Prosecution Insights
Last updated: October 02, 2026
Application No. 19/186,737

Demand Transference Machine Learning Model

Final Rejection §101§102
Filed
Apr 23, 2025
Priority
Apr 24, 2024 — provisional 63/637,963
Examiner
GUNN, JEREMY L
Art Unit
Tech Center
Assignee
ORACLE INTERNATIONAL Corporation
OA Round
2 (Final)
30%
Grant Probability
At Risk
3-4
OA Rounds
1y 8m
Est. Remaining
76%
With Interview

Examiner Intelligence

Grants only 30% of cases
30%
Career Allowance Rate
49 granted / 164 resolved
-30.1% vs TC avg
Strong +46% interview lift
Without
With
+45.8%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
27 currently pending
Career history
204
Total Applications
across all art units

Statute-Specific Performance

§101
42.1%
+2.1% vs TC avg
§103
36.3%
-3.7% vs TC avg
§102
13.1%
-26.9% vs TC avg
§112
7.3%
-32.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 164 resolved cases

Office Action

§101 §102
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 . Claims 1-20 have been reviewed and are under consideration by this office action. Notice to Applicant The following is a Final Office action. Applicant, on 07/31/2026, amended claims. Claims 1-20 are pending in this application and have been rejected below. Response to Amendment Applicant’s amendments are received and acknowledged. The amended claims overcome the 103 rejections as well as the Applicant’s arguments are found persuasive specifically pages 5-6. The 103 Rejections are withdrawn. Response to Arguments - 35 USC § 101 Applicant’s arguments with respect to the 35 USC 101 rejections have been fully considered, but they are not persuasive. Applicant contends that the claims provide a technical solution that cannot be performed manually such as Scan*Pro and log linear models and further assert embodiments can provide a mathematical guarantee…. Examiner respectfully disagrees. The concept of a log-linear model is a concept capable of being performed in the human mind (i.e. via pen and paper) and as such is part of the abstract idea. The use of a Scan*Pro model is addressed as an additional element although the model is not inherently an artificial intelligence model. The additional elements are performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h). Applicant contends with respect to Desjardins, that the claims require materially different models and reflect an improvement in the accuracy of the system for determining demand. Examiner respectfully disagrees. The claims do not follow the fact pattern of Desjardins as Dejardins is directed towards training a machine learning model on a series of tasks with the credited benefits of reduced storage, reduced system complexity, and preservation of performance attributes associated with earlier tasks during subsequent computational task (i.e. catastrophic forgetting). The alleged improvement merely improves upon the efficiency and accuracy of the analysis which is an improvement upon the abstract idea itself and not the technology or technological field as a whole. Applicant contends that the claims recite a unique arrangement of models which constrains the predictions for automated ordering. Examiner respectfully disagrees. The additional elements are analysed both individually as well as in combination and determined to be performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h). The 101 Rejection is updated and maintained below. 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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Step One - First, pursuant to step 1 in the January 2019 Guidance on 84 Fed. Reg. 53, the claim(s) is/are directed to statutory categories. Step 2A, Prong One – The claims are found to recite limitations that set forth the abstract idea(s), namely in independent claims recite a series of steps for the abstract idea recited below. Regarding independent claims, (additional elements bolded) Regarding Claims 1 and 10, A method of determining demand transference for an item assortment of a retailer, the method comprising:/ A non-transitory computer readable medium having instructions stored thereon that, when executed by one or more processors, cause the processors to determine demand transference for an item assortment of a retailer, the determining demand transference comprising: receiving historical sales data for a category of items corresponding to the retailer; receiving hierarchy data for the category of items corresponding to the retailer, wherein the hierarchy data comprises a merchandise hierarchy corresponding to the retailer and a location hierarchy corresponding to the retailer; based on the historical sales data and the hierarchy data, estimating first variables of a multinomial logit (MNL) model (recited a high level of generality), wherein the MNL model determines a category level total demand of the item assortment based on a combined utility; and based on the historical sales data and the hierarchy data, estimating second variables of a log linear retail sales model, wherein the log-linear retail sales model determines item shares at a stock-keeping-unit-store level; and generating item-level sales forecasts by multiplying the category level total demand by the respective item shares. Regarding Claim 19, A sales forecast system for determining demand transference for an item assortment of a retailer, the system comprising: a first database storing historical sales data for a category of items corresponding to the retailer; a second database storing hierarchy data for the category of items corresponding to the retailer wherein the hierarchy data comprises a merchandise hierarchy corresponding to the retailer and a location hierarchy corresponding to the retailer; a multinomial logit (MNL) model; a log linear retail sales model; one or more processors configured to: based on the historical sales data and the hierarchy data, estimate first variables of the multinomial logit (MNL) model, wherein the MNL model determines a category level total demand of the item assortment based on a combined utility; and based on the historical sales data and the hierarchy data, estimate second variables of the log linear retail sales model, wherein the log linear retail sales model determines item shares at a stock-keeping-unit-store level; and generate item-level sales forecasts by multiplying the category level total demand by the respective item shares. As drafted, this is, under its broadest reasonable