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 .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more. The claims recite mathematical concepts and mental processes. This judicial exception is not integrated into a practical application because the claims generally link abstract ideas to a generic computer. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they include mere instructions to perform mathematical concepts and mental processes on a generic computer without creating a significant improvement or change to the computer.
Claim 1:
Step 2A Prong 1: Identification of Abstract Ideas
Claim 1 recites:
generate with the clustering model a clustering model output, wherein when generating the clustering model output the clustering model maps vectors from each support request record in the output from the embedding model into a vector space (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
evaluates the vectors for similarities (MPEP 2106.04(a)(2)(III)A, “collecting and comparing known information” as mental process)
locates separations between groups of similarly mapped vectors (MPEP 2106.04(a)(2)(III)A, “collecting and comparing known information” as mental process)
defines clusters based on the separations, and maps each support request record to a single cluster; (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
wherein when the anomaly detection model receives the clustering model output, the anomaly detection model generates an anomaly detection model output based, at least in part, on the clustering model output (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
and when generating the anomaly detection model output the anomaly detection model evaluates one or more metadata elements of support requests associated with a cluster, derives scores from the one or more metadata elements based on the number of occurrences of support requests with each of the one or more metadata elements during one or more preset time periods (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
evaluates the scores to detect time periods with anomalous scores, and maps each support request to indicate that the support request occurred during an anomalous time period or during a non-anomalous time period based on the scores (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
when the forecasting model receives the clustering model output, the forecasting model generates a forecasting model output based, at least in part, on the clustering model output (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
and when generating the forecasting model output the forecasting model evaluates one or more clusters of the clustering model output (MPEP 2106.04(a)(2)(III)A, “collecting and comparing known information” as mental process)
maps one or more clusters to one or more time periods (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
creates a mathematical function for each cluster to describe the trend of that cluster during the one or more time periods (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
and extrapolates the mathematical function to future time periods (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
Step 2A Prong 2: Identification of Additional Elements
Claim 1 further recites:
one or more processors (MPEP 2106.04(d): regarding, “simply implementing a mathematical principle on a physical machine, namely a computer, was not a patentable application of that principle”)
receive into a clustering model output from an embedding model, the information from the embedding model including information related to a plurality of support request records;(MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
receive the clustering model output directly into an anomaly detection model, and a forecasting model (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
receive into a database ingestion model the clustering model output (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
and receive into the database ingestion model the at least one of the anomaly detection model output and the forecasting model output; and display on a user display the information received into the database ingestion model to provide information about the support request records to a user. (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
Step 2B: Significantly More Analysis
The additional elements of the claim do not integrate the abstract idea into a practical application. The additional elements amount to mere instructions to apply the judicial exceptions on a generic computer (MPEG 2106.05(f)) and insignificant extra-solution activity. (MPEG 2106.05(g)) The computer is cited at such a high level of generality that it cannot be determined to be a particular machine (MPEP 2106.05(b)) and is simply linking the judicial exception to a particular technology (MPEP 2106.05(h))
Claim 2:
Claim 2 recites:
The system of claim 1, wherein at least one of the clusters into which support request records are mapped is a generic cluster for support requests that do not fit into one of the specified clusters.
Claim 2 merely further describe the clusters of claim 1, respectively
Claim 3:
Claim 3 recites:
The system of claim 1, wherein the scores include day score, week score, month score and year score normalizations.
Claim 3 merely further describe the scores of claim 1, respectively
Claim 4:
Step 2A Prong 1: Identification of Abstract Ideas
Claim 4 recites:
The system of claim 1, wherein when generating the anomaly detection model output the anomaly detection model evaluates the scores to detect border points. (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
Step 2B: Significantly More Analysis
Does the claim recite additional elements that amount to significantly more than the judicial exception?
No.
Claim 5:
Claim 5 recites:
The system of claim 1, wherein the anomaly detection model evaluates scores on a cluster by cluster basis.
Claim 5 merely further describe the evaluate scores process of claim 1, respectively
Claim 6:
Claim 6 recites:
The system of claim 1, wherein the anomaly detection model outputs support request data wherein captured support requests are mapped to a classification as anomalous, borderline or normal.
Claim 6 merely further describe the anomaly detection model outputs of claim 1, respectively
Claim 7:
Claim 7 recites:
The system of claim 1, wherein the one or more metadata elements include time.
