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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Acknowledgement is made of applicant’s claim for foreign priority to 23 August 2021 under 35 U.S.C. 119(a)-(d).
Status of Claims
Claims 1-28 received on 23 February 2024 are currently pending and being considered by Examiner in this Office Action.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 23 February 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the IDS is being considered by the Examiner in this Office Action.
Drawings
The drawings are objected to because Figs. 4A-4B, 6A-6B, 8A-8B, 11, 12, 13, 14, 15, & 18 are illegible. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claims 1-28 are objected to because of the following informalities
Regarding claims 1, 26, & 28, the claims have multiple subordinate limitations that begin with a capital letter and have indentations such as “a.” or “b.”, see MPEP 608.01(m) which discusses the form of claims, i.e. "each claim begins with a capital letter and ends with a period.” and “periods may not be used elsewhere in the claims except for abbreviations”;
Regarding claims 2-25 & 27, these claims are dependent from independent claims 1 & 26 and inherit the deficiencies thereof by virtue of dependency;
Further regarding claim 20, a period is found between “dietary items” and “a restaurant” in the phrase “…nutritional value of one or more dietary items. or a restaurant” and should be replaced with a comma instead.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
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.
Claims 3-7, 10-11, 12, 15, 17-19, & 27 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention:
Regarding Claim 3, the claim recites “…the information about the kind, quantity, and quality of the ingredients in the dietary item including the information about the molecular ingredients, micronutrients, phytonutrients, macronutrients, chemicals, additives, antioxidants, and spices used in the dietary item”, however neither of these “information’s regarding kind, quantity, and quality or molecular ingredients, micronutrients, phytonutrients, macronutrients, chemicals, additives, antioxidants, and spices used in the dietary item have not been established previously in the claim or in a claim that claim 3 depends from, and therefore lacks antecedent basis. As such, claim 3 will be interpreted to recite “…information about the kind, quantity, and quality of the ingredients in the dietary item including information about the molecular ingredients, micronutrients, phytonutrients, macronutrients, chemicals, additives, antioxidants, and spices used in the dietary item”;
Regarding Claims 4 & 5, the claims recite “… comprises the intensity scores associated with the visual tags…” and “…the said intensity scores are…”, respectively, however, no “intensity scores” have been previously established in the claims or in claims that claims 4 & 5 depend from. As such, claim 4 will be interpreted to recite “… comprises intensity scores associated with the visual tags” and claim 5 will remain the same because the new interpretation of claim 4, which claim 5 depends from, effectively establishes an intensity score;
Regarding Claim 6, the claim recites “the recipe for preparation of the dietary item including the information about cooking, roasting, processing, chopping, mixing, grinding, serving, etc. of all the ingredients” however, no “recipe for preparation” or “information about cooking, roasting, processing, chopping, mixing, grinding, serving, etc.” have been previously established in the claim or in claims that claim 6 depends from. As such, claim 6 will be interpreted to recite “… a recipe for preparation of the dietary item including information about cooking, roasting, processing, chopping, mixing, grinding, serving, etc. of all the ingredients”;
Regarding Claim 7, the claim recites “…the mouthfeel experience of the prepared dietary item after the requisite cooking, roasting, processing, chopping, mixing, grinding, etc. of the ingredients as per a recipe” however, no “mouthfeel experience” or “requisite cooking, roasting, processing, chopping, mixing, grinding, etc.” has been previously established in the claim or in claims that claim 7 depends from. As such, claim 7 will be interpreted to recite “…a mouthfeel experience of the prepared dietary items after a requisite cooking, roasting, processing, chopping, mixing, grinding, etc. of the ingredients as per a recipe”;
Regarding Claim 10, the claim recites “…the techniques of self-learning and artificial intelligence” however, no “techniques of self-learning and artificial intelligence” have been previously established in the claim or in claims that claim 10 depends from. As such, claim 10 will be interpreted to recite “…techniques of self-learning and artificial intelligence”;
Regarding Claim 11, this claim is dependent from claim 10 and inherits the deficiencies thereof by virtue of dependency;
Regarding Claim 12, the claim recites “…the external factors” however, no “external factors” have been previously established in the claim or in claims that claim 12 depends from. As such, claim 12 will be interpreted to recite “…external factors”;
Regarding Claim 15, the claim recites “…the dietary items outside the comfort range” however, no “dietary items outside the comfort range” have been previously established in the claim or in claims that claim 15 depends from. As such, claim 15 will be interpreted to recite “…dietary items outside the comfort range”;
Regarding Claim 17, the claim recites “…the techniques of self-learning and artificial intelligence” however, no “techniques of self-learning and artificial intelligence” have been previously established in the claim or in claims that claim 17 depends from. As such, claim 17 will be interpreted to recite “…techniques of self-learning and artificial intelligence”;
Regarding Claim 18, this claim is dependent from claim 17 and inherits the deficiencies thereof by virtue of dependency;
Regarding Claim 19, the claim recites “…the techniques of self-learning and artificial intelligence” however, no “techniques of self-learning and artificial intelligence” have been previously established in the claim or in claims that claim 19 depends from. As such, claim 19 will be interpreted to recite “…techniques of self-learning and artificial intelligence”;
Regarding Claim 27, the claim recites “…the techniques of self-learning and artificial intelligence” however, no “techniques of self-learning and artificial intelligence” have been previously established in the claim or in claims that claim 27 depends from. As such, claim 27 will be interpreted to recite “…techniques of self-learning and artificial intelligence”.
