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 .
Response to Amendment
This communication is in response to the amendment filed on 6 May 2026.
Claims 1 and 17-18 are amended.
Claims 1-2, 5-12, and 16-21 have been examined.
Response to Arguments
In response to Applicant’s remarks filed on 6 May 2026:
a. Rejections of the pending claims under 35 U.S.C. 112(a) are withdrawn in view of Applicant's amendments and arguments.
b. Applicant's arguments with respect to the 35 U.S.C. 101 rejections of the pending claims have been fully considered but are not deemed persuasive.
On pages 11-16 of Applicant’s remarks, Applicant argues against the 35 U.S.C. 101 rejections of the pending claims. Applicant argues that claim 1 does not recite an abstract idea under Step 2A, Prong One; does recite a practical application under Step 2A, Prong Two; and/or does recite significantly more than an abstract idea under Step 2B.
The Office respectfully disagrees with the above remarks. With regards to the analysis at Step 2A, Prong One; Applicant cites paragraphs 0150-0152 of the instant specification, and in particular, Table 2. Applicant points out the size of the datasets described in Table 2 and concludes “A human cannot possibly classify molecules in consideration of all these numbers of nodes and edges and further in view of 37
number of node types representing atom types” and “a human cannot analyze electron density, binding affinity, and interactions with proteins” (remarks, page 13, first paragraph). Applicant is advised of the following:
“Claims in a pending application must be ‘given their broadest reasonable interpretation consistent with the specification.’” MPEP § 2111 citing Phillips v. AWH Corp., 415 F.3d 1303, 1316, 75 USPQ2d 1321, 1329 (Fed. Cir. 2005)..
“Though understanding the claim language may be aided by explanations contained in the written description, it is important not to import into a claim limitations that are not part of the claim. For example, a particular embodiment appearing in the written description may not be read into a claim when the claim language is broader than the embodiment.” Superguide Corp. v. DirecTV Enterprises, Inc., 358 F.3d 870, 875, 69 USPQ2d 1865, 1868 (Fed. Cir. 2004). See also Liebel-Flarsheim Co. v. Medrad Inc., 358 F.3d 898, 906, 69 USPQ2d 1801, 1807 (Fed. Cir. 2004). See MPEP § 2111.01.
With regards to subject matter eligibility analysis, “It is essential that the broadest reasonable interpretation (BRI) of the claim be established prior to examining a claim for eligibility. The BRI sets the boundaries of the coverage sought by the claim and will influence whether the claim seeks to cover subject matter that is beyond the four statutory categories or encompasses subject matter that falls within the exceptions.” MPEP 2106(II).
Applicant’s argument with respect to the analysis at Step 2A, Prong One is unpersuasive because what is being argued is narrower than what is claimed. The BRI of claim 1 does not require classifying any molecules, electron density, binding affinity, or interactions with proteins. These are all limitations improperly imported from the specification into the claim. Claim 1 recites a “classification task” that is generic and unrestricted. Under the BRI, this classification task can be as simple as classifying an image as depicting a dog or cat, or classifying a text passage as having positive or negative sentiment, for example. Such a classification task amounts to no more than evaluation(s)/judgement(s) and is mentally performable by a human with the aid of pencil and paper. Hence, the claimed performance of a classification task is also an abstract idea under the “Mental Processes” grouping.
With regards to the analysis at Step 2A, Prong Two and Step 2B; Applicant makes analogy to the McRo ruling (remarks, pages 13-16) and concludes the following:
“As with McRO, the present claims are directed to a computerized process based on a set of rules that were not previously performed in the art (as acknowledged by the Office Action). Therefore, the present claims provide the technological benefit similar to the benefit realized in McRO, that is, improving accuracy in generating an embedding representation and automatically performing a predetermined graph task. Accordingly, Applicant submits that the claims are not directed to an abstract idea, and Applicant further submits that the claims integrate any alleged abstract idea into a practical application and/or amount to significantly more than any alleged abstract idea, by improving the technical field of graph embedding and tasks in a computerized system implementing rules not previously utilized in the art.”
