DETAILED ACTION
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
This action is in reply to Application 18/627,823 filed on 5 April 2024.
Claims 1-20 are currently pending, have been examined, and are allowed.
Information Disclosure Statement
The Information Disclosure Statement filed 7 May 2024 has been considered. An initialed copy of the Form 1449 are enclosed herewith.
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.
In the instant case, representative method claim 11 is directed towards facilitating providing automated vehicle transaction support involving the use of rules and/or instructions to perform the steps of merely receiving, filtering, generating, calculating (“scoring”), and displaying product-related (e.g., “vehicle”) data/information associated with performing a commercial (“bid”) transaction, which is grouped under the certain methods of organizing human activity – fundamental economic principles, practices or concepts; sales activity; following set of instructions; commercial or legal interactions (agreements in the form of contracts; business relations); managing interactions between people (including social activities, teachings, following rules or instructions), and mathematical concepts – mathematical relationships groupings, in prong one of step 2A (See 2019 Revised Patent Subject Matter Eligibility Guidance), inasmuch as the claimed method as a whole is directed towards generating filtered and scored vehicle transaction support data associated with a plurality of vehicles for use in conjunction with a bidding transaction, involving steps which are nothing more than merely base on rules and instructions , but for the recitation of computer-related components.
Facilitating the filtering and scoring of product-related data/information provided in a commercial transaction is a fundamental economic/commercial practice that falls within the certain methods of organizing human activity (e.g., fundamental economic principles, practices or concepts (e.g., risk mitigation); managing personal behavior of relationships or interactions between people) grouping of abstract ideas, whereas performing the calculations utilizing the mathematical concepts/techniques indicated in the claims falls within the mathematical concepts grouping of abstract ideas. Other than the mere nominal recitation of computer-related devices in the claim – nothing in the claim element precludes the steps from the organizing human interactions, and mathematical concepts groupings. Accordingly, for these reasons, the claim recites an abstract idea.
Claim 11 recites: “receiving vehicle source data indicating vehicles available from at least one vehicle source; filtering the vehicle source data based on vehicle filter parameters and generating filtered vehicle source data responsive thereto indicating a plurality of the vehicles; generating, based on vehicle requirements data and the filtered vehicle source data … filtered and scored vehicle source data that indicates scores associated with the plurality of the vehicles; receiving, …, vehicle selection data corresponding to selected ones of the plurality of the vehicles; generating, in respond to the vehicle selection data, vehicle bid data corresponding to the selected ones of the plurality of the vehicles; and sending the vehicle bid data to the at least one vehicle source.”
The steps merely comprise merely the use of rules and/or instructions to perform the steps of receiving, filtering, generating, calculating (“scoring”), and displaying product-related (e.g., “vehicle”) data/information associated with performing a commercial (“bid-purchase”) transaction and, thus, do no more than add insignificant extra-solution activity to the judicial exception (see MPEP § 2106.05(g)). Accordingly, the claim recites an abstract idea (See 2019 Revised Patent Subject Matter Eligibility Guidance).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A (See 2019 Revised Patent Subject Matter Eligibility Guidance), the additional elements of the claim such as a “processor”, “scoring engine”, “graphical user interface”, “AI model”, “machine learning”, represent the use of a computer as an intermediary and/or tool to perform an abstract idea and/or does no more than generally link the abstract idea to a particular field of use (e.g., particular technological environment (MPEP 2106.04 (d) I)). Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to (i.e. automate) implementing the acts of the use of rules and/or instructions to perform the steps of receiving, filtering, generating, calculating (“scoring”), and displaying product-related (e.g., “vehicle”) data/information associated with performing a commercial (“bid-purchase”) transaction.
When analyzed under step 2B (See 2019 Revised Patent Subject Matter Eligibility Guidance), the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself. Viewed as a whole, the combination of elements recited in the claims merely describe the concept of the use of rules and/or instructions to perform the steps of receiving, filtering, generating, calculating (“scoring”), and displaying product-related (e.g., “vehicle”) data/information associated with performing a commercial (“bid-purchase”) transaction using computer technology. Therefore, the use of these additional elements does no more than employ a computer as a tool to automate and/or implement the abstract idea, which cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)).
Hence, claim 11 is not patent eligible.
Independent claim 1 recites substantially the same limitations as claim 11 above and are ineligible for the same reasons. The subject matter of claim 1 corresponds to the subject matter of claim 11 in terms of a system (e.g., machine). Therefore the reasoning provided for claim 11 applies to claim 1 accordingly.
Dependent claims 2-10 and 12-20 add further details and contain limitations that narrow the scope of the invention. However, these details do not result in significantly more than the abstract idea itself. As explained in the December 16, 2014 Interim Eligibility Guidance from the USPTO (in reference to the BuySAFE, Inc. v. Google, Inc. decision), further narrowing the details of an abstract idea does not change the § 101 analysis since a more narrow abstract idea does not make it any less abstract.
Viewed individually and in combination, these additional elements do not provide meaningful limitations to transform the abstract idea such that the claims amount to significantly more than the abstraction itself.
