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.
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 mailing date of this final action.
Status of the Application
The following is a Final Office Action in response to Examiner's communication of 09/04/2025, Applicant, on 11/21/2025.
Status of Claims
Claims 1, 10, and 19 are currently amended.
Claims 3 and 11-12 are canceled.
Claims 1-2, 4-10, and 13-20 are currently pending following this response.
New matter
No new matter has been added to the amended claims.
Response to Arguments - 35 USC § 101
The arguments have been fully considered, but they are not persuasive.
The Examiner respectfully disagrees.
The Examiner notes that the invention remains an abstract idea, most notably mental processes since a human can reasonably collect and analyze data to detect anomaly. Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer’).
Applicant’s arguments (page 10) about at least one thousand statistical model and at least one million scores do not take the claimed limitations out of the mental process. Performed in the human mind as described in MPEP § 2106.04(a)(2) does have a time limit to perform the mental process. The mental process can take five years and twenty people to be performed and still be a mental process.
Applicant’s arguments (page 11) “fast processing speed” are not persuasive because the possessing time or speed in the instant claimed invention are due filtering or preparing data. The processing speed is not due to an improvement in the computer itself. An Example of faster computation time is Example 3 “Digital Image Processing” in Examples 1-36 of the July 2015 Update. In Example 3 the inventor has improved upon previous halftoning techniques by developing an improved mask called a “blue noise” mask. The blue noise mask requires less memory than previous masks and results in a faster computation time while improving image quality.
As such, a skilled in the art would not agree with Applicant’s arguments in page 12 regarding “the claimed invention of claims 1-2, 4-10, and 13-20 is directed to an improvement to computer functionality or computer-related technology.”
Further, Figure 3 of the original disclosure teaches a processor, a memory, an input device, and a communication interface connected to plurality of entities via a network in addition to multiple software modules which is not an unconventional arrangement as argued by Applicant on pages 14-15.
The claimed process can be broken down into the steps of 1) data collection, relevant transaction data (e.g., amount, date/time, location, etc.) is gathered, 2) algorithmic analysis (machine learning) to analyze the data to identify unusual patterns or deviations from what is considered normal or expected behavior based on historical data or defined rules. This deviation or unexpectedness can be thought of as a measure of "surprise", 3) surprise scoring, a numerical score, representing the probability or likelihood of the anomaly being fraudulent, is assigned to the transaction based on the analysis. The concept of surprise measure in the context of deviation from expected pattern is abstract (see example 47 claim 2 July 2024 Subject Matter Eligibility Examples).
Claim 2 Example 47
[Claim 1] An application specific integrated circuit (ASIC) for an artificial neural network (ANN), the ASIC comprising:
a plurality of neurons organized in an array, wherein each neuron comprises a register, a microprocessor, and at least one input; and
a plurality of synaptic circuits, each synaptic circuit including a memory for storing a synaptic weight, wherein each neuron is connected to at least one other neuron via one of the plurality of synaptic circuits.
[Claim 2] A method of using an artificial neural network (ANN) comprising:
(a) receiving, at a computer, continuous training data;
(b) discretizing, by the computer, the continuous training data to generate input data;
(c) training, by the computer, the ANN based on the input data and a selected training algorithm to generate a trained ANN, wherein the selected training algorithm includes a backpropagation algorithm and a gradient descent algorithm;
(d) detecting one or more anomalies in a data set using the trained ANN;
(e) analyzing the one or more detected anomalies using the trained ANN to generate anomaly data; and
(f) outputting the anomaly data from the trained ANN.
Claim 2 in Example 47 was found ineligible based on the following:
Steps (a), (b), and (c) are all recited as being performed by a computer. The recited computer is recited at a high level of generality, i.e., as a generic computer performing generic computer functions.
Step (d) recites detecting one or more anomalies in a data set using the trained ANN. The claim does not provide any details about how the trained ANN operates or how the detection is made, and the plain meaning of “detecting” encompasses mental observations or evaluations, e.g., a computer programmer’s mental identification of an anomaly in a data set.
Step (e) recites analyzing the one or more detected anomalies using the trained artificial neural network to generate anomaly data. The step of analyzing includes both determining that an anomaly has been detected and may further include suggesting a type or cause of the anomaly. The plain meaning of “analyzing” encompasses evaluating information, which in this claim is limited to evaluating detected anomalies to generate anomaly data by the trained ANN. The claim does not limit how the analysis (evaluation) is performed, and there is nothing about a detected anomaly itself that would limit how it can be analyzed. As explained in the background, “the anomaly data may explain the type of anomaly or a cause of the anomaly.” The claim does not include any additional details that explain the analysis of detected anomalies.
Regarding step (f), the step of outputting the anomaly data merely requires a generic output using the trained ANN. The claim does not impose any limits on how the data is output or require any particular components that are used to output the anomaly data.