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 1-28 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.
The claims recite subject matter within a statutory category as a process (claims 1-25), machine (claims 26-28) (Subject Matter Eligibility (SME) Test Step 1: Yes) which recite steps of:
compiling a database of plurality of dietary items;
constructing a profile for each of the dietary item in the database, wherein the profile of each of the dietary item comprises:
an ingredient profile of the dietary item
a sensory profile of the dietary item, wherein the sensory profile comprises:
a visual profile comprising visual tags depicting visual attributes of the dietary item;
a taste profile comprising taste tags depicting taste attributes of the dietary item;
an aroma profile taste profile comprising taste tags depicting taste attributes of the dietary item ;
a texture profile comprising texture tags depicting texture attributes of the dietary item;
a geographical profile of the dietary item, identifying at least one geographical territory associated with the dietary item;
acquiring information and preferences from the user to construct user profile wherein the user profile comprises at least one preferred ingredient or one preferred dietary item or one preferred geographical location;
mapping the user profile against the profile of a plurality of dietary items in the database;
constructing a confidence score for each of the mapped dietary items;
creating a set of dietary items having confidence score within a range, wherein the said range is calibrated with the user’s profile;
generating recommendation information for the user, wherein the recommendation information comprises at least one dietary item selected from the set of dietary items having the confidence score within the range; and
presenting the recommendation information to the user.
These steps of compiling a database of dietary items, constructing a profile for each dietary item in the database, acquiring information and preferences from a user to construct a user profile, mapping the user profile to a generated dietary item profile, constructing a confidence score for the mappings, creating a list of items having a confidence score within a range, generating recommendation information for the user including the list of items, and presenting the recommended information, as drafted, under the broadest reasonable interpretation, includes performance of the limitation in the mind but for recitation of generic computer components. That is, other than reciting steps as performed by the generic computer components, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the compiling a database of constructed profiles for one or more dietary items language, compiling a database of one or more dietary item profiles in the context of this claim encompasses a mental process of a user having knowledge of one or more foods, ingredients, and/or recipes with associated characteristics. Similarly, the limitation of acquiring information and preferences from a user to construct a user profile and mapping certain dietary items to the user based on said information and/or preferences and a calculated confidence score that the user will like or enjoy said dietary items, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, such as a user or physician, such as a dietitian, recommending certain dietary items for said user or a patient based on preferences/constraints of the user/patient, and calculating the confidence of said recommendations for the patient based on one or more applied formulae. For example, but for the generating recommendation information for the user and presenting said recommendation information to the user language, generating and presenting recommendation information in the context of this claim encompasses a mental process of a user or doctor, such as a dietitian, generating varying recommendations based on the certain dietary items that were shown to be compatible for a user/patient given certain preferences/restraints, and displaying the results either in an interface or a report to be given to the user/patient. Therefore, the processes described in the claims heavily relate to mental processes that, for instance, a dietitian performs for a patient regarding optimizing said patient’s food intake and/or dietary items based on preferences and/or restraints of the user, but recited for automation by generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
These steps of compiling a database of dietary items, constructing a profile for each dietary item in the database, acquiring information and preferences from a user to construct a user profile, mapping the user profile to a generated dietary item profile, constructing a confidence score for the mappings, creating a list of items having a confidence score within a range, generating recommendation information for the user including the list of items, and presenting the recommended information, as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity. MPEP 2106.04(a)(2)(II) sets forth various methods of organizing human activity, including concepts relating to 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, and business relations); and managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions). That is, the typical behavior or interaction of a person regarding decisions of consuming one or more dietary items, i.e. foods, is effectively being managed by the performance of the system. The system effectively receives user preferences and/or behaviors, and subsequently updates one or more lists of foods that are compatible to a user based on analysis performed on said data.
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 2-25 & 27, reciting particular aspects of how determining certain food characteristics, determining certain matching dietary items for a user, and/or recommending/presenting recommended dietary items may be performed in the mind but for recitation of generic computer components) (SME Test Step 2A, Prong 1: Yes).