Accordingly, the present pending claims are not patent eligible and are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections – 35 USC § 103
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 Hoover et al., US 10,902,515 B1(“Hoover”), in view of Dalinina et al., US 2020/0342478 A1 (“Dalinina”).
Re Claim 1: Hoover discloses a vehicle transaction support system, comprising:
at least one processing system that includes a processor; (C2 L11-44)
at least one memory including a non-transitory computer readable storage medium that stores executable instructions that, when executed by the at least one processing system, cause performance of operations that include: (C2 L11-44)
receiving vehicle source data indicating vehicles available from at least one vehicle source; (C1 L14-44; C6 L23-35; C9 L3-20; C12 L49-67; C22 L26-46)
filtering the vehicle source data based on vehicle filter parameters and generating filtered vehicle source data responsive thereto indicating a plurality of the vehicles; (C1 L14-44; C6 L23-35; C9 L3-20; C12 L49-67; C22 L26-46)
Regarding the limitation feature comprising:
generating, based on vehicle requirements data and the filtered vehicle source data and utilizing a vehicle scoring engine having at least one artificial intelligence (AI) model trained via machine learning, filtered and scored vehicle source data that indicates scores associated with the plurality of the vehicles;
Dalinina makes this teaching in a related endeavor (¶¶[5, 6, 9, 10, 11, 13, 23, 43, 58, 63, 72, 73, 85, 86, 96, 97, 106). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Dalinina with the invention of Hoover as disclosed above for the motivation of providing filter criteria to assist in narrowing available vehicle inventory choices.
Hoover further discloses:
receiving, via a graphical user interface, vehicle selection data corresponding to selected ones of the plurality of the vehicles; (C1 L14-44; C6 L23-35; C9 L3-20; C12 L49-67; C14 L15-20; C22 L26-46)
generating, in respond to the vehicle selection data, vehicle bid data corresponding to the selected ones of the plurality of the vehicles; (C1 L14-44; C2 L65-67; C3 L1-13; C7 L9-22; C6 L23-35; C9 L3-20; C12 L49-67; C22 L26-46)
sending the vehicle bid data to the at least one vehicle source. (C1 L14-44; C6 L23-35; C9 L3-20; C12 L49-67; C22 L26-46)
Re Claim 2: Hoover in view of Dalinina discloses the vehicle transaction support system of claim 1. Hoover further discloses:
wherein the graphical user interface displays a subset of the plurality of the vehicles that is generated based on a comparison of scores indicated by the filtered and scored vehicle source data and a scoring threshold. (C4 L5-30; C7 L60-67; C8 L1-6)
Re Claim 3: Hoover in view of Dalinina discloses the vehicle transaction support system of claim 1. Hoover further discloses:
wherein the graphical user interface displays at least a subset of the plurality of the vehicles that is rank ordered based on scores indicated by the filtered and scored vehicle source data. (C4 L5-30; C7 L60-67; C8 L1-6)
Re Claim 4: Hoover in view of Dalinina discloses the vehicle transaction support system of claim 1. Regarding the limitation feature(s) comprising:
wherein the at least one AI model includes a plurality of AI models.
Dalinina makes this teaching in a related endeavor (¶¶[5, 6, 9, 10, 11, 13, 23, 43, 58, 63, 72, 73, 85, 86, 96, 97, 106). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Dalinina with the invention of Hoover as disclosed above for the motivation of providing filter criteria to assist in narrowing available vehicle inventory choices.
Re Claim 5: Hoover in view of Dalinina discloses the vehicle transaction support system of claim 4. Regarding the limitation feature(s) comprising:
wherein the plurality of AI models includes at least one of:
a vehicle desirability model trained via machine learning to generate a vehicle desirability score;
a vehicle net present value (NPV) model trained via machine learning to generate a vehicle NPV score;
a vehicle reliability model trained via machine learning to generate a vehicle reliability score; or
a vehicle cost conditioning model trained via machine learning to generate a vehicle cost conditioning score.
Dalinina makes this teaching in a related endeavor (¶¶[5, 6, 9, 10, 11, 13, 23, 43, 58, 63, 72, 73, 85, 86, 96, 97, 106). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Dalinina with the invention of Hoover as disclosed above for the motivation of providing filter criteria to assist in narrowing available vehicle inventory choices.
Re Claim 6: Hoover in view of Dalinina discloses the vehicle transaction support system of claim 4. Regarding the limitation feature(s) comprising:
wherein the vehicle scoring engine further includes a scoring model that generates the filtered and scored vehicle source data based on scoring results from the plurality of AI models.
Dalinina makes this teaching in a related endeavor (¶¶[5, 6, 9, 10, 11, 13, 23, 43, 58, 63, 72, 73, 85, 86, 96, 97, 106). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Dalinina with the invention of Hoover as disclosed above for the motivation of providing filter criteria to assist in narrowing available vehicle inventory choices.
