithms, ant colony systems, particle swarm, shuffled frog leaping, memetic algorithms and others. The use of stochastic optimization processes for conceptual design in architecture has been applied in various areas…”
The claimed invention is directed towards an abstract idea of a mathematical concept, mental process, and certain methods of organizing human activity without significantly more.
Regarding the dependent claims
Claim 3 recites additional steps in both the mental process and the mathematical concept, wherein the mathematical concept is claimed with such generality that it does not preclude a person from mentally evaluating the math, wherein the additional elements do not integrate the claimed invention into a practical application or amount to significantly more. To be specific:
The step of “determining a plurality of weighted directions…” is considered as a mental step, e.g. ta person making a mental observation of the edges to determine directions, and then making mental judgements/evaluations of these edges to weight them, e.g. ¶ 158: “The base direction engine 410 then weights each of the directions based on the total length of the non-boundary edges in the direction and the total length of the boundary edges in the direction to generate a corresponding weighted direction (not shown).” – e.g. by making observations, such as with the aid of a ruler and pen and paper, and then taking a ratio of these total lengths so as to mentally evaluate the weight for each direction.
The steps of “executing a clustering algorithm on the plurality of weighted directions for each clustering setting included in a plurality of clustering settings to generate a plurality of sets of direction clusters; executing an elbow method heuristic on the plurality of sets of direction clusters to determine an elbow point;” are considered part of the math concept as discussed above, and for similar reasons as discussed above for similar limitations in claim 1, and should this be found not to be part of the abstract idea then this would be part of the mere instructions to apply a computer as a tool to perform the recited abstract idea, specifically the mental step of performing the first clustering operations as discussed above with respect to claim 1, as well as mere instructions to apply the abstract idea on a computer, as well as generally linking the judicial exception to the technological environment of computers, wherein these are also considered as well-understood, routine, and conventional activities in view of the instant disclosure, ¶ 161: “As persons skilled in the art will recognize, K-means clustering refers to a type of well-known unsupervised learning algorithms that generate a pre-determined number of clusters” and ¶ 167: “As persons skilled in the art will recognize, the elbow method refers to a well-known type of technique for determining an optimal number of clusters (i.e., value of K) into which a set of points can be clustered.”
The step of “computing the first plurality of base directions…” is considered as both a mental process step of an evaluation, as well as a mathematical calculation recited in textual form (wherein the calculation is recited with enough generality that it does not preclude it from being mentally performed).
Claim 14 is rejected under a similar rationale as claim 3
Claim 4 is considered as a mental process of a mental evaluation/judgment followed by a mental judgment/opinion – e.g. a person mentally observing a chart which shows an accuracy or error metric for each set of clusters, as compared to the number of clusters, such as on the display of a computer or on print-outs from a computer, and mentally observing/judging an elbow point on said chart (e.g. an inflection point), wherein the set of clusters nearest to this point is mentally judged to be highest ranked.
Claim 15 is rejected under a similar rationale
The Examiner also notes that this is a well-understood, routine, and conventional activity in view of ¶ 167 of the instant disclosure: “As persons skilled in the art will recognize, the elbow method refers to a well-known type of technique for determining an optimal number of clusters (i.e., value of K) into which a set of points can be clustered”. To clarify on what is involved in this “well-known” technique, see:
Also see previously cited Schubert et al., “Stop using the elbow criterion for kmeans”, § 3: “…In a data set with very well-separated clusters, we expect to initially see a sharp drop until some optimum" number of clusters, afterwards we are splitting true" clusters, which leads to much smaller gains. And indeed, on certain toy data sets, this appears to work well. In Figure 1a we have a data set with three well-separated clusters, that is easily clustered by k-means. Figure 1f is the corresponding elbow plot, with a clear inflection at the desired k = 3….” And §§ 3.1-3.2
See previously cited Badvelu et al., “Determining Optimal Distribution Centers locations using Weighted K-Means”, 2020, section “In cluster analysis, the elbow method is a heuristic used in determining the optimal number of clusters in a data set. The Within-Cluster-Sum of Squared Errors (SSE) for different values of ‘k’ is calculated . For whichever ‘k’ value the WSS becomes first starts to diminish, that particular ‘k’ is chosen. Typically, the K value where it forms an elbow shape is considered as an optimal value” – include seeing the charts in these references for additional clarification
Claim 5 recites both a mental process and a mathematical concept, wherein the mathematical concept is claimed with such generality that it does not preclude a person from mentally evaluating the math.
The step of “determining a first subset of weighted equations…” is considered as both a mental process step of a mental evaluation/judgment, e.g. a person judging what equations to use based on observing the edges, and as a mathematical equations or mathematical relationships in textual form (as the claim is determining a set of equations). See ¶ 173: “…For instance, in some embodiments, each of the weighted equations is specified in the format of "Ax+ By+ C = 0."…”, wherein the Examiner notes with a simple re-arrangement, this is in the form of an equation of a line, i.e. y=mx+b (the re-arrangement: By = -Ax-C => y = -(A/B)x – C/B => m=-A/B, b = -C/B), i.e. the person is mentally judging to use the equation of a line to fit “edges” representing beams, i.e. use the equation of a line to fit rectangular objects of beams, represented by edges/lines.
The step of “executing a first unsupervised K-means clustering algorithm on the first subset of weighted equations to generate a plurality of equation clusters included in the equation cluster set list” is rejected under a similar rationale as the similar limitations found in claim 1
The step of “generating the first plurality of grid lines based on the plurality of equation clusters” is considered as a mental process step of a mental evaluation/judgment, akin to the ones discussed above for the independent claims.
Claim 13 is rejected under a similar rationale as claim 5
Claim 6 recites a mathematical concept in textual form of mathematical equations and/or relationships being determined/generated, wherein the mathematical equations/relationships are recited with such generality that they do not preclude a person from mentally evaluating the math. In addition, this is also considered as a series of mental judgments, such as an engineer judging what equations to use. See the discussion of ¶ 173 above for claim 5 to clarify on the equation.
Claim 7 further limits the mental process. The additional elements in the claim are similar to the ones recited in the independent claim and rejected under a similar rationale.
Claim 16 is rejected under a similar rationale
Claim 8 is considered as further limiting the mental process as was discussed above (e.g. the building is the Empire State Building), wherein should this be found to not be part of the abstract idea this would be generally linking to a field of use/technological environment
Claim 17 is rejected under a similar rationale
Claim 9 is reciting another portion of the mental process of a mental observation/evaluation/judgement. To clarify, this would be akin to using a protractor to mentally judge/evaluate/observe if the edges are all in approximately the same direction, e.g. 5 degrees of a direction of 180 degrees, wherein when the tolerance amount is a large number, e.g. 30 degrees, a person would readily be able to do this purely mentally as a mental observation
Claim 18 is rejected under a similar rationale
Claim 10 is reciting another step in the mental process of a mental evaluation/judgment, akin to the ones discussed above for claim 1
Claim 19 is rejected under a similar rationale
Claim 12 recites another step in the mental process of a series of mental evaluations/judgements. The additional elements in the claim are similar to the ones recited in the independent claim and rejected under a similar rationale. To clarify, the determining of at least two groups would be mental observations/evaluations/judgements akin to the ones discussed above for claim 1, and the determining the set of edges from a union of the at least two groups of edges is mentally observing that the two groups are connected together, e.g. observing where the edges of the groups meet
Claim 21 – this is considered as adding mental steps to the abstract idea, akin to those found in claim 1 (the generation of the frame system specification based on the objective value), in the above noted mental trial-and-error process, wherein the use of the genetic algorithm in this is rejected under the rationale discussed above for it.
The claimed invention is directed towards an abstract idea of a mathematical concept, mental process, and certain methods of organizing human activity without significantly more.
Conclusion
THIS ACTION IS MADE FINAL. 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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/David A Hopkins/Primary Examiner, Art Unit 2188
Prosecution Insights