Based on the plain meaning of the words in the claim, the broadest reasonable interpretation of claim 2 is a method that receives continuous training data at a computer, uses the computer to discretize the continuous training data to generate input data, trains the ANN using the input data
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
As discussed above, the broadest reasonable interpretation of steps (b), (d), and (e) is that those steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III.
Specifically, step (b) recites discretizing continuous training data to generate input data by processes including rounding, binning, or clustering continuous data, which may be practically performed in the human mind using observation, evaluation, judgment, and opinion. For example, the claimed discretizing of continuous data encompasses observing continuous data and performing an evaluation, such as rounding the continuous data. Step (d) recites detecting one or more anomalies in a data set using the trained ANN. Under its broadest reasonable interpretation when read in light of the specification, the “detecting” encompasses mental observations or evaluations that are practically performed in the human mind. For example, the claimed detecting of anomalies in a data set encompasses observing data in a data set and performing an evaluation by comparing anomalous and non-anomalous data. Step (e) recites analyzing the one or more detected anomalies using the trained ANN to generate anomaly data. Step (e) encompasses performing evaluation, judgment, and opinion to make a determination about detected anomalies. Under its broadest reasonable interpretation when read in light of the specification, the “analyzing” encompasses mental processes practically performed in the human mind by observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III.
As discussed above, the broadest reasonable interpretation of discretizing in step (b) also encompasses mathematical concepts (e.g., rounding data values) that can be performed mentally. Step (c) requires specific mathematical calculations (a backpropagation algorithm and a gradient descent algorithm) to perform the training of the ANN and therefore encompasses mathematical concepts.
“Unless it is clear that a claim recites distinct exceptions, such as a law of nature and an abstract idea, care should be taken not to parse the claim into multiple exceptions, particularly in claims involving abstract ideas.” MPEP 2106.04, subsection II.B. However, if possible, the examiner should consider the limitations together as a single abstract idea rather than as a plurality of separate abstract ideas to be analyzed individually. “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.” MPEP 2106.04, subsection II.B. Under such circumstances, however, the Supreme Court has treated such claims in the same manner as claims reciting a single judicial exception. Id. (discussing Bilski v. Kappos, 561 U.S. 593 (2010)). Here, steps (b), (d), and (e) fall within the mental process grouping of abstract ideas, and steps (b) and (c) fall within the mathematical concepts grouping of abstract ideas. Limitations (b)-(e) are considered together as a single abstract idea for further analysis. (Step 2A, Prong One: YES).
Step 2A, Prong Two:
The additional elements in the claim are recited as being performed by a computer. The computer is recited at a high level of generality. In limitation (a), the computer is used as a tool to perform the generic computer function of receiving data. See MPEP 2106.05(f). In limitations (b) and (c), the computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amount to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
As explained with respect to Step 2A, Prong Two, there are four additional elements.
The additional element of “using the trained ANN” in limitations (d) and (e) are at best mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept. See MPEP 2106.05(f).
The Examiner asserts that the present claims are similar to Example 47 claim 2 using an ordinary computer processor to perform ordinary computer functions and the present claims do not improve any existing technology.
In conclusion, the pending claims are not eligible under 35 USC § 101 and the Examiner maintains the rejection of the pending claims under 35 USC § 101 in the present office action.
CLAIM INTERPRETATION
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations (claim 1, 3, 5-6, 10-12, and 15-16) that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: collection module, analysis module, detection module, and remediation module as in claim 1. The specification barely explains what these modules are doing (function) but does not give any structures of these units as far as what these units are.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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, 4-10, and 13-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Specifically, claims 1-2, 4-10, and 13-20 are directed to an abstract idea without additional elements to integrate the claims into a practical application or to amount to significantly more than the abstract idea.
Claims 1-2, 4-10, and 13-20 are directed to a process, machine, or manufacture (Step 1), however the claims are directed to the abstract idea of detecting anomalous data and generating and displaying metric scores.
With respect to Step 2A Prong One of the frameworks, claim 1 recites an abstract idea. Claim 1 includes limitations for “collect a plurality of metrics measuring a plurality of attributes of voluminous received data from a plurality of entities grouped into a plurality of peer groups; generate a plurality of measures of surprise (MoS) with each measure of surprise is generated for every single metric of the plurality of metrics and for every peer group of the plurality of peer group using a predetermined measuring algorithm applied to the metrics, wherein each measure of surprise is determined from:
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wherein AH is a change in an entropy of a respective metric Mi with reference to a respective attribute A of the plurality of attributes from a reference period to an observation period, MetricShareInReferencePeriod is determined from counts of the metrics, and k is a predetermined scaling factor to generate at least one thousand micro-statistical models from the plurality of measures of surprise, from each metric of the plurality of metrics, and from each peer group in the plurality of peer groups, and to generate at least one million scores from the at least one thousand micro-statistical models with each score of the at least one million scores associated with a corresponding metric using the measures of surprise; a detection module configured to detect problematic data among the received data using the plurality of scores; and a remediation module executes the instructions using the hardware- based processor and, responsive to user-defined criteria, remediates the problematic data including performing a remediation action selected from the group consisting of: a roll back of the problematic data, deletion of the problematic data, or flagging the problematic data, thereby correcting anomalies, outliers, or errors in the problematic data.”