Re Claim 7: Hoover in view of Dalinina discloses the vehicle transaction support system of claim 4. Regarding the limitation feature(s) comprising:
wherein the plurality of AI models includes:
a vehicle desirability model trained via machine learning to generate a vehicle desirability score;
a vehicle net present value (NPV) model trained via machine learning to generate a vehicle NPV score;
a vehicle reliability model trained via machine learning to generate a vehicle reliability score; and
a vehicle cost conditioning model trained via machine learning to generate a vehicle cost conditioning score and wherein the vehicle scoring engine further includes a scoring model that generates the filtered and scored vehicle source data based on scoring results from the plurality of AI models.
Dalinina makes this teaching in a related endeavor (¶¶[5, 6, 9, 10, 11, 13, 23, 43, 58, 63, 72, 73, 85, 86, 96, 97, 106). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Dalinina with the invention of Hoover as disclosed above for the motivation of providing filter criteria to assist in narrowing available vehicle inventory choices.
Re Claim 8: Hoover in view of Dalinina discloses the vehicle transaction support system of claim 1. Hoover further discloses:
wherein the vehicle source data indicates a plurality of vehicle attributes that include: a vehicle make, a vehicle model, a vehicle year, a vehicle mileage, and a vehicle cost. (FIG. 5:{520, 530, 540, 550, 560}; C9 L3-20; C13 L1-21)
Re Claim 9: Hoover in view of Dalinina discloses the vehicle transaction support system of claim 8. Hoover further discloses:
wherein the vehicle source data further includes at least one of: accident data; engine type, fuel type, transmission type. (C9 L3-20; C13 L1-21)
Re Claim 10: Hoover in view of Dalinina discloses the vehicle transaction support system of claim 1.
wherein the operations further include generating, based on the filtered and scored vehicle source data, targeted maximum bid data for at least a subset of the plurality of the vehicles indicated by the filtered vehicle source data, and wherein the targeted maximum bid data is displayed via the graphical user interface. (C1 L14-44; C2 L65-67; C3 L1-13; C7 L9-22; C6 L23-35; C9 L3-20; C12 L49-67; C14 L15-20; C22 L26-46)
Re Claim 11: Claim 11, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 1. Accordingly, claim 11 is rejected in the same or substantially the same manner as claim 1.
Re Claim 12: Claim 12, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 2. Accordingly, claim 12 is rejected in the same or substantially the same manner as claim 2.
Re Claim 13: Claim 13, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 3. Accordingly, claim 13 is rejected in the same or substantially the same manner as claim 3.
Re Claim 14: Claim 14, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 4. Accordingly, claim 14 is rejected in the same or substantially the same manner as claim 4.
Re Claim 15: Claim 15, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 5. Accordingly, claim 15 is rejected in the same or substantially the same manner as claim 5.
Re Claim 16: Claim 16, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 6. Accordingly, claim 16 is rejected in the same or substantially the same manner as claim 6.
Re Claim 17: Claim 17, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 7. Accordingly, claim 17 is rejected in the same or substantially the same manner as claim 7.
Re Claim 18: Claim 18, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 8. Accordingly, claim 18 is rejected in the same or substantially the same manner as claim 8.
Re Claim 19: Claim 19, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 9. Accordingly, claim 19 is rejected in the same or substantially the same manner as claim 9.
Re Claim 20: Claim 20, as best understood by the Examiner, encompasses the same or substantially the same scope as claim 10. Accordingly, claim 20 is rejected in the same or substantially the same manner as claim 10.
Conclusion
The prior art(s) made of record and not relied upon is/are considered pertinent to applicant's disclosure.
Smith (US 11,301,922 B2) discloses a system and method for providing comprehensive vehicle information. Systems and methods are provided for determining additional vehicle data for a vehicle based on a vehicle identifier, such as a vehicle identification number (VIN). Based on the
VIN, manufacturer codes, model codes, and other additional manufacturer information can be determined. The manufacturer codes and/or model codes can be used in determining a list of options on the vehicle. This information can be used by a variety of systems in determining more accurate vehicle specifications to yield more accurate vehicle evaluations based at least in part on the list options.
Gupta et al. (US 2023/0186250 A1) discloses a machine learning based vehicle service recommendation system. A device receives current vehicle data that describes a current state of each of a plurality of components of the vehicle. The device accesses historical data describing prior services previously performed on the vehicle and applies the current vehicle data and the historical vehicle data to a trained machine learning model to obtain a set of recommended services, where the model was trained using labeled training data associated with additional vehicles having a threshold
similarity to the vehicle. The machine learning model is trained to output a set of recommended services to be performed for a given vehicle based on inputs of given current vehicle data and given historical vehicle data for the given vehicle. The device outputs for display the set of recommended
services to be performed on the vehicle to a user.
Claims 1-20 are rejected.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Clifford Madamba whose telephone number is 571-270-1239. The examiner can normally be reached on Mon-Thu 7:30-5:00 EST Alternate Fridays.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Calvin Hewitt II, can be reached at 571-272-6709. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CLIFFORD B MADAMBA/Primary Examiner, Art Unit 3692