Remarks, page 16, first full paragraph.
The Office respectfully disagrees with the above remarks. In McRo, the Court found that the computer-automated process was a distinct process, not a process previously performed by humans1. In contrast, the limitations of claim 1 recite steps of calculating edge weight, generating a line graph, determining edge weight, generating edge filtration (i.e. series of subgraphs, as detailed below), and generating embedding representation. These steps are all mathematical concepts (e.g. mathematical calculations or operations) and/or mental processes (i.e. mentally performable by a human with the aid of pencil and paper. Hence, the steps of instant claim 1 stand in stark contrast to those in McRo, since the latter were deemed to be not previously performed by humans whereas the former clearly are. Claim 1 is not patent eligible.
Claims 17 and 18 recite limitations similar to those of claim 1 and are ineligible under 35 U.S.C. 101 for the same reasons that claim 1 is ineligible, as set forth above.
Claims 2, 5-12, 16, and 19-21 are ineligible under 35 U.S.C. 101 for the same reasons that claims 1 is ineligible, as set forth above, and for the additional reasons detailed below in the claim rejections under 35 U.S.C. 101.
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 1-2, 5-12, and 16-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As to claims 1, 17, and 18, these claims recite “a colored graph” and “a target graph.” These claims do not place any limits or specifications upon the claimed graphs, other than specifying the colored graph as “where each node is assigned a color value through coloring for the target graph.” The broadest reasonable interpretation (BRI) of the claimed graphs encompasses simple graphs having just a few nodes and edges. These claims recite “calculating an edge weight for the colored graph based on node color values of the colored graph.” This amounts to no more than mathematical calculation(s). Hence, this limitation is an abstract idea under the “Mathematical Concepts” grouping. Alternatively, this limitation may be deemed an abstract idea under the “Mental Processes” grouping because a human can, with the aid of pencil and paper, mentally perform the claimed “calculating” for the simple graphs encompassed by the BRI of the claims. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with a pencil and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas.
These claims also recite generating a line graph corresponding to the colored graph, node color values of the line graph being determined based on color values of a node tuple connected by a corresponding edge in the colored graph. For the simple graphs encompassed by the BRI of the claims, a human could draw out on a piece of paper a line graph that is as described in the claims. Hence, this limitation is also an abstract idea under the “Mental Processes” grouping.
These claims also recite “determining an edge weight for a first edge of the colored graph corresponding to a first node in the line graph based on an output value of a predictor that is obtained by inputting a color value of the first node.” Read in light of the instant specification, the claimed “edge weight” and “output value” are understood to be numerical values. Hence, the claimed “determining” in this limitation amounts to no more than mathematical calculation(s), i.e. calculating the claimed edge weight based on the claimed output value. Hence, this limitation is an abstract idea under the “Mathematical Concepts” grouping. Alternatively, this limitation may be deemed an abstract idea under the “Mental Processes” grouping, since a human can mentally performs these calculations with the aid of pencil and paper.
These claims also recite “generating an edge filtration for the colored graph using the edge weight as a connectivity metric between nodes.” The claimed “edge filtration” is defined in the instant specification as follows: “the term ‘filtration’ refers to a collection or sequence of subgraphs that represent an evolutionary process of a graph (particularly, a simplicial complex), where the subgraphs have an inclusion relationship in one direction (i.e., an increasing direction) (see FIGS. 7 and 8 for reference)” (see para. 0076 of Applicant’s published specification). Applicant’s Figure 8, reproduced below, depicts an edge filtration:
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Given that the BRI of the claims encompasses a simple case, as set forth above, a human could mentally perform the claimed generating of an edge filtration with the aid of pencil and paper. For example, with the aid of pencil and paper, a human could mentally generate the sequence of subgraphs (claimed “edge filtration”) depicted in Applicant’s Figure 8. Hence, this limitation is also an abstract idea under the “Mental Processes” grouping.
