DETAILED ACTION
This rejection is in response to Amendments filed 09/30/2025.
Claims 17-26 are currently pending.
Claims 1-16 are cancelled.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 09/30/2025 has been entered.
Response to Arguments
Applicant’s arguments, see page 12-14, filed 09/30/2025, with respect to 35 U.S.C. 112(b) rejection and to 35 U.S.C. 103 rejection have been fully considered and are persuasive. The 35 U.S.C. 112(b) rejection and 35 U.S.C. 103 rejection have been withdrawn.
Applicant's arguments filed 09/30/2025 have been fully considered but they are not persuasive.
With respect to applicant’s arguments on pages 9-11 of remarks filed 09/30/2025 that even if the claims are directed to an abstract idea, the claims are directed to a practical application because the claims improve item delivery, reduce error in item delivery, improve customer satisfaction, reduce food waste, and reduce computer resources to coordinate returns as well as using machine learning and robotic mechanism improves the automated system in a way which a human cannot, Examiner respectfully disagrees.
If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. An indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art. See MPEP 2106.05(a).
Improvements to item delivery, reducing item delivery error and food waste, and improving customer satisfaction are directed to commercial problems that are not rooted in technology. None of the claims recite any limitations related to returns so it is not apparent to one of ordinary skill in the art how exactly computer resources are reduced to coordinate returns. The specification does not provide any details on how technology is improved. Merely using a computer than uses machine learning or controls robotic mechanism does not appear to provide any improvements to technology but merely uses the computer as a tool to implement the claim limitations. Therefore, the claims are not directed to a practical application since the claimed invention merely solves and improves commercial problems that are not rooted in technology.
With respect to applicant’s arguments on pages 11-12 of remarks filed 09/30/2025 that the claims are not directed towards a building block of human ingenuity, Examiner respectfully disagrees.
The claims are not directed to a building block of human ingenuity. The abstract idea that the claims are grouped under is “certain methods of organizing human activity” which includes sales activities and commercial interactions, not a building block of human ingenuity. The claims are directed to certain methods of organizing human activity because the claims are directed towards sales activities and commercial interactions such as receiving an order and determining recipes to initiate filing an order based on attributes identified from questions and answers, preferences, and order history.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 17-26 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 17 and 21 recites: a plurality of known questions having known answers relative to feedback on recipes having recipe attributes selected based on the known questions and known answers, with each question and answer being associated with one or more recipe attributes,…, wherein the dynamic-question-selection data structure is a tree data structure with each node being a question and each edge being an answer to that question;… traversing the tree data structure of the dynamic-question-selection data structure for each question and answer, rendering said claim indefinite because it is unclear whether known answers and each question and answer is the same or different than the subsequent recitation of known answers, a question, an answer to that question. Appropriate correction or clarification is required. All dependent claims inherit deficiencies of independent claims.
Claim 21 recites: feedback on recipes having recipe attributes…;… training data that includes at least item attributes and recipe attributes, rendering said claim indefinite because it is unclear whether recipe attributes is the same or different than the subsequent recitation of recipe attributes. Appropriate correction or clarification is required. All dependent claims inherit deficiencies of independent claims.
Claims 18-19 and 22-23 recite: feedback, rendering said claims indefinite because it is unclear whether feedback in independent claims 17 and 21 is the same or different than the subsequent recitation of feedback in claims 18-19 and 22-23. Appropriate correction or clarification is required. All dependent claims inherit deficiencies of independent claims.
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 17-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (an abstract idea) without significantly more.
Under Step 1 of the Subject Matter Eligibility Test, it must be considered whether the claims are directed to one of the four statutory classes of invention. See MPEP § 2106. In the instant case, claims 17-20 and 25-26 are directed to a system and claims 21-24 are directed to a method which falls within one of the four statutory categories of invention(process/apparatus). Accordingly, the claims will be further analyzed under revised step 2:
Under step 2A (prong 1) of the Subject Matter Eligibility Test, it must be considered whether the claims recite a judicial exception if so, then determine in Prong Two if the recited judicial exception is integrated into a practical application of that exception. If the claim recites a judicial exception (i.e., an abstract idea), the claim requires further analysis in Prong Two. One of the enumerated groupings of abstract ideas is defined as certain methods of organizing human activity that includes fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). See MPEP § 2106.04(a)(2).
Regarding representative independent claim 17, the abstract idea includes:
…analyzes a plurality of known questions having known answers relative to feedback on recipes having recipe attributes selected based on the known questions and known answers, with each question and answer being associated with one or more recipe attributes, including merging or reinforcing the known questions based on the feedback, wherein the dynamic-question-selection data structure is a tree data structure with each node being a question and each edge being an answer to that question;
receive,.., a request for an order for a customer;
dynamically present a plurality of questions to the customer, including: select a next question from the dynamic-question-selection data structure based on a previous question presented to the customer and a previous answer received from the customer;
transmit a first message… to present the next question to the customer; and
receive a second message…indicating a next answer to the next question from the customer;
traverse the tree data structure of the dynamic-question-selection data structure for each question and answer to identify a plurality of recipe attributes associated with the plurality of questions presented to the customer, wherein each traversed node in the dynamic-question-selection data structure includes at least one recipe attribute of the plurality of recipe attributes associated with the plurality of questions presented to the customer;
select a group of initial recipes from the plurality of recipes for the customer based on the plurality of recipe attributes;
obtain one or more hard constraints for the customer and the order, wherein the one or more hard constraints define at least one first parameter that cannot be violated by a recipe or a set of recipes to be selected for the customer;
obtain one or more soft constraints for the order, wherein the one or more soft constraints define at least one second parameter that expresses a tradeoff value associated with the recipe or the set of recipes to be selected for the customer;
select a plurality of predicted recipes from the group of initial recipes for the order based on preferences of the customer and an order history of the customer;
generate a plurality of sets of recipes from the plurality of predicted recipes based on the one or more hard constraints, wherein each separate recipe set of the plurality of sets of recipes includes different combinations of multiple recipes;
score each separate recipe set of the plurality of sets of recipes based on the one or more soft constraints,…;
select a set of recipes for the order based on the scores of the plurality of sets of recipes based on the selected set of recipes having a score above a selected threshold, wherein the selected threshold is dynamically set by the customer;
and initiate filling the order for the customer with items associated with the selected set of recipes, including …to select the items associated with the selected set of recipes from one or more shelves in an item warehouse and fill a delivery box with the items.
