Prosecution Insights
Last updated: October 02, 2026
Application No. 18/138,930

UNIVARIATE SERIES TRUNCATION POLICY USING CHANGEPOINT DETECTION

Final Rejection §101§103
Filed
Apr 25, 2023
Examiner
CHOY, PAN G
Art Unit
3624
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
ORACLE INTERNATIONAL Corporation
OA Round
2 (Final)
24%
Grant Probability
At Risk
3-4
OA Rounds
1y 3m
Est. Remaining
59%
With Interview

Examiner Intelligence

Grants only 24% of cases
24%
Career Allowance Rate
114 granted / 467 resolved
-27.6% vs TC avg
Strong +35% interview lift
Without
With
+34.9%
Interview Lift
resolved cases with interview
Typical timeline
4y 8m
Avg Prosecution
36 currently pending
Career history
501
Total Applications
across all art units

Statute-Specific Performance

§101
36.8%
-3.2% vs TC avg
§103
40.5%
+0.5% vs TC avg
§102
4.1%
-35.9% vs TC avg
§112
18.0%
-22.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 467 resolved cases

Office Action

§101 §103
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 . Introduction The following is a final Office Action in response to Applicant’s communications received on June 16, 2026. Claims 1, 8 and 15 have been amended. Currently claims 1-20 are pending, Claims 1, 8 and 15 are independent. Information Disclosure Statement The information disclosure statement (IDS) submitted on 06/16/2026 appears to be in compliance with the previsions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the Examiner. Response to Amendments Applicant’s amendments necessitated the new ground(s) of rejection in this Office Action. Applicant’s amendments to claims 1, 8 and 15 are NOT sufficient to overcome the 35 U.S.C. § 101 rejection as set forth in the previous Office Action. Therefore, the 35 U.S.C. § 101 rejection to claims 1-20 is maintained. Response to Arguments Applicant’s arguments filed on 06/16/2026 have been fully considered but they are not persuasive. In the Remarks on page 13, Applicant’s arguments regarding the 35 U.S.C. § 101 rejection that the claims are not directed to a judicial exception; the Examiner appears to characterize certain limitations of claim 1, including the steps of determining change points, generating truncated time series, generating forecast values, comparing forecast values using a second time series…; claim 1, considered as a whole, is directed to a specific computer-implemented forecasting technique, not to mental process or other abstract idea. In response to Applicant’s argument, the Examiner respectfully disagrees. In Alice, the Supreme Court sets forth an analytical “framework for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent-eligible applications of those concepts.” Id. at 2355 (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1296—97 (2012)). The first step in the analysis is to “determine whether the claims at issue are directed to one of those patent-ineligible concepts,” such as an abstract idea. Regardless of the level of generality used to describe the abstract idea recited, the claims are directed to an abstract idea. Cf. Accenture Glob. Servs., GmbH v. Guidewire Software, Inc., 728 F.3d 1336, 1344–45 (Fed. Cir. 2013) (“Although not as broad as the district court’s abstract idea of organizing data, it is nonetheless an abstract concept.”). Moreover, regardless the technique or algorithm a person is using, making a forecast based past experience is a fundamental building block of human ingenuity. As such it is an abstract idea. In the Remarks on page 15, Applicant’s arguments regarding the 35 U.S.C. § 101 rejection that the Examiner, beyond merely identifying certain limitations of claim 1 (i.e., determining, generating, comparing and selecting steps in claim 1), the Examiner has not provided any evidence that the identified limitations are in fact “mental process” or “a method of organizing human activity.” In response to Applicant’s argument, the Examiner respectfully disagrees. MPEP § 2106.07 describes the requirements of a prima facie case of ineligibility. The initial burden on the Examiner is to identify and explain why a claim or claims are ineligible for patent protection. The Court has held that the USPTO carries its procedural burden of establishing a prima facie case when its rejection satisfies the requirements of 35 U.S.C. § 132 by notifying the Applicant of the reasons for rejection, "together with such information and references as may be useful in judging of the propriety of continuing the prosecution of [the] application." In re Jung, 637 F.3d 1356, 1362 (Fed. Cir. 2011) (citation omitted). All that is required of the Office is to set forth the statutory basis of the rejection, as well as any reference on which the rejection relies, in a sufficiently articulate and informative manner as to meet the notice requirement of § 132. The burden shifts to Applicant to provide persuasive arguments supported by any necessary evidence to demonstrate that one of ordinary skill in the art would understand that the disclosure invention improves technology. See also Revised 2019 Guidance, 84 Fed. Reg. 50, at 13, 15 (January 7, 2019). Besides, the USPTO policy does not require Examiners to provide such documentary evidence to demonstrate abstractness. In the Remarks on page 17, Applicant’s arguments regarding the 35 U.S.C. § 101 rejection that the claimed process improves the performance of the forecasting system itself by enhancing forecast accuracy while reducing the time and computing resources required for model fitting. For at least these reasons, claim 1 integrates any alleged judicial exception into a practical application under Step 2A, Prong Two. In response to Applicant’s argument, the Examiner respectfully disagrees. In order for a claim to integrate the exception into a practical application, the additional claimed elements must, for example, improve the functioning of a computer or any other technology or technical field (see MPEP § 2106.05(a)), apply the judicial exception with a particular machine (see MPEP § 2106.05(b)), affect a transformation or reduction of a particular article to a different state or thing (see MPEP § 2106.05(c)), or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment (see MPEP § 2106.05(e)). See Revised 2019 Guidance. Here, claim 1 recites the additional element of “a computing system” for performing the steps. The Specification describes that “a computing system including one or more processors and a computer-readable medium” (see ¶ 13), and “by way of example, personal computers and/or laptop computers running various versions of Microsoft Windows, Apple Macintosh, and/or Linux operating systems.”(See ¶ 104). When given the broadest reasonable interpretation and in light of the Specification, the additional element is recited at a high level of generality and merely invoked as tools to perform generic computer functions including receiving, manipulating and transmitting information over a network. Reciting “a computing system” in the claim to perform such steps is no more than adding the words “apply it” or using “a particular machine” with an abstract idea, or mere instructions to implement the abstract idea on a computer. Thus, merely adding a generic computer, generic computer components, or programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 2358-59, 110 USPQ2d 1976, 1983-84 (2014); see CyberSource, 654 F.3d at 1375 (the incidental use of a computer to perform mental processes does not impose a meaningful limitation on the claim scope). However, simply implementing the abstract idea on a generic computer does not integrate the abstract idea into a practical application. Revised 2019 Guidance, 84 Fed. Reg. at 55 (explaining that courts have identified merely using a computer as a tool to perform an abstract idea as an example of when a judicial exception has not been integrated into a practical application). In the Remarks on page 19, Applicant’s arguments regarding the 35 U.S.C. § 101 rejection that the features of independent claim 1 when viewed as a whole do not correspond to an abstract idea, the additional claim limitations in claim 1 clearly recite an ordered combination of elements that amounts to significantly more than any alleged abstract idea. In response to Applicant’s argument, the Examiner respectfully disagrees. Step 2B is to determine whether any “inventive concept” which can transform the abstract idea into a patent-eligible invention. The “inventive concept” may arise in one or more of the individual claim limitations or in the ordered combination of the limitations. Alice, 134 S. Ct. at 2355. An “inventive concept” that transforms the abstract idea into a patent-eligible invention must be significantly more than the abstract idea itself, and cannot simply be an instruction to implement or apply the abstract idea on a computer. Id. at 2358. In the present case, beyond the abstract idea, the claim recites the additional element of “by a computing system” for performing the steps. The Specification describes that “a computing system including one or more processors and a computer-readable medium” (see ¶ 13), and “by way of example, personal computers and/or laptop computers running various versions of Microsoft Windows, Apple Macintosh, and/or Linux operating systems.”(See ¶ 104). When given the broadest reasonable interpretation and in light of the Specification, the additional element is recited at a high level of generality and merely invoked as tools to perform generic computer functions including receiving, manipulating and transmitting information over a network. Reciting “a computing system” in the claim to perform such steps is merely adding the words “apply it” or using “a particular machine” with an abstract idea, or mere instructions to implement the abstract idea on a computer do not amount to significantly more than the abstract idea. See 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); See also RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1326-27, 122 USPQ2d 1377, 1379-80 (Fed. Cir. 2017) (the manipulation of information through a series of mental steps and a mathematical calculation, was held directed to an abstract idea)). Thus, simply implementing the abstract idea on a generic computer for performing generic computer functions do not amount to significantly more than the abstract idea. (MPEP 2106.05(a)-(c), (e-f) & (h)). In the Remarks on page 21, Applicant argues that neither Willemain, Sahaf, nor Cao, alone or in combination, teaches or suggests all of these features. For example, as amended recites, among other things, “determining…using a data structure that maps forecasting techniques to corresponding change point detection algorithms, a first change point detection algorithm associated with a first forecasting technique,”…and determining…using the second change point detection algorithm, a second change point of the first time series based…”. However, Applicant’s arguments are directed to the newly amended claims, and therefore, the newly amended claims will be fully addressed in this Office Action. 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. As per Step 1 of the subject matter eligibility analysis, it is to determine whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. In this case, claims 1-7 are directed to a method for generating forecasted value, which falls within the statutory category of a process. Claims 8-14 are directed to a system comprising one or more processors and a computer-readable medium, which falls within the statutory category of a machine. Claims 15-20 are directed to a non-transitory computer-readable storage medium storing computer instructions, which falls within the statutory category of a product. In Step 2A of the subject matter eligibility analysis, it is to “determine whether the claim at issue is directed to a judicial exception (i.e., an abstract idea, a law of nature, or a natural phenomenon). Under this step, a two-prong inquiry will be performed to determine if the claim recites a judicial exception (an abstract idea enumerated in the 2019 Guidance), then determine if the claim recites additional elements that integrate the exception into a practical application of the exception. See Revised 2019 Patent Subject Matter Eligibility Guidance (2019 Guidance), 84 Fed. Reg. 50, 54-55 (January 7, 2019). In Prong One, it is to determine if the claim recites a judicial exception (an abstract idea enumerated in the 2019 Guidance, a law of nature, or a natural phenomenon). Taking the method as representative, claim 1 recites limitations of “determining.. using a data structure that maps forecasting techniques to corresponding change point detection algorithms, determining…using the first change point detection algorithm, a first change point of the first time series, determining…using the data structure, a second change point detection algorithm associated with a second forecasting technique, determining…using the second change point detection algorithm, a second change point of the first time series, generating a first truncated time series based at least in part on the first point, generating a second truncated time series, generating a first forecasted value using a first forecasting technique and the first truncated time series, generating a second forecasted value using a second forecasting technique and the second truncated time series, determining a first forecast error between the first forecasted value and a second time series, determining a second forecast error between the first forecasted value and a second time series, determining a second forecast error…,, selecting the first forecasting technique or the second forecasting technique to generate a final forecasted value, and generating a final forecasted value”, dependent claims 2-7 recite limitations of “determining a first confidence score for the first candidate change point, determining a first relative position score for the first candidate change point, determining a first category score of the first candidate change point, determining an average of the first confidence score, comparing the first overall score of for the first candidate change point to a second overall score of a second candidate change point, selecting the first candidate change point to be the first change point, determining the first time series and the second time series, selecting a data point of a third time series, splitting the third time series into the first time series and the second time series, splitting the first time series at the first change point, determining a final truncated time series, extracting input features from the first truncated time series, and forecasting the final forecasted value”. None of the limitations recites technological implementation details for any of these steps, but instead recite only results desired by any and all possible means. The limitations, as drafted, are directed to processes, under their broadest reasonable interpretation, cover performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting “by a computing system” for performing the steps, nothing in the claim elements precludes the steps from practically being performed in the mind (including an observation, evaluation, judgment, opinion), or by a human using a pen and paper. For example, the claim encompasses a person can manually determining, generating, comparing, selecting which forecasting technique in the mind, or by a human using a pen and paper. Thus, the claims fall within the mental processes grouping. The mere nominal recitation of “by a computing system” does not take the claims out of the mental processes grouping. See Under the 2019 Guidance, 84 Fed. Reg. 52. Accordingly, the claims recite an abstract idea, and the analysis is proceeding to Prong Two. Beyond the abstract idea, the claims recite the additional elements of “by a computing system”. The Specification describes that “a computing system including one or more processors and a computer-readable medium” (see ¶ 13), and “by way of example, personal computers and/or laptop computers running various versions of Microsoft Windows, Apple Macintosh, and/or Linux operating systems.”(See ¶ 104). When given the broadest reasonable interpretation and in light of the Specification, the additional element is no more than generic computer and is recited at a high level of generality and amount to no more than adding the words “apply it” or using “a particular machine” with an abstract idea, or mere instructions to implement the abstract idea on a computer. Thus, merely adding a generic computer, generic computer components, or programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 2358-59, 110 USPQ2d 1976, 1983-84 (2014). Again, automating an abstract process does not convert it into a practical application. See Credit Acceptance v. Westlake Servs., 859 F.3d 1044, 1055 (Fed. Cir. 2017) (“Our prior cases have made clear that mere automation of manual processes using generic computers does not constitute a patentable improvement in computer technology.”); see also Bancorp Servs., L.L.C. v. Sun Life Assurance Co. of Canada (U.S.), 687 F.3d 1266, 1278 (Fed. Cir. 2012) (A computer “employed only for its most basic function . . . does not impose meaningful limits on the scope of those claims.”). However, simply implementing the abstract idea on a generic computer does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Further, nothing in the claims that reflects an improvement to the functioning of a computer itself or another technology, effects a transformation or reduction of a particular article to a different state or thing, or applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Therefore, the additional element does not integrate the judicial exception into a practical application. The claims are directed to an abstract idea, the analysis is proceeding to Step 2B. In Step 2B of Alice, it is "a search for an ‘inventive concept’—i.e., an element or combination of elements that is ‘sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept’ itself.’” Id. (alternation in original) (quoting Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1294 (2012)). The claims as described in Prong Two above, nothing in the claims that integrates the abstract idea into a practical application. The same analysis applies here in Step 2B. Beyond the abstract idea, the claims recite the additional elements of “by a computing system”. The Specification describes that “a computing system including one or more processors and a computer-readable medium” (see ¶ 13), and “by way of example, personal computers and/or laptop computers running various versions of Microsoft Windows, Apple Macintosh, and/or Linux operating systems.”(See ¶ 104). When given the broadest reasonable interpretation and in light of the Specification, the additional element is no more than generic computer and is recited at a high level of generality and merely invoked as tools to perform the generic computer functions. Taking the claim elements separately and as an ordered combination, the computing system (one or more processors), at best, may perform the generic computer functions including receiving, manipulating, and transmitting information over a network. However, generic computer for performing generic computer functions have been recognized by the courts as merely well-understood, routine, and conventional functions of generic computers. Again, reciting the additional element of a processor is merely adding the words “apply it” or using “a particular machine” with an abstract idea, or mere instructions to implement an abstract idea on a computer do not amount to significantly more than the abstract idea. See 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); Collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016); RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1326-27, 122 USPQ2d 1377, 1379-80 (Fed. Cir. 2017) (the manipulation of information through a series of mental steps and a mathematical calculation, was held directed to an abstract idea)). Thus, simply implementing the abstract idea on a generic computer for performing generic computer functions do not amount to significantly more than the abstract idea. (MPEP 2106.05(a)-(c), (e-f) & (h)). For the foregoing reasons, claims 1-7 cover subject matter that is judicially-excepted from patent eligibility under § 101 as discussed above, the other system claims 8-14 and medium claims 15-20 parallel claims 1-7—similarly cover claimed subject matter that is judicially excepted from patent eligibility under § 101. Therefore, the claims as a whole, viewed individually and as a combination, do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. The claims are not patent eligible. Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Willemain et al., (US 2022/00050763, hereinafter: Willemain), and in view of Sahaf (US 2022/0317674), and further in view of Cao et al., (US 2022/0065785, hereinafter: Cao), and Kautzner et al., (CN 100547615, hereinafter: Kautzner). Regarding claim 1, Willemain discloses a method, comprising: generating, by the computing system (see Fig. 5, # 103; ¶ 45, ¶ 51), a first truncated time series based at least in part on the first change point, the first truncated time series comprising a first subset of data points of the first time series ranging from the first change point to a youngest data point of the first time series (see ¶ 5-6, ¶ 21, ¶ 28); generating, by the computing system, a second truncated time series based at least in part on the second change point, the second truncated time series comprising a second subset of data points of the first time series ranging from the second change point to the youngest data point of the first time series (see ¶ 7, ¶ 25-27, ¶ 28); generating, by the computing system, a first forecasted value using a first forecasting technique and the first truncated time series (see ¶ 3, ¶ 21, ¶ 26); generating, by the computing system, a second forecasted value using a second forecasting technique and the second truncated time series (see ¶ 22, 42-44); selecting, by the computing system, the first forecasting technique or the second forecasting technique based on a comparison of the first forecast error and the second forecast error (see ¶ 7-9, ¶ 22, ¶ 24, ¶ 27, ¶ 40-42). Willemain discloses collecting time series data associated with resources and analyzing each of a plurality of time series to detect a change point occurred (see ¶ 7). Willemain does not explicitly disclose a first time series and a second time series; however, Sahaf in an analogous art for identifying subcomponent failure discloses determining, by a computing system, using the first change point detection algorithm a first time series comprising a first set of data points (see ¶ 100, ¶ 124, ¶ 216, claim 2). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain to include the teaching of Sahaf in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more specific time data set, and enabling better decision making. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Willemain discloses evaluating all possible change points for multiple comparison test (see ¶ 31). Willemain and Sahaf do not explicitly the following limitations; however, Cao in an analogous art for detecting change points discloses determining, by a computing system, using a data structure that maps forecasting techniques to corresponding change point detection algorithms, a first change point detection algorithm associated with a first forecasting technique (see ¶ 56-57, ¶ ¶ 81-84, ¶ 95, ¶ 104-105); determining, by the computing system, using the first change point detection algorithm, a first change point of the first time series based at least in part on a first relative position of the first change point in the first time series and a category of the first change point (see ¶ 56-57, ¶ 60-62, ¶ 95-97, ¶ 105, ¶ 145-148); determining, by the computing system, using the data structure, a second change point detection algorithm associated with a second forecasting algorithm (¶ 56-57, ¶ 81-84, ¶ 95, ¶ 104-105); determining, by the computing system, using the second change point detection algorithm, a second change point of the first time series based at least in part on a second relative position of the second change point in the first time series and a category of the second change point (see ¶ 56-57, ¶ 95-97, ¶ 105, ¶ 113-115, ¶ 146). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain and in view of Sahaf to include teaching of Cao in order to gain the commonly understood benefit of such adaption, such as providing the benefit of enhancing computational efficiency, in turn of operational efficiency. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Sahaf discloses determining a prediction error and a prediction error is calculated by comparing the random forest with the ground truth labels (see Fig. 5A; ¶ 163). Willemain, Sahaf and Cao do not explicitly the following limitations; however, Kautzner in an analogous art for representing changeable graphic model discloses determining, by the computing system, a first forecast error between the first forecasted value and a second time series (see pg. 3, ¶ 4-5; pg. 15, claim 1); determining, by the computing system, a second forecast error between the second forecasted value and a second time series (see pg. 3, ¶ 4-5; pg. 15, claim 1); and selecting, by the computing system, the first forecasting technique or the second forecasting technique based on a comparison of the first forecast error and the second forecast error (see pg. 3, ¶ 4-5; pg. 8, ¶ 2; pg. 15, claim 1); and generating, by the computing system, a final forecasted value using the selected forecasting technique (see pg. 8, ¶ 2; pg. 10, ¶ 7). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain and in view of Sahaf and Cao to include the teaching of Kautzner in order to gain the commonly understood benefit of such adaption, such as providing the benefit of an additional layer of analysis, resulting in more focused solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 2, Willemain does not explicitly the following limitations; however, Sahaf discloses the method of claim 1, wherein determining the first change point of the first time series comprises: determining a first confidence score for a first candidate change point (see ¶ 167, ¶ 179, ¶ 202); determining a first relative position score for the first candidate change point based at least in part on the relative position of the first candidate change point in the first time series (see ¶ 39, ¶ 51-52, ¶ 57-59); determining a first category score of the first candidate change point based at least in part on a first change point category (see ¶ 59-62, ¶ 113-116); determining an average of the first confidence score, the first relative position score, and the first category score to generate a first overall score of the first candidate change point (see ¶ 39, ¶ 64, ¶ 117-118); comparing the first overall score of the first candidate change point to a second overall score of a second candidate change point (see ¶ 27-29, ¶ 68, ¶ 115). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain to include the teaching of Sahaf in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more specific time data, and enabling better decision making. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Willemain and Sahaf do not explicitly disclose the following limitations; however, Cao discloses determining a first category score of the first candidate change point based at least in part on a first change point category (see ¶ 59-62, ¶ 113-116); selecting the first candidate change point to be the first change point based at least in part on the comparison (see ¶ 105). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain and in view of Sahaf to include teaching of Cao in order to gain the commonly understood benefit of such adaption, such as providing the benefit of enhancing computational efficiency, in turn of operational efficiency. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 3, Willemain does not explicitly the following limitations; however, Sahaf discloses the method of claim 2, wherein the first overall score is normalized overall score with respect to a second overall score (see ¶ 68-69). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain to include the teaching of Sahaf in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more specific time data, and enabling better decision making. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 4, Willemain discloses the method of claim 1, wherein method further comprises: determining the first time series and the second time series by: selecting a data point of a third time series based at least in part on avoidance of a forecasting bias (see Fig. 2, #S3; ¶ 27); and splitting the third time series into the first time series and the second time series based at least in part on the selected data point, the first time series comprising a training set of data points, the second time series comprising a testing set of data points (see Fig. 2, #S4; ¶ 8, ¶ 20, ¶ 26, claim 2). Regarding claim 5, Willemain discloses the method of claim 1, wherein generating the first truncated time series comprises splitting the first time series at the first change point (see ¶ 7, ¶ 21). Regarding claim 6, Willemain discloses the method of claim 1, wherein the first forecasting technique is selected, and wherein generating the final forecasted value comprises: determining a final truncated time series based at least in part on combining the selected first truncated time series with the second time series (see ¶ 7, ¶ 25-27); extracting input features from the final truncated time series (see ¶ 27, claim 17) ; and forecasting the final forecasted value based at least in part on the input features (see ¶ 22, ¶ 44). Regarding claim 7, Willemain discloses the method of claim 1, wherein the first forecasting technique comprises Prophet, autoregressive integrated moving average (ARIMA), deep learning-based forecasting, and machine learning-based forecasting (see ¶ 7, ¶ 42). In addition, claim 7 merely describing the characteristics of the first forecasting technique is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05). Regarding claim 8, Willemain discloses a computing system, comprising: one or more processors (see Fig. 5, # 103; ¶ 45, ¶ 51); and a computer-readable medium including instructions that, when executed by the one or more processors (see ¶ 46, ¶ 51), cause the one or more processors to perform operations comprising: generating a first truncated time series based at least in part on the first change point, the first truncated time series comprising a first subset of data points of the first time series ranging from the first change point to a youngest data point of the first time series (see ¶ 5-6, ¶ 21, ¶ 28); generating a second truncated time series based at least in part on the second change point, the second truncated time series comprising a second subset of data points of the first time series ranging from the second change point to the youngest data point of the first time series (see ¶ 7, ¶ 25-27, ¶ 28); generating a first forecasted value using a first forecasting technique and the first truncated time series (see ¶ 3, ¶ 21, ¶ 26); generating a second forecasted value using a second forecasting technique and the second truncated time series (see ¶ 22, 42-44). . Willemain discloses collecting time series data associated with resources and analyzing each of a plurality of time series to detect a change point occurred (see ¶ 7). Willemain does not explicitly disclose a first time series and a second time series; however, Sahaf discloses determining a first time series comprising a first set of data points (see ¶ 100, ¶ 124, ¶ 216, claim 2). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain to include the teaching of Sahaf in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more specific time data set, and enabling better decision making. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Willemain discloses evaluate all possible change points can be considered a multiple comparison test (see ¶ 31). Willemain and Sahaf do not explicitly the following limitations; however, Cao discloses determining, using a data structure that maps forecasting techniques to corresponding change point detection algorithms, a first change point detection algorithm associated with a first forecasting technique (see ¶ 56-57, ¶ ¶ 81-84, ¶ 95, ¶ 104-105); determining a first change point of the first time series based at least in part on a first relative position of the first change point in the first time series and a category of the first change point (see ¶ 56-57, ¶ 60-62, ¶ 95-97, ¶ 105, ¶ 145-148); determining, using the data structure, a second change point detection algorithm associated with a second forecasting algorithm (¶ 56-57, ¶ 81-84, ¶ 95, ¶ 104-105); determining, using the second change point detection algorithm, a second change point of the first time series based at least in part on a second relative position of the second change point in the first time series and a category of the second change point (see ¶ 56-57, ¶ 95-97, ¶ 105, ¶ 113-115, ¶ 146). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain and in view of Sahaf to include teaching of Cao in order to gain the commonly understood benefit of such adaption, such as providing the benefit of enhancing computational efficiency, in turn of operational efficiency. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Sahaf discloses determining a prediction error and a prediction error is calculated by comparing the random forest with the ground truth labels (see Fig. 5A; ¶ 163). Willemain, Sahaf and Cao do not explicitly the following limitations; however, Kautzner discloses determining, by the computing system, a first forecast error between the first forecasted value and a second time series (see pg. 3, ¶ 4-5; pg. 15, claim 1); determining, by the computing system, a second forecast error between the second forecasted value and a second time series (see pg. 3, ¶ 4-5; pg. 15, claim 1); and selecting the first forecasting technique or the second forecasting technique based on a comparison of the first forecast error and the second forecast error (see pg. 3, ¶ 4-5; pg. 8, ¶ 2; pg. 15, claim 1); and generating a final forecasted value using the selected forecasting technique (see pg. 8, ¶ 2; pg. 10, ¶ 7). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain and in view of Sahaf and Cao to include the teaching of Kautzner in order to gain the commonly understood benefit of such adaption, such as providing the benefit of an additional layer of analysis, resulting in more focused solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 9, Willemain does not explicitly the following limitations; however, Sahaf discloses the computing system of claim 8, wherein determining the first change point of the first time series comprises: determining a first confidence score for a first candidate change point (see ¶ 167, ¶ 179, ¶ 202); determining a first relative position score for the first candidate change point based at least in part on the relative position of the first candidate change point in the first time series (see ¶ 39, ¶ 51-52, ¶ 57-59); determining an average of the first confidence score, the first relative position score, and the first category score to generate a first overall score of the first candidate change point (see ¶ 39, ¶ 64, ¶ 117-118); comparing the first overall score of the first candidate change point to a second overall score of a second candidate change point (see ¶ 27-29, ¶ 68, ¶ 115). Willemain and Sahaf do not explicitly disclose the following limitations; however, Cao discloses determining a first category score of the first candidate change point based at least in part on a first change point category (see ¶ 59-62, ¶ 113-116); selecting the first candidate change point to be the first change point based at least in part on the comparison (see ¶ 105). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain and in view of Sahaf to include teaching of Cao in order to gain the commonly understood benefit of such adaption, such as providing the benefit of enhancing computational efficiency, in turn of operational efficiency. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 10, Willemain does not explicitly the following limitations; however, Sahaf discloses the computing system of claim 9, wherein the first overall score is normalized overall score with respect to a second overall score (see ¶ 68-69). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain to include the teaching of Sahaf in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more specific time data, and enabling better decision making. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 11, Willemain discloses the computing system of claim 8, wherein the instructions that, when executed by the one or more processors, further cause performance of operations comprising: determining the first time series and the second time series by: selecting a data point of a third time series based at least in part on avoidance of a forecasting bias (see Fig. 2, #S3; ¶ 27); and splitting the third time series into the first time series and the second time series based at least in part on the selected data point, the first time series comprising a training set of data points, the second time series comprising a testing set of data points (see Fig. 2, #S4; ¶ 8, ¶ 20, ¶ 26, claim 2). Regarding claim 12, Willemain discloses the computing system of claim 8, wherein generating the first truncated time series comprises splitting the first time series at the first change point (see ¶ 7, ¶ 21). Regarding claim 13, Willemain discloses the computing system of claim 8, wherein the first forecasting technique is selected, and wherein generating the final forecasted value comprises: determining a final truncated time series based at least in part on combining the selected first truncated time series with the second time series (see ¶ 7, ¶ 25-27); extracting input features from the final truncated time series (see ¶ 27, claim 17); and forecasting the final forecasted value based at least in part on the input features (see ¶ 22, ¶ 44). Regarding claim 14, Willemain discloses the computing system of claim 8, wherein the first forecasting technique comprises Prophet, autoregressive integrated moving average (ARIMA), deep learning-based forecasting, and machine learning-based forecasting (see ¶ 7, ¶ 42). In addition, claim 7 merely describing the characteristics of the first forecasting technique is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05). Regarding claim 15, Willemain discloses a non-transitory computer-readable medium including stored thereon a sequence of instructions that, when executed by one or more processors (see ¶ 26-28), causes performance of operations comprising: generating a first truncated time series based at least in part on the first change point, the first truncated time series comprising a first subset of data points of the first time series ranging from the first change point to a youngest data point of the first time series (see ¶ 5-6, ¶ 21, ¶ ¶ 28); generating a second truncated time series based at least in part on the second change point, the second truncated time series comprising a second subset of data points of the first time series ranging from the second change point to the youngest data point of the first time series (see ¶ 7, ¶ 25-27, ¶ 28); generating a first forecasted value using a first forecasting technique and the first truncated time series (see ¶ 3, ¶ 21, ¶ 26); generating a second forecasted value using a second forecasting technique and the second truncated time series (see ¶ 22, 42-44). selecting the first forecasting technique or the second forecasting technique based on a comparison of the first forecast error and the second forecast error (see ¶ 7-9, ¶ 22, ¶ 24, ¶ 27, ¶ 40-42). Willemain discloses collecting time series data associated with resources and analyzing each of a plurality of time series to detect a change point occurred (see ¶ 7). Willemain does not explicitly disclose a first time series and a second time series; however, Sahaf in an analogous art for identifying subcomponent failure discloses determining a first time series comprising a first set of data points (see ¶ 100, ¶ 124, ¶ 216, claim 2). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain to include the teaching of Sahaf in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more specific time data set, and enabling better decision making. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Willemain discloses evaluate all possible change points can be considered a multiple comparison test (see ¶ 31). Willemain and Sahaf do not explicitly the following limitations; however, Cao in an analogous art for detecting change points discloses determining, using a data structure that maps forecasting techniques to corresponding change point detection algorithms, a first change point detection algorithm associated with a first forecasting technique (see ¶ 56-57, ¶ ¶ 81-84, ¶ 95, ¶ 104-105); determining, using the first change point detection algorithm, a first change point of the first time series based at least in part on a first relative position of the first change point in the first time series and a category of the first change point (see ¶ 56-57, ¶ 60-62, ¶ 95-97, ¶ 105, ¶ 145-148); determining, using the data structure, a second change point detection algorithm associated with a second forecasting algorithm (¶ 56-57, ¶ 81-84, ¶ 95, ¶ 104-105);; determining, using the second change point detection algorithm, a second change point of the first time series based at least in part on a second relative position of the second change point in the first time series and a category of the second change point (see ¶ 56-57, ¶ 95-97, ¶ 105, ¶ 113-115, ¶ 146). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain and in view of Sahaf to include teaching of Cao in order to gain the commonly understood benefit of such adaption, such as providing the benefit of enhancing computational efficiency, in turn of operational efficiency. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Sahaf discloses determining a prediction error and a prediction error is calculated by comparing the random forest with the ground truth labels (see Fig. 5A; ¶ 163). Willemain, Sahaf and Cao do not explicitly the following limitations; however, Kautzner discloses determining, by the computing system, a first forecast error between the first forecasted value and a second time series (see pg. 3, ¶ 4-5; pg. 15, claim 1); determining, by the computing system, a second forecast error between the second forecasted value and a second time series (see pg. 3, ¶ 4-5; pg. 15, claim 1); and selecting the first forecasting technique or the second forecasting technique based on a comparison of the first forecast error and the second forecast error (see pg. 3, ¶ 4-5; pg. 8, ¶ 2; pg. 15, claim 1); and generating a final forecasted value using the selected forecasting technique (see pg. 8, ¶ 2; pg. 10, ¶ 7). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain and in view of Sahaf and Cao to include the teaching of Kautzner in order to gain the commonly understood benefit of such adaption, such as providing the benefit of an additional layer of analysis, resulting in more focused solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 16, Willemain does not explicitly the following limitations; however, Sahaf discloses the non-transitory computer-readable medium of claim 15, wherein determining the first change point of the first time series comprises: determining a first confidence score for a first candidate change point (see ¶ 167, ¶ 179, ¶ 202); determining a first relative position score for the first candidate change point based at least in part on the relative position of the first candidate change point in the first time series (see ¶ 39, ¶ 51-52, ¶ 57-59); determining an average of the first confidence score, the first relative position score, and the first category score to generate a first overall score of the first candidate change point (see ¶ 39, ¶ 64, ¶ 117-118); comparing the first overall score of the first candidate change point to a second overall score of a second candidate change point(see ¶ 27-29, ¶ 68, ¶ 115). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain to include the teaching of Sahaf in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more specific time data, and enabling better decision making. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Willemain and Sahaf do not explicitly disclose the following limitations; however, Cao discloses determining a first category score of the first candidate change point based at least in part on a first change point category (see ¶ 59-62, ¶ 113-116); selecting the first candidate change point to be the first change point based at least in part on the comparison (see ¶ 105). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain and in view of Sahaf to include teaching of Cao in order to gain the commonly understood benefit of such adaption, such as providing the benefit of enhancing computational efficiency, in turn of operational efficiency. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 17, Willemain does not explicitly the following limitations; however, Sahaf discloses the non-transitory computer-readable medium of claim 16, wherein the first overall score is normalized overall score with respect to a second overall score (see ¶ 68-69). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Willemain to include the teaching of Sahaf in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more specific time data, and enabling better decision making. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 18, Willemain discloses the non-transitory computer-readable medium of claim 15, wherein the instructions that, when executed by the one or more processors, further cause performance of operations comprising: determining the first time series and the second time series by: selecting a data point of a third time series based at least in part on avoidance of a forecasting bias (see Fig. 2, #S3; ¶ 27); and splitting the third time series into the first time series and the second time series based at least in part on the selected data point, the first time series comprising a training set of data points, the second time series comprising a testing set of data points (see Fig. 2, #S4; ¶ 8, ¶ 20, ¶ 26, claim 2). Regarding claim 19, Willemain discloses the non-transitory computer-readable medium of claim 15, wherein generating the first truncated time series comprises splitting the first time series at the first change point (see ¶ 7, ¶ 21). Regarding claim 20, Willemain discloses the non-transitory computer-readable medium of claim 15, wherein the first forecasting technique is selected, and wherein generating the final forecasted value comprises: determining a final truncated time series based at least in part on combining the selected first truncated time series with the second time series (see ¶ 7, ¶ 25-27); extracting input features from the final truncated time series (see ¶ 27, claim 17); and forecasting the final forecasted value based at least in part on the input features (see ¶ 22, ¶ 44). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Okutani, (JP 2018147442) discloses a method for change point detection amount of time series data. Nakamura, (WO 2022003969) discloses a data processing device comprising a time series acquisition unit for acquiring time series data, a feature extraction unit for extracting the feature amount of the time series data, a first division unit for dividing the time series data into a plurality of items of first partial time series data, and a second division unit for dividing each of the plurality of items of first partial time series data. Xia et al., (CN 112651539) discloses an information processing apparatus for detecting a plurality of change points from the history characteristic data sequence of the object using a first data dividing unit, a first data partition unit, and a training unit configured to train the predictor of the object based on a plurality of data segments. Xu et al., (US 11651271 B1) discloses a system for detecting a future change point in time series data used as input to a machine learning model to generate a forecast for the time series data and extract data features from individual segments in the time series data. Liu, “Sequential Change-point Detection for Time Series”, Northwestern University, June 2022. Bijak et al., “Assessing time series models for forecasting international migration: Lessons from the United Kingdom”, Wiley, Research Article. 31, January 2019. 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 PAN CHOY whose telephone number is (571)270-7038. The examiner can normally be reached 5/4/9 compressed work schedule. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached on 571-272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /PAN G CHOY/Primary Examiner, Art Unit 3624
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Prosecution Timeline

Apr 25, 2023
Application Filed
Mar 05, 2026
Non-Final Rejection mailed — §101, §103
Jun 02, 2026
Applicant Interview (Telephonic)
Jun 02, 2026
Examiner Interview Summary
Jun 16, 2026
Response Filed
Sep 11, 2026
Final Rejection mailed — §101, §103 (current)

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