These claims also recite generating an embedding representation of the target graph based on topology information extracted from the edge filtration. An “embedding” is defined as “any representation of data that captures its relevant qualities,” and it is well-known to those of ordinary skill in the art that humans can generate embeddings in a process known as manual feature engineering2. As described in the specification at [0003] and [0059], the embedding representation itself is merely a vector or matrix. One can mentally perform a task using a vector or matrix representing a specific target graph. Given that the BRI of the claims encompasses a simple case as set forth above, a human could, with the aid of pencil and paper, mentally perform the claimed generating of an embedding representation. Hence, these limitations are also an abstract idea under the “Mental Processes” grouping. Alternatively, these limitations may be deemed an abstract idea under the “Mathematical Concepts” grouping since the claimed generating of an embedding representation amounts to no more than mathematical calculation(s) and/or operation(s).
These claims also recite automatically performing a predefined graph task using the embedding representation of the target graph, wherein the predefined graph task includes a classification task. As described in Applicant’s specification at [0003] and [0059] the embedding representation itself is merely a vector or matrix. Under the BRI, the claimed classification task encompasses something as simple as classifying an image as depicting a dog or cat, or classifying a text passage as having positive or negative sentiment, for example. Such a classification task amounts to no more than evaluation(s)/judgement(s) and is mentally performable by a human with the aid of pencil and paper. Hence, the claimed performance of a classification task is also an abstract idea under the “Mental Processes” grouping. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. Other than the abstract idea, the claims recite the following:
a) receiving a target graph as described in the claims, acquiring a colored graph as described in the claims, and transmitting the generated embedding representation as described in the claims;
b) use of a multi-layer perceptron3-based color value mapping module;
c) use of a neural network;
d) “wherein the predictor is configured to output a score indicating whether an edge of the colored graph corresponding to an input node is an actual edge or a virtual edge, based on a color value of the input node, the predictor being trained by updating parameters based on loss between predefined correct answers and individual scores;”
e) “at least one processor”;
f) “a memory configured to store a computer program that is executed by the at least one processor”; and
g) “A non-transitory computer-readable recording medium having stored therein a
computer program.”
Limitation (a) amounts to no more than mere data gathering, which has been deemed by the courts to be insignificant extra-solution activity. See MPEP 2106.05(g). Limitation (b) through (d) are high level, generic references to use of machine learning tools (i.e. use of a multi-layer perceptron, a neural network, and a trained predictor) and amount to generally linking the abstract idea to a particular technological environment, which cannot be deemed a practical application. See MPEP 2106.05(e). Limitations (e) through (g) are recited at a high level of generality, i.e. as generic computer components performing generic computing functions. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Looking at the additional elements as a whole adds nothing beyond the additional elements considered individually—they still represent insignificant extra-solution activity; generally linking to a technological environment; and/or generic computer implementation. Hence, the claim as a whole, looking at the additional elements individually and in combination, does not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Limitation (a) amounts to no more than mere data gathering, which has been deemed by the courts to be insignificant extra-solution activity. See MPEP 2106.05(g). In addition, the courts have deemed receiving/transmitting data to be well-understood, routine, and conventional activity, as in the following cases: Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015) (storing and retrieving information in memory). See MPEP 2106.05(d)(II). Limitation (b) through (d) are high level, generic references to use of machine learning tools (i.e. use of a multi-layer perceptron, a neural network, and a trained predictor) and amount to generally linking the abstract idea to a particular technological environment, which cannot be deemed significantly more. See MPEP 2106.05(e). As discussed above with respect to integration of the abstract idea into a practical application, additional elements (e) through (g) amount to no more than mere field of use limitations and instructions to apply the exception using generic computer components. Mere instructions to apply an exception using conventional computer components and functions cannot provide an inventive concept. Looking at the additional elements as a whole adds nothing beyond the additional elements considered individually—they still represent insignificant extra-solution activity; well-understood, routine, and conventional subject matter; generally linking to a particular technological environment; and/or generic computer implementation. Hence, the claims as a whole, looking at the additional elements individually and in combination, do not amount to significantly more than the abstract idea. These claims are not patent eligible.
