DETAILED ACTION
This is a Final Office Action in response to Claims on 04/15/2026. Claims 1-15 are pending. The effective filing date is 10/20/2023.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 09/27/2024 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Step 1-Claims 1-5 are directed to a device, which is a statutory category. Claims 6-10 are directed to a method, which is a statutory category. Claims 11-15 are directed to a non-transitory computer-readable recording medium, which is an article of manufacture, which is a statutory category. Claims 1-15 pass step 1.
Step 2A, Prong 1-The independent claim 1, and similarly claims 6 and 11, recite:
A meal suggestion device comprising:
at least one memory configured to store instructions (additional element to be analyzed in Step 2A, Prong 2); and
at least one processor configured to execute the instructions (additional element to be analyzed in Step 2A, Prong 2) to:
acquire target person related data related to a target person to whom a meal is to be suggested (acquiring information about a target person to suggest a meal is a way to use information for a commercial interaction, which can be grouped as a method of organizing human activity under MPEP 2106.04(a)(2)(II)(B) using an algorithm for determining the optimal number of visits by a business representative to a client, In re Maucorps, 609 F.2d 481, 485, 203 USPQ 812, 816 (CCPA 1979); additionally, the acquiring of information can be a mental process of collecting data, see MPEP 2106.04(a)(2)(III)(A) a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016));
detect that the target person related data indicates content of work performed by the target person (detecting the type of work a person is performing can be considered a certain method of organizing human activity, under MPEP 2106.04(a)(2)(II)(C) in that this includes the management of personal behavior and this action is monitoring how a person behaves; additionally, this can be grouped under a mental process, as it is obtaining information by making an observation, which can be achieved in the human mind, se MPEP 2106.04(a)(2)(III));
based on the content of work, determine a suggested meal to be suggested to the target person as a meal having calorie content equal to or exceeding a predetermined threshold using the target person related data (making a determination about a target person to suggest a meal is a way to use information for a commercial interaction, which can be grouped as a method of organizing human activity under MPEP 2106.04(a)(2)(II)(B) using an algorithm for determining the optimal number of visits by a business representative to a client, In re Maucorps, 609 F.2d 481, 485, 203 USPQ 812, 816 (CCPA 1979); additionally, making a determination can be a mental process of analyzing data, see MPEP 2106.04(a)(2)(III)(A) a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016));
generate basis information indicating a basis for suggesting the suggested meal based on the content of work (generating a suggestion about a meal is a way to use information for a commercial interaction, which can be grouped as a method of organizing human activity under MPEP 2106.04(a)(2)(II)(B) using an algorithm for determining the optimal number of visits by a business representative to a client, In re Maucorps, 609 F.2d 481, 485, 203 USPQ 812, 816 (CCPA 1979); additionally, generating a suggestion can be a mental process of analyzing data, see MPEP 2106.04(a)(2)(III)(A) a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016)); and
present the suggested meal and the basis information to the target person (presenting information about the suggested a meal is a way to use information for a commercial interaction, which can be grouped as a method of organizing human activity under MPEP 2106.04(a)(2)(II)(B) using an algorithm for determining the optimal number of visits by a business representative to a client, In re Maucorps, 609 F.2d 481, 485, 203 USPQ 812, 816 (CCPA 1979); additionally, the presentation of information can be a mental process of displaying results, see MPEP 2106.04(a)(2)(III)(A) a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016)).
Step 2A, Prong 2- The additional elements of independent claim 1 are a memory and processor. This judicial exception is not integrated into a practical application because the elements are used as tools to perform the abstract idea. Under MPEP 2106.05(f)(2) when the claim invokes a computer merely as a tool to perform an existing process, it fails to integrate the abstract idea into a practical application. This is showcased by the memory storing instruction, and the instructions being the abstract ideas. The processors are used to execute the instruction, which additionally showcase its use as a tool to use a computer to perform instructions. Similarly claims 6 and 11 do not add additional elements that would integrate the abstract idea into a practical application, as a storage medium holding the instructions remains a tool to perform the abstract idea. Therefore, the claims fail step 2A, prong 2.