Claim 7 merely further describe the metadata elements of claim 1, respectively
Claim 8:
Step 2A Prong 1: Identification of Abstract Ideas
Claim 8 recites:
generate with the pre-processing model a pre-processing model output, wherein when generating the pre-processing model output the pre-processing model preparing data fields for further use including deriving additional metadata based on calculations utilizing raw metadata (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
wherein when the pattern-based filtering model receives the pre-processing model output, the pattern-based filtering model generates pattern-based filtering model output (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
and when generating the pattern-based filtering model output the pattern-based filtering model recognizes patterns in the support request record data related to extraneous system information, wherein the extraneous information includes system information that is duplicative of metadata or irrelevant to the content of the support request (MPEP 2106.04(a)(2)(III)A, “collecting and comparing known information” as mental process)
identifies irrelevant or extraneous text based on the recognized patterns (MPEP 2106.04(a)(2)(III)A, “collecting and comparing known information” as mental process)
)
and removes from the data set text identified as being irrelevant or extraneous (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
and wherein the embedding model receives pre-processing model output or pattern-based filtering output, and when the embedding model receives the pre-processing model output or the pattern-based filtering output, the embedding model generates a first embedding model output based, at least in part, on the received pre-processing model output or pattern-based filtering output (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
and when generating the first embedding model output the embedding model assigns vectors to the text elements of the support request data representing the content of the text elements (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
wherein when the message relevancy filtering model receives the first embedding model output, the message relevancy filtering model generates message relevancy filtering model output (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
and when generating the message relevancy filtering model output the message relevancy filtering model categorizes each individual correspondence of each support request record as being either relevant or irrelevant to the technical topic addressed in the support request record (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
removes from the text elements those individual correspondences identified as being irrelevant (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
and when the embedding model receives message relevancy filtering model output, the embedding model generates a second embedding model output based, at least in part, on the received message relevancy filtering model output (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
and when generating the second embedding model output the embedding model assigns vectors to the text elements of the support request data representing the content of the text elements (MPEP 2106.04(a)(2)(I): regarding mathematical relationships, mathematical formulas or equations, and mathematical calculations as abstract ideas)
Step 2A Prong 2: Identification of Additional Elements
Claim 8 further recites:
one or more processors (MPEP 2106.04(d): regarding, “simply implementing a mathematical principle on a physical machine, namely a computer, was not a patentable application of that principle”)
receive into a pre-processing model output from an ingestion deployment, the information from the ingestion deployment including information related support request records; (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
receive the pre-processing model output into at least one of a pattern-based filtering model, and an embedding model (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
and delivers the pattern-based filtering model output to the embedding model (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
and receive the first embedding model output into a message relevancy filtering model, or a database ingestion model (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
and delivers the message relevancy filtering model output back to the embedding model (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
and delivers the message relevancy filtering model output to the embedding model (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
and delivers the second embedding model output to the database ingestion model; display the information received into the database ingestion model from the second embedding model output to provide information about the support request records to a user (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
and display information about the support request records to a user when the database ingestion model receives the first embedding model output, the information received into the database ingestion model from the first embedding model output is used (MPEP 2106.05(g): mere data gathering is an Insignificant Extra-Solution Activity)
Step 2B: Significantly More Analysis
The additional elements of the claim do not integrate the abstract idea into a practical application. The additional elements amount to mere instructions to apply the judicial exceptions on a generic computer (MPEG 2106.05(f)) and insignificant extra-solution activity. (MPEG 2106.05(g)) The computer is cited at such a high level of generality that it cannot be determined to be a particular machine (MPEP 2106.05(b)) and is simply linking the judicial exception to a particular technology (MPEP 2106.05(h))
Claim 9:
The processors of claim 9 performs the same method steps as the methods of claims 1 and 8, and claims 9 are therefore rejected using the same rationale set forth above in the rejection of claims 1 and 8
Step 2A Prong 2: Identification of Additional Elements
one or more processors (MPEP 2106.04(d): regarding, “simply implementing a mathematical principle on a physical machine, namely a computer, was not a patentable application of that principle”)
Step 2B: Significantly More Analysis
The additional elements of the claim do not integrate the abstract idea into a practical application. The additional elements amount to mere instructions to apply the judicial exceptions on a computer (MPEG 2106.05(f))
Response to Arguments
Applicant’s arguments, filed 02/11/2026, regarding the rejections applied under 35 U.S.C 101 have been fully considered but they are not persuasive. The steps of “display on a user display” and “display information to a user” are merely the communication or presentations of the results of the abstract idea. This represents insignificant post-solution activity because it does not require more than a general-purpose computer to perform the functions, nor does it transform the abstract idea into a patent-eligible application. The applicant argues that the invention “improve a user’s ability to obtain actional information related to support request records”. However, improving user’s experience or ‘humanly comprehensible’ acquisition of data is not a technical improvement to the functioning of a computer itself. (MPEP2106.05(a)II, Examples that the courts have indicated may not be sufficient to show an improvement to technology include: “iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48;”)
Applicant’s arguments, filed 02/11/2026, regarding the rejections applied under 35 U.S.C 103 have been fully considered are persuasive. The 103 rejection of claim 1 has been withdrawn.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
(US 20240420568 A1): A computer-implemented method comprising: clustering a plurality of sets of traffic data based on similarity to each other to generate a plurality of clusters of the plurality of sets of traffic data; selecting a representative set of a respective plurality of set of traffic data of a respective cluster which is most similar to an average; and based on the set of traffic data corresponding to a target geographical region, performing mobility analysis to determine parameters for a seasonal traffic forecast and, based on at least one set of traffic data corresponding to at least one other geographical region, performing mobility analysis to determine parameters for at least one other seasonal traffic forecast for the at least one other geographical region; performing a traffic forecasting process for the target geographical region; and predicting emissions produced by traffic in the target geographical region based on the combined traffic forecast.
(US 12265446 B1): A determination is made that anomaly analysis is to be performed with respect to an application. An anomaly score of the application is generated with respect to observed values of a plurality of metrics of the application. Generation of the anomaly score comprises computing an anomaly score contribution associated with an analysis of a correlation between values of a pair of metrics of the application. In response to a detection that the anomaly score exceeds a threshold, an anomaly response operation is initiated.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to XINYUAN YU whose telephone number is (571)272-7140. The examiner can normally be reached Monday-Friday 8:30-5:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bryce Bonzo can be reached at 571-272-3655. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/XINYUAN YU/Examiner, Art Unit 2113 /BRYCE P BONZO/Supervisory Patent Examiner, Art Unit 2113
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