This arrangement amounts to certain methods of organizing human activity associated with sales activities and commercial interactions involving receiving a customer order, presenting questions to the user to answer, receive answers to the questions, identify recipe attributes associated with the questions, select recipes based on recipe attributes, obtain constraints for the order, select recipes based on customer preferences and order history, generate recipes based on constraints, and score each recipe, and select recipes based on score, and initiate filling the order for customer. Such concepts have been considered ineligible certain methods of organizing human activity by the Courts. See MPEP § 2106.
The Step 2A (prong 2) of the Subject Matter Eligibility Test, is the next step in the eligibility analyses and looks at whether the abstract idea is integrated into a practical application. This requires an additional element or combination of additional elements in the claims to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. See MPEP § 2106.
In this instance, the claims recite the additional elements such as:
A computing system, comprising: a recipe database that stores a plurality of recipes; an item-inventory database that stores inventory information regarding a plurality of items associated with the plurality of recipes; a customer database that stores preferences and order histories for a plurality of customers; and an item-selection server that includes: a memory that stores computer instructions; and a processor that is configured to execute the computer instructions to: generate a dynamic-question-selection data structure by employing one or more machine learning techniques that systematically…; … , from a customer device,…; …to the customer device…;…from the customer device…;… controlling an automated item selection robotic mechanisms (Claim 17);
generating a dynamic-question-selection data structure by employing one or more machine learning techniques that systematically…;… , from a customer device,…; …to the customer device…;…from the customer device…;…wherein the model is trained using one or more artificial intelligence or machine learning techniques on training data that includes at least item attributes and recipe attributes (Claim 21);
the processor of the item-selection server is configured to further execute the computer instructions to: (Claims 18-20 and 25-26).
However, these elements do not amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, 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, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Independent claims and dependent claims also fail to recite elements which amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, 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, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. For example, independent claims and dependent claims are directed to the abstract idea itself and do not amount to an integration according to any one of the considerations above.
Step 2B is the next step in the eligibility analyses and evaluates whether the claims recite additional elements that amount to an inventive concept (i.e., “significantly more”) than the recited judicial exception. According to Office procedure, revised Step 2A overlaps with Step 2B, and thus, many of the considerations need not be re-evaluated in Step 2B because the answer will be the same. See MPEP § 2106.
In Step 2A, several additional elements were identified as additional limitations:
A computing system, comprising: a recipe database that stores a plurality of recipes; an item-inventory database that stores inventory information regarding a plurality of items associated with the plurality of recipes; a customer database that stores preferences and order histories for a plurality of customers; and an item-selection server that includes: a memory that stores computer instructions; and a processor that is configured to execute the computer instructions to: generate a dynamic-question-selection data structure by employing one or more machine learning techniques that systematically…; … , from a customer device,…; …to the customer device…;…from the customer device…;… controlling an automated item selection robotic mechanisms (Claim 17);
generating a dynamic-question-selection data structure by employing one or more machine learning techniques that systematically…;… , from a customer device,…; …to the customer device…;…from the customer device…;…wherein the model is trained using one or more artificial intelligence or machine learning techniques on training data that includes at least item attributes and recipe attributes (Claim 21);
the processor of the item-selection server is configured to further execute the computer instructions to: (Claims 18-20 and 25-26).
These additional limitations, including the limitations in the independent claims and dependent claims, do not amount to an inventive concept because the recitations above do not amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, 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, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. In addition, they were already analyzed under Step 2A and did not amount to a practical application of the abstract idea.
For these reasons, the claims are rejected under 35 U.S.C. 101.
Allowable Subject Matter
Claims 17-20 and 25-26 would be allowable if rewritten to overcome the 35 U.S.C. 101 rejection and 35 U.S.C. 112(b) rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is cited as Pinel et al. (US Pub. No. 20190243922 A1) related to generating alternative recipes based on purchase history, Pulley et al. (US Pub. No. 20180218461 A1) related to evaluating user responses to various potential meal-kit menu designs, and non-patent literature, “Personalized Food Recommendation as Constrained Question Answering over a Large-scale Food Knowledge Graph,” related to recommending food recipes based on user history and knowledge based question answering.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LATASHA DEVI RAMPHAL whose telephone number is (571)272-2644. The examiner can normally be reached 11 AM - 7:30 PM (EST).
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/LATASHA D RAMPHAL/Examiner, Art Unit 3688
/Jeffrey A. Smith/Supervisory Patent Examiner, Art Unit 3688