Step 2B-The independent claim 1, and similarly claims 6 and 11, do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements describe a processor and memory, which are computers disclosed in generality. See MPEP 2106.05(f)(3) that when a claim has broad applicability across many fields, such as a memory storing information, and a processor executing instruction, they may not provide meaningful limitation that amounts to significantly more.
Dependent Claims
Claims 2-5, 7-10 and 12-15, add additional steps of making a determination and displaying information, both of which can be grouped as a mental process of analyzing and displacing results, under MPEP 2106.04(a)(2)(III). They do not provide additional elements beyond the previously presented memory and processor, and therefore do not integrate the abstract idea into a practical application, or provide significantly more under MPEP 2106.05(f).
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, 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 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over US 2020/0382454 A1 Gershony et al. (hereinafter Gershony) in view of US 2011/0281687 A1 Gilley et al. (hereinafter Gilley).
Regarding claim 1, 6 and 11, Gershony teaches a meal suggestion device (Gershony Abstract, suggestions based on input; [0005] the response may be to make a restaurant reservation or food order) comprising:
at least one memory configured to store instructions (Gershony [0020] processors and memory for storing and implementing instructions); and
at least one processor configured to execute the instructions (Gershony [0020] processors and memory for storing and implementing instructions) to:
acquire target person related data related to a target person to whom a meal is to be suggested (Gershony [0064] user can consent to profile information that can be used to aid in suggestions);
detect that the target person related data indicates content of work performed by the target person (Gershony Figs. 3, 4A, 4B and 4G, showcases that the application can analyze the messages to determine its contents, whether that is if the user wants to obtain lunch, is tired and wants to relax, or if they want to go get a specific type of cuisine);
based on the content of work, determine a suggested meal to be suggested to the target person using the target person related data (Gershony [0084] using a variety of factors to determine the suggestion, including type of food, time of food, etc.);
generate basis information indicating a basis for suggesting the suggested meal based on the content of work (Gershony [0087] learning from responses about the determination to generate a final suggestion); and
present the suggested meal and the basis information to the target person (Gershony [0100] the determined suggestion is sent to a display for a user; Fig. 3).
Gershony fails to explicitly disclose the content of work performed by the target person;
based on the content of work, determine a suggested meal as a meal having calorie content equal to or exceeding a predetermined threshold.
Gilley is in the field of lifestyle companions (Gilley Abstract, lifestyle companion to suggest activities and food) and teaches the content of work performed by the target person (Gilley [0075] sensor data obtained from a user device and calculated and determines the calories burned during a specific physical activity);
based on the content of work, determine a suggested meal as a meal having calorie content equal to or exceeding a predetermined threshold (Gilley [0186-0187] based on the user profile, such as a desire to lose weight, the system may suggest a specific restaurant that would match their nutritional needs (calories) when compared to the calories burned from the content of the work being performed by the user). 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 analysis of messaging to suggest a restaurant in Gershony with the use of target person collected data to make meal suggestion as taught n Gilley. The motivation for doing so would be to not solely rely on text analysis, but use feedback from the actual targets body to make better suggestions based on the users specific goals (Gilley [0010-0011] combining multiple areas of a persons life, who they speak with and the physical activities performed, to create an optimized food plan).
Regarding claim 2, 7 and 12, Gershony teaches the meal suggestion device according to claim 1, wherein the at least one processor is further configured to execute the instructions to: determine incentive information indicating an incentive for the target person to select the suggested meal (Gershony [0088] the system may provide a coupon as an incentive to go to a specific restaurant).
Regarding claim 3, 8 and 13, Gershony teaches the meal suggestion device according to claim 1, wherein the at least one processor is further configured to execute the instructions to: determine a meal provided at a place within a predetermined range from position information of the target person as the suggested meal (Gershony [0078] the location of the user may be used to determine the suggestion; Fig. 4A); and
present a map indicating position information of the target person and a place where the suggested meal is provided (Gershony [0100] the graphic representation may be a location of the suggested restaurant, Fig. 4A).