interpretation, within the Abstract idea groupings of “Mental processes—concepts performed in the human mind” (observation, evaluation, judgment, opinion) as the claims are directed towards receiving historic sales data, receiving hierarchy data, and estimating variables all of which are concepts capable of being performed in the human mind (i.e. via pen and paper). Further the claims are directed towards the abstract idea grouping of “Certain methods of organizing human activity” — commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations) and/or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as the claims are directed towards determining a demand transference of an item assortment (See Specification, [09]). Step 2A, Prong Two - This judicial exception is not integrated into a practical application. The independent claims utilize at least the additional elements bolded above The additional elements are performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h). Step 2B - The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are just “apply it” on a computer. (See MPEP 2106.05(f) – Mere Instructions to Apply an Exception – “Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” Alice Corp., 134 S. Ct. at 235) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h). Regarding Claims 2-3, 6-8, 11-12, and 15-18, the claim further narrows the abstract idea or recite additional elements previously addressed in the independent claims. Regarding Claims 4-5 and 13-14, the claim further recite the additional element(s) of a Scan*Pro model. This elements is performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) in Steps 2A-Prong 2 and 2B. Regarding Claims 9 and 20, the claim further recite the additional element(s) of an automated inventory management application. This elements is performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) in Steps 2A-Prong 2 and 2B. Accordingly, the claim fails to recite any improvements to another technology or technical field, improvements to the functioning of the computer itself, use of a particular machine, effecting a transformation or reduction of a particular article to a different state or thing, adding unconventional steps that confine the claim to a particular useful application, and/or meaningful limitations beyond generally linking the use of an abstract idea to a particular environment. See 84 Fed. Reg. 55. Viewed individually or as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Examining Claims with Respect to Prior Art Claims 1-20, though directed to non-statutory subject matter, are deemed to define over the currently known prior art under 35 USC 102 and 103. Examiner interprets based upon the claim limitations that there is no currently known prior art that discloses the features relating to: “determining demand transference for an item assortment of a retailer, the method comprising: receiving historical sales data for a category of items corresponding to the retailer; receiving hierarchy data for the category of items corresponding to the retailer, wherein the hierarchy data comprises a merchandise hierarchy corresponding to the retailer and a location hierarchy corresponding to the retailer; based on the historical sales data and the hierarchy data, estimating first variables of a multinomial logit (MNL) model, wherein the MNL model determines a category level total demand of the item assortment based on a combined utility; and based on the historical sales data and the hierarchy data, estimating second variables of a log linear retail sales model, wherein the log linear retail sales model determines item shares at a stock-keeping-unit-store level; and generating item-level sales forecasts by multiplying the category level total demand by the respective item shares.” The reason to withdraw the 35 USC 103 rejection of claims 1-20 in the instant application is because the prior art of record fails to teach the overall combination as claimed. Therefore, it would not have been obvious to one of ordinary skill in the art to modify the prior art to meet the combination above without unequivocal hindsight and one of ordinary skill would have no reason to do so. Upon further searching the examiner could not identify any prior art to teach these limitations. The prior art on record, alone or in combination, neither anticipates, reasonably teaches, not renders obvious the Applicant’s claimed invention. Known Prior Art (patent) US 20120130726 A1 PRODUCT PRICING OPTIMIZATION SYSTEM US 20160155137 A1 DEMAND FORECASTING IN THE PRESENCE OF UNOBSERVED LOST-SALES US 20090177520 A1 TECHNIQUES FOR CASUAL DEMAND FORECASTING US 20190325463 A1 SYSTEMS AND METHODS FOR PRODUCT-LINE PRICING UNDER DISCRETE MIXED MULTINOMIAL LOGIT DEMAND US 20120254092 A1 MANAGING OPERATIONS OF A SYSTEM US 20090063251 A1 System And Method For Simultaneous Price Optimization And Asset Allocation To Maximize Manufacturing Profits US 20170178180 A1 PRODUCT SUGGESTION FOR PUBLISHER US 20220138783 A1 Discrete Choice Hotel Room Demand Model US 20150332298 A1 PRICE MATCHING IN OMNI-CHANNEL RETAILING Known Prior Art (NPL) S. -h. Yu, Y. -j. Li and X. -b. Yan, "A Spatial Neural Network Application in Consumer Spatial Behavior Modeling," 2006 International Conference on Machine Learning and Cybernetics, Dalian, China, 2006, pp. 3044-3047, doi: 10.1109/ICMLC.2006.258363. Known Prior Art (foreign) JP2024514309A Inventory allocation and pricing optimization system 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 JEREMY L GUNN whose telephone number is (571)270-1728. The examiner can normally be reached Monday - Friday 6:30-4:30. 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. /JEREMY L GUNN/ Primary Examiner, Art Unit 3624
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Prosecution Timeline

Apr 23, 2025
Application Filed
Jun 08, 2026
Non-Final Rejection mailed — §101, §102
Jul 14, 2026
Interview Requested
Jul 30, 2026
Applicant Interview (Telephonic)
Jul 30, 2026
Examiner Interview Summary
Jul 31, 2026
Response Filed
Sep 21, 2026
Final Rejection mailed — §101, §102 (current)

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Prosecution Projections

3-4
Expected OA Rounds
30%
Grant Probability
76%
With Interview (+45.8%)
3y 1m (~1y 8m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 164 resolved cases by this examiner. Grant probability derived from career allowance rate.

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