The limitations above recite an abstract idea under Step 2A Prong One. More particularly, the limitations above recite Mental Process because an ordinary person can reasonably collect and analyze data to detect anomaly. As a result, claim 1 recites an abstract idea under Step 2A Prong One.
Claims 10 and 19 recite substantially similar limitations to those presented with respect to claim 1. As a result, claims 10 and 19 recite an abstract idea under Step 2A Prong One for the same reasons as stated above with respect to claim 1. Similarly, claims 2, 4-9, 13-18, and 20 recite a Mental Process because the claimed elements describe a process for detecting anomalous data and generating and displaying metric scores. As a result, claims 2, 4-9, 13-18, and 20recite an abstract idea under Step 2A Prong One.
With respect to Step 2A Prong Two of the framework, claim 1 does not include additional elements that integrate the abstract idea into a practical application. Claim 1 includes additional elements that do not recite an abstract idea. The additional elements of claim 1 include “A system, comprising: a hardware-based processor; a memory configured to store instructions and configured to provide the instructions to the hardware-based processor; and a set of modules configured to implement the instructions provided to the hardware-based processor, the set of modules including: a metric collection module configured to”, “an analysis module configured to”, “a detection module configured to”, “and a remediation module”. When considered in view of the claim as a whole, the step of “collecting” does not integrate the abstract idea into a practical application because “collecting” is an insignificant extra solution activity to the judicial exception. When considered in view of the claim as a whole, the recited computer elements do not integrate the abstract idea into a practical application because the computer elements are generic computer elements that are merely used as a tool to perform the recited abstract idea. As a result, claim 1 does not include additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
As noted above, claims 10 and 19 recite substantially similar limitations to those recited with respect to claim 1. Although claim 10 further recites “A system, comprising: a display; a hardware-based processor; a memory configured to store instructions and configured to provide the instructions to the hardware-based processor; and a set of modules configured to implement the instructions provided to the hardware-based processor, the set of module”, when considered in view of the claim as a whole, the recited computer elements do not integrate the abstract idea into a practical application because the computer elements are generic computer elements that are merely used as a tool to perform the recited abstract idea. As a result, claims 10 and 19 do not include additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Claims 2, 4-9, 13-18, and 20do not include any additional elements beyond those recited by independent claims 1, 10, and 19. As a result, claims 2, 4-9, 13-18, and 20 do not include additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
With respect to Step 2B of the framework, claim 1 does not include additional elements amounting to significantly more than the abstract idea. As noted above, claim 1 includes additional elements that do not recite an abstract idea. The additional elements of claim 1 include “A system, comprising: a hardware-based processor; a memory configured to store instructions and configured to provide the instructions to the hardware-based processor; and a set of modules configured to implement the instructions provided to the hardware-based processor, the set of modules including: a metric collection module configured to”, “an analysis module configured to”, “a detection module configured to”, “and a remediation module”. The step of “collecting” does not amount to significantly more than the abstract idea because “collecting” is well-understood, routine, and conventional computer function in view of MPEP 2106.05(d)(ll). The recited computer elements do not amount to significantly more than the abstract idea because the computer elements are generic computer elements that are merely used as a tool to perform the recited abstract idea. As a result, claim 1 does not include additional elements that amount to significantly more than the abstract idea under Step 2B.
As noted above, claims 10 and 19 recite substantially similar limitations to those recited with respect to claim 1. Although claim 10 further recites “A system, comprising: a display; a hardware-based processor; a memory configured to store instructions and configured to provide the instructions to the hardware-based processor; and a set of modules configured to implement the instructions provided to the hardware-based processor, the set of module”, the recited computer elements do not amount to significantly more than the abstract idea because the computer elements are generic computer elements that are merely used as a tool to perform the recited abstract idea. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claims 10 and 19 do not include additional elements that amount to significantly more than the abstract idea under Step 2B.
Claims 2, 4-9, 13-18, and 20 do not include any additional elements beyond those recited by independent claims 1, 10, and 19. As a result, claims 2, 4-9, 13-18, and 20 do not include additional elements that amount to significantly more than the abstract idea under Step 2B.
Therefore, the claims are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea. Accordingly, claims 1-2, 4-10, and 13-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Conclusion
Applicant's amendments and arguments dated 11/21/2025 necessitated the updating of the 35 USC § 101 rejections of the pending claims presented in the present 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).
Any inquiry concerning this communication from the Examiner should be directed to Abdallah El-Hagehassan whose contact information is (571) 272-0819 and Abdallah.el-hagehassan@uspto.gov The Examiner can normally be reached on Monday- Friday 8 am to 5 pm.
If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, Rutao Wu can be reached on (571) 272-6045. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/ABDALLAH A EL-HAGE HASSAN/
Primary Examiner, Art Unit 3623
Prosecution Insights