Regarding claim 4, 9 and 14, Gershony teaches the meal suggestion device according to claim 3, wherein the at least one processor is further configured to execute the instructions to:
optimize a route from a location of the target person to the place where the suggested meal is provided using a constraint condition including at least part of the meal and the target person related data (Gershony [0063] requesting driving directions to the specific location; [0098] the application may provide the user with directions to the suggested restaurant location); and
display the route on the map (Gershony [0063] requesting driving directions to the specific location; [0098] the application may provide the user with directions to the suggested restaurant location; Fig. 4A).
Regarding claim 5, 10 and 15 Gershony teaches the meal suggestion device according to claim 1, wherein the at least one processor is further configured to execute the instructions to: determine the suggested meal by inputting the target person related data to a model that machine learned a relationship between the target person related data and a meal related to the target person related data (Gershony [0010] the suggestion may be based on machine learning model, and can be trained using user information and history of suggestions).
Response to Arguments
Applicant's arguments filed 04/15/2026 have been fully considered but they are not persuasive.
Regarding 101, Applicant states that the specific criteria of a predetermined calorie threshold that is determined based on the type of work performed by the user to generate the output of a suggested meal showcases more than a high-level acquisition, determination and display of information. However, Examiner looks at the claim limitations, and see that the way the calorie threshold is applied (using it as the calculation) using the data collected about the work performed (data collection) and that there is a suggested meal output (displayed to the user). The specific nature of what is being calculated, like a meal suggestion based on calories, does not change the actions being performed, and those actions are using known data points to make a decision about a meal, which has been grouped in both a method of organizing human behavior, as it is making decision about meals for a person, and a mental process, because it is applying the mental decision making of what meal to eat onto a processor to apply an algorithm. The claims do not add additional elements that would amount to more than a tool to perform the abstract idea, and the functioning of the steps does not improve the functioning of a computer. Therefore, the claims remain rejected under 101.
Regarding Example 47 of the USPO published examples, Claim 3 goes into specific details about how the detection, processing, generation and presentation is more than high level mental processes. As shown in the explanation for Claim 3, under Step 2A, Prong 2, it is to look at the claim as a whole to determine id there is an improvement to a computer, and if there is a technical explanation of the asserted improvement found within the specification. Here, the instant application is directed to meal suggestion, and this meal suggestion is accomplished using tools to obtain data, and process data, which showcases using a tool to perform the idea of meal suggestions. This is distinct from the Example 47 which is directed to techniques for detecting potentially malicious network packets. Therefore, the way in which the network operates is different from previous systems, and shows an improvement to the functioning of a computer, and this is why the example was found eligible.
The additional elements of the claims include memories and processors, which are used to perform the tasks normally assigned to them, such as storing information, or processing information. The step of acquiring data is not an additional element, but rather is the abstract element being analyzed in combination with the additional elements.
Regarding 102, the amended claim language specifies the “related data indicates content of wok performed”, which on its face can be broad, is the work being performed by the person a search for nearby restaurants as shown in Gershony Fig. 4A. The specifications of the instant application showcase that “content of work” is more in line with the physical labor performed by the user, and therefore, the 102 rejection has been removed.
A new 103 rejection has been presented to showcase that the content of work performed by the user may include physical labor performed, and that the physical labor calories burned may influence the meal suggestions, as shown in Gilley, see the above new rejection.
Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 2021/0216920 A1 Mimassi teaches personalized advertisements (Abstract); US 2021/0097882 A1 Lyke et al. teaches machine learning meal prep suggestions; US 2020/0098466 A1 Murdoch et al. teaches machine learning model to create a menu (Abstract).
Conclusion
THIS ACTION IS MADE FINAL. 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.
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/JESSICA E SULLIVAN/Examiner, Art Unit 3627
/FAHD A OBEID/Supervisory Patent Examiner, Art Unit 3627
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