This judicial exception is not integrated into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception (such as recitation of a computer, one or more computer-readable memory/storage devices, one or more input-output devices with graphic user interfaces, one or more data processing apparatuses, one or more devices, a graphical user interface, amounts to invoking computers as a tool to perform the abstract idea, see Applicant’s Specification p. 14, ll. 3-5 for a computer; p. 12, ll. 16 – p. 13, ll. 5 for one or more computer-readable memory/storage devices; p. 5, ll. 19 – p. 6, ll. 3 for one or more input-output devices with graphic user interfaces; p. 5, ll. 20 – p. 6, ll. 3 for one or more data processing apparatus; p. 13, ll. 6-14 for one or more hardware devices; p. 5, ll. 19 – p. 6, ll. 3 for a graphical user interface, see MPEP 2106.05(f));
add insignificant extra-solution activity to the abstract idea (such as recitation of compiling a database of plurality of dietary items, receiving profile information of a dietary item including a ingredient profile, a sensory profile comprising a visual profile, a taste profile, an aroma profile, a texture profile, and a geographical profile, acquiring information and preferences from a user to construct a user profile comprising preferred ingredients and dietary items or geographical locations amounts to mere data gathering, recitation of constructing one or more profiles for dietary items, one or more users, etc., based on received data, mapping the user profile against the dietary item profiles amounts to selecting a particular data source or type of data to be manipulated, recitation of storing the database one or more computer-readable memory devices, calculating a confidence score for each of the mapped dietary items, generating recommendation information comprising selected/appropriate dietary items based on the confidence score amounts to insignificant application, see MPEP 2106.05(g); presenting the recommendation information to the user through the input-output device with a graphic user interface amounts to gathering and analyzing information using conventional techniques and displaying the result, see MPEP 2106.05(a));
generally link the abstract idea to a particular technological environment or field of use (such as generally reciting the algorithms being applied to dietary items and nutritional recommendations, see MPEP 2106.05(h)).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2-25 & 27, which recite limitations relating to an automated computer-implemented device, self-learning, artificial intelligence, an application interface, a mobile/handheld device, one or more computer-readable memory devices, and a processing apparatus, additional limitations which amount to invoking computers as a tool to perform the abstract idea, see Applicant’s Specification p. 12, ll. 14 – p. 13, ll. 5 for a computer-implemented device; p. 29, ll. 7-10 for self-learning; p. 29, ll. 7-10 for artificial intelligence; p. 29, ll. 9-13 for an application interface; p. 14, ll. 3-5 for a mobile/handheld device; p. 12, ll. 16 – p. 13, ll. 5 for one or more computer-readable memory devices; p. 5, ll. 20 – p. 6, ll. 3 for a processing apparatus, see MPEP 2106.05(f); claims 2-9, 11-16, 18, 20-21, & 23, which recite limitations relating to varying data being received and/or extracted, receiving varying profiles, receiving various tags, receiving various scores, receiving varying information associated with the dietary item such as preparation methods, location, etc., receiving varying information associated with the user including location etc., fetching information for profiles on a real-time basis such as via web through an internet protocol, receiving inputs/modifications to varying parameters from a user, additional limitations which add insignificant extra-solution activity to the abstract idea which amounts to mere data gathering; claims 2-9, 11-16, 18, 20-21, & 23, which recite limitations relating to receiving, analyzing, and/or maintaining received data in a database/profile, etc., additional limitations which add insignificant extra-solution activity to the abstract idea by selecting a particular data source or type of data to be manipulated; claims 4, 5, 7, 10, 15, 17, 19, 25 & 27, which recite limitations relating to applying one or more machine learning and/or artificial intelligence algorithms for performance of the analyses recited, calculating one or more scores for various aspects of the data, patient, dietary items, etc., additional limitations which amount to insignificant application; claims 2-25 & 27, generally reciting the algorithms being applied to dietary items and nutritional recommendations additional limitations which generally link the abstract idea to a particular technological environment or field of use; claims 10, 16-18, 22, 25 which recite limitations relating to displaying or outputting information additional limitations which amount to gathering and analyzing information using conventional techniques and displaying the result). 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 and do not impose a meaningful limit to integrate the abstract idea into a practical application (SME Test Step 2A, Prong 2: No).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and generally link the abstract idea to a particular technological environment or field of use. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields (such as compiling a database of plurality of dietary items, receiving profile information of a dietary item including a ingredient profile, a sensory profile comprising a visual profile, a taste profile, an aroma profile, a texture profile, and a geographical profile, acquiring information and preferences from a user to construct a user profile comprising preferred ingredients and dietary items or geographical locations, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); mapping the user profile against the dietary item profiles, calculating a confