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 .
Status of the Claims
Claims 1-2, 4-8, 10-14, and 16-18 were currently pending. Claims 1, 7, and 13 were amended in the reply filed June 24, 2026. Claims 1-2, 4-8, 10-14, and 16-18 are currently pending.
Response to Arguments
Applicant's arguments with respect to the rejection made under § 101 have been fully considered but are not persuasive. Applicant analogizes the claims to Example 39. Remarks, 12. However, this claim was eligible not because it recites training sets, but because it does not recite an abstract idea. Applicant does not present any reasons as to why the claims do not recite certain methods of organizing human activities or mathematical calculations. The mere presence of additional elements in a claim does not mean that an abstract idea is not also present at this point in the framework. Accordingly, the rejection is maintained.
Specification
The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o). Correction of the following is required: the detailed description lacks antecedent basis for the claim terms "training," "temporal transformation," "anomalous pricing behavior."
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-2, 4-8, 10-14, and 16-18 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
As amended, the independent claims recite: "the boosting model is generated by: creating a first training dataset from the clustered dataset comprising historical transaction data for a first time window by applying a temporal transformation to each historical transaction record in the first training dataset based on the age of the historical transaction record in time periods relative to a current time period; training the boosting model in a first stage using the first training dataset; creating a second training dataset utilizing the first training dataset by transforming historical transaction records from the clustered dataset identified as exhibiting anomalous pricing behavior; training the boosting model in a second stage using the second training dataset."
There is no form of "training" described in the disclosure, as it would be understood to one having ordinary skill in the art. The models set forth there are not described as being machine learning models and instead are purely mathematical (see ¶¶ 0060-77). The term "temporal transformation" also does not appear in the disclosure, and it is not sufficiently clear that the "temporally-weighted historical data" (¶ 0061) is commensurate in scope with a "temporal transformation." Similarly, the phrase/term "exhibiting anomalous pricing behavior" also does not appear in the disclosure, and it is not sufficiently clear which element in the Specification this is referencing. The dependent claims inherit the rejections of their respective base claims and, as such, are rejected for the same reasons.
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, 4-8, 10-14, and 16-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter (abstract idea without significantly more). Claims are eligible for patent protection under § 101 if they are in one of the four statutory categories and not directed to a judicial exception to patentability. Alice Corp. v. CLS Bank Int'l, 573 U.S. 208 (2014). Claims 1-2, 4-8, 10-14, and 16-18, each considered as a whole and as an ordered combination, are directed to a judicial exception (i.e., an abstract idea) without significantly more.
MPEP 2106 Step 2A – Prong 1:
The claims recite an abstract idea reflected in the recited representative functions of the independent claims—including:
presenting used vehicle pricing for a geographic area;
obtaining data from distributed data sources, the data from the distributed data sources including historical transaction data comprising: individual historical transaction data for a plurality of vehicles having a plurality of vehicle configurations in a plurality of geographic regions, wherein each vehicle configuration in the plurality of vehicle configurations comprise one or more factors, including a year, make and model, and wherein the individual historical transaction data for the plurality of sold vehicles comprises sale prices and vehicle specific usage data for the plurality of sold vehicles;
storing the historical transaction data for the plurality of vehicle configurations;
performing a process divided into a back end process and a front end process, the back end process performed at a time interval preceding and asynchronously to the front end process, wherein the back end process comprises: clustering the historical transaction data for the plurality of sold vehicles into a clustered dataset, the clustered dataset including a subset of the historical transaction data of a plurality of sold vehicles of different makes, wherein the subset of the historical transaction data for the plurality of sold vehicles includes a vehicle configuration factor common to the plurality of sold vehicles in the subset to overcome sparse historical transaction data; generating a boosting model from the clustered dataset of historical transaction data for modelling pricing adjustments for an average vehicle based on the vehicle configuration factors of the subset, wherein the boosting model comprises an exponentially weighted moving average St=αYt-1+(1- α)St-1, wherein St represents the exponentially weighted moving average in week t, St-1 represents the exponentially weighted moving average in week t-1, α is a parameter controlling how quickly historical transactions are discounted and Yt-1 is price of transactions occurring in week t-1, and the boosting model is generated by: creating a first training dataset from the clustered dataset comprising historical transaction data for a first time window by applying a temporal transformation to each historical transaction record in the first training dataset based on the age of the historical transaction record in time periods relative to a current time period; creating a second training dataset utilizing the first training dataset by transforming historical transaction records from the clustered dataset identified as exhibiting anomalous pricing behavior; generating a regionality model based on the historical transaction data and the plurality of geographic regions, the regionality model incorporating factors including seasonality and regionality; standardizing the historical transaction data by applying the boosting model to the historical transaction data to adjust the sales price associated with each historical individual transaction;Attorney Docket No.Application No. 16/433,521TCAR1620-1Customer ID: 44654 5storing the boosting model; and wherein the front end process comprises: receiving, from a client, user input data about a used vehicle in a location, including a user vehicle configuration including values for each of the one or more factors for the used vehicle configuration; responsive to the user input data that includes the values for the used vehicle configuration, determining a base model value from a back-end process for the used vehicle based on the standardized historical transaction data for the used vehicle configuration and the user input data that includes the values for the used vehicle configuration;
adjusting the base model value for the used vehicle using the boosting model to generate a final price for the used vehicle configuration based on the values for each of the one or more factors for the used vehicle configuration;
adjusting the final price for the used vehicle based on the location and the regionality model;
generating the adjusted final price for the used vehicle; and
communicating the [adjusted final price] in response to receiving the user input data;
configuring the values for the used vehicle configuration in the location, the configuring including adjusting the one or more factors and individual pieces of the used vehicle configuration so as to increase efficiency of the front end process while tailoring to the used vehicle configuration in the location.
This qualifies as a certain method of organizing human activities because it recites collecting, analyzing, and outputting information to arrive at optimal price values for vehicles (i.e., in the terminology of the 2019 Revised Guidance fundamental economic practices; commercial interactions (including marketing or sales activities or behaviors; business relations)). Additionally, aside from the general technological environment (addressed below), it recites several mathematical relationships/calculations (i.e., mathematically modeling and adjusting the models to arrive at a numerical result (i.e., a price) based on other numerical data, inputs, factors, and formulas (see published Specification ¶¶ 0027, 60-77, 82 and their analogous recitations in the claim)).
It shares similarities with other abstract ideas held to be non-statutory by the courts (see Versata Development Group, Inc. v. SAP America, Inc., 793 F.3d 1306 (Fed. Cir. 2015)—determining a price using organizational and product group hierarchies, similar because at another level of abstraction the claims could be characterized as determining a price using vehicle configurations and other data; OIP Technologies, Inc. v. Amazon.com, Inc., 788 F.3d 1359 (Fed. Cir. 2015)—price optimization based on factors such as offers, similar because at another level of abstraction the claims could be characterized as price modeling based on factors such as vehicle configurations, transaction data, etc.).
These cases all describe significantly similar aspects of the claimed invention, albeit at another level of abstraction. See Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1240-41 (Fed. Cir. 2016) ("An abstract idea can generally be described at different levels of abstraction. As the Board has done, the claimed abstract idea could be described as generating menus on a computer, or generating a second menu from a first menu and sending the second menu to another location. It could be described in other ways, including, as indicated in the specification, taking orders from restaurant customers on a computer.").
MPEP 2106 Step 2A – Prong 2:
This judicial exception is not integrated into a practical application because there are no meaningful limitations that transform the exception into a patent eligible application. The elements merely serve to provide a general link to a technological environment (e.g., computers and the Internet) in which to carry out the judicial exception (server computer with a visual interface that provides a web site or web service on Internet, the visual interface having user interface elements, the server computer having a processor and a non-transitory computer-readable medium storing instructions; processor, a non-transitory computer-readable medium, data store, "online process," client device with a visual interface, generating a web page; and communicating the web page to the client device, wherein the web page is generated and communicated to the client device in response to the vehicle data system receiving the user input data from the client device, configuring the user interface elements with user-adjustable user interface elements—all recited at a high level of generality).
The claims also recite training the boosting model in a first stage using the first training dataset and training the boosting model in a second stage using the second training dataset. However, choosing which data is used to train a model is not a patent-eligible improvement to machine learning. Instead, it further describes part of the general link to a technological environment in which the abstract idea is executed, as training on selected data is a generic feature of all machine learning implementations. "[P]atents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101." Recentive Analytics, Inc. v. Fox. Corp., Fed Cir. No. 2023-2437 (Apr. 18, 2025) (slip op. at 18). "The requirements that the machine learning model be 'iteratively trained' or dynamically adjusted in the Machine Learning Training patents do not represent a technological improvement." Id. at 12 (emphasis added).
Although the claims have and execute instructions to perform the abstract idea itself (e.g., modules, program code, "vehicle data application," etc. to automate the abstract idea), this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." Aside from such instructions to implement the abstract idea, they are solely used for generic computer operations (e.g., receiving, storing, retrieving, transmitting data), employing the computer as a tool. See FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1096 (Fed. Cir. 2016) ("[T]he use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent-eligible subject matter.") (citing DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245,1256 (Fed. Cir. 2014)) (emphasis added). The generating and communicating of the web page to the client device in response to the vehicle data system receiving the user input data from the client device can also be considered an insignificant extra-solution activity which is merely outputting the result of the abstract pricing algorithm to the user (i.e., an insignificant application of technology tangentially related to the invention similar to the printing or downloading of menus in Ameranth—see MPEP 2106.05(g)).
The claims only manipulate abstract data elements into another form. They do not set forth improvements to another technological field or the functioning of the computer itself and instead use computer elements as tools to improve the functioning of the abstract idea identified above (i.e., by applying the abstract idea in the context of generic computerized devices connected via the Internet). Looking at the additional limitations and abstract idea as an ordered combination and as a whole adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Rather than any meaningful limits, their collective functions merely provide generic computer implementation of the abstract idea identified in Prong One. None of the additional elements recited "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Alice Corp., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
At the levels of abstraction described above, the claims do not readily lend themselves to a finding that they are directed to a nonabstract idea. Therefore, the analysis proceeds to step 2B. See BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1349 (Fed. Cir. 2016) ("The Enfish claims, understood in light of their specific limitations, were unambiguously directed to an improvement in computer capabilities. Here, in contrast, the claims and their specific limitations do not readily lend themselves to a step-one finding that they are directed to a nonabstract idea. We therefore defer our consideration of the specific claim limitations’ narrowing effect for step two.") (citations omitted).
MPEP 2106 Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the same reasons as presented in Step 2A Prong 2 (i.e., they amount to nothing more than a general link to a particular technological environment and instructions to apply it there). Moreover, the additional elements recited are known and conventional computing elements. See published Specification describing these at a high level of generality and in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy the statutory disclosure requirements (server computer with a visual interface that provides a web site or web service on Internet, the visual interface having user interface elements, the server computer having a processor and a non-transitory computer-readable medium storing instructions (published Specification ¶¶ 0037, 95, 100-102), data store (¶ 0036), vehicle data application (¶ 0034), "online process" (i.e., a process running on the Internet—¶ 0095), client device with a visual interface (¶ 0035), generating a web page (¶ 0035), and communicating the web page to the client device, wherein the web page is generated and communicated to the client device in response to the vehicle data system receiving the user input data from the client device (¶ 0035)), configuring the user interface elements with user-adjustable user interface elements (¶ 0026; see also Fig. 9 showing conventional interface elements such as sliders, which are not described in the disclosure at any level of detail). The claims also recite training the boosting model in a first stage using the first training dataset and training the boosting model in a second stage using the second training dataset, but training a model is not described in the Specification at any level of detail. Moreover, these limitations do not demonstrate a patent-eligible improvement to technology for the same reasons as in Prong Two above.
The Federal Circuit has recognized that "an invocation of already-available computers that are not themselves plausibly asserted to be an advance, for use in carrying out improved mathematical calculations, amounts to a recitation of what is 'well-understood, routine, [and] conventional.'" SAP Am., Inc. v. InvestPic, LLC, 890 F.3d 1016, 1023 (Fed. Cir. 2018) (alteration in original) (citing Mayo v. Prometheus, 566 U.S. 66, 73 (2012)). Apart from the instructions to implement the abstract idea, they only serve to perform well-understood functions (e.g., receiving, storing, retrieving, transmitting data—see Specification above as well as Alice Corp.; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016); and Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) covering the well-known nature of these computer functions).
"The use and arrangement of conventional and generic computer components recited in the claims—such as a database, user terminal, and server— do not transform the claim, as a whole, into 'significantly more' than a claim to the abstract idea itself. We have repeatedly held that such invocations of computers and networks that are not even arguably inventive are insufficient to pass the test of an inventive concept in the application of an abstract idea." Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1056 (Fed. Cir. 2017) (citations and quotation marks omitted). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Dependent Claims Step 2A:
The limitations of the dependent claims merely set forth further refinements of the abstract idea without changing the analysis already presented (i.e., they only further limit aspects of the same abstract idea identified above without adding any new additional elements beyond it). Additionally, for the same reasons as above, when viewed in combination the limitations fail to integrate the abstract idea into a practical application because they use the same general link to technological environment and instructions to implement the abstract idea as the independent claims (i.e., generic computers and the Internet).
Dependent Claims Step 2B:
The dependent claims merely use the same general link to a technological environment and instructions to implement the abstract idea without adding any new additional elements beyond it. The Specification also indicates this is the routine use of known components for the same reasons presented with respect to the elements in the independent claims above. Accordingly, they are not directed to significantly more than the exception itself, and are not eligible subject matter under § 101.
Conclusion
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 DANIEL VETTER whose telephone number is (571)270-1366. The examiner can normally be reached M-F 9:00-6:00.
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/DANIEL VETTER/Primary Examiner, Art Unit 3628
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