As to dependent claim 2, the following is recited: “wherein the colored graph is generated by updating a color value of each node that forms the target graph, in a manner that aggregates color values of neighboring nodes.” Given that the BRI of the claims encompasses simple graphs having just a few nodes and edges, as set forth above in the discussion of the parent claims, a human can mentally perform this limitation with the aid of pencil and paper. Hence, this limitation is also an abstract idea under the “Mental Processes” grouping.
As to dependent claims 5, this claim recites certain details of the training processor for the predictor model. As detailed above in the discussion of the parent claims, the use of trained predictor model is a high level, generic reference to use of a machine learning tool, and it amounts to generally linking the abstract idea to a particular technological environment. Generally linking the abstract idea to a particular technological environment cannot be deemed a practical application nor an inventive concept. See MPEP 2106.05(e).
As to dependent claims 6-9, these claims recite further details of “generating the line graph” and/or “calculating the edge weight.” Given that the BRI of the claims encompasses simple graphs having just a few nodes and edges, as set forth above in the discussion of the parent claims, a human can mentally perform the limitations of these claims with the aid of pencil and paper. Hence, the limitations of these claims are also an abstract idea under the “Mental Processes” grouping. Alternatively, these limitations may be deemed an abstract idea under the “Mathematical Concepts” grouping because they amount to no more than mathematical calculations and/or operations.
As to dependent claim 10, the following is recited: “wherein the generating the edge filtration comprises generating the edge filtration using a Vietoris-Rips filtration technique.” Given that the BRI of the claims encompasses simple graphs having just a few nodes and edges, as set forth above in the discussion of the parent claims, a human can mentally perform this limitation with the aid of pencil and paper. Hence, this limitation is also an abstract idea under the “Mental Processes” grouping. Alternatively, this limitation may be deemed an abstract idea under the “Mathematical Concepts” grouping because it amounts to no more than mathematical calculation(s) and/or operation(s).
As to dependent claims 11-12, and 19-21, these claims recite further details of “generating the embedding representation.” Given that the BRI of the claims encompasses simple graphs having just a few nodes and edges, as set forth above in the discussion of the parent claims, a human can mentally perform the limitations of these claims with the aid of pencil and paper. Hence, the limitations of these claims are also an abstract idea under the “Mental Processes” grouping. Alternatively, these limitations may be deemed an abstract idea under the “Mathematical Concepts” grouping because they amount to no more than mathematical calculations and/or operations.
As to dependent claim 16, the following is recited: “calculating a task loss by performing a predefined task based on the generated embedding representation; and updating values of parameters involved in the generating the embedding representation
based on the task loss.” Given that the BRI of the claims encompasses simple graphs having just a few nodes and edges, as set forth above in the discussion of the parent claims, a human can mentally perform this limitation with the aid of pencil and paper. Hence, this limitation is also an abstract idea under the “Mental Processes” grouping. Alternatively, these limitations may be deemed an abstract idea under the “Mathematical Concepts” grouping because they amount to no more than mathematical calculations and/or operations.
Conclusion
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 extension fee 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 date of this final action.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to UMAR MIAN whose telephone number is (571)270-3970. The examiner can normally be reached Monday to Friday, 10 am to 6:30 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tony Mahmoudi can be reached on (571) 272-4078. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Umar Mian/
Primary Examiner, Art Unit 2163
1 “The computer here is employed to perform a distinct process to automate a task previously performed by humans.” McRO Inc. v. Bandai Namco Games America Inc., page 24.
2 Bergmann, David and Strykyer, Cole. "What is vector embedding?" Published 12 June 2024 by IBM. Accessed 28 August 2025 from https://www.ibm.com/think/topics/vector-embedding
See pages 4 and 6.
3 A multi-layer perceptron is defined as a neural network having at least three layers: an input layer, an hidden layer and an output layer, where each layer operates on the outputs of its preceding layer.
See Yehoshua, Roi. “Multi-Layer Perceptrons.” Published 2 April 2023 by towardsdatascience.com. Accessing 2 Jan 2026 from https://towardsdatascience.com/multi-layer-perceptrons-8d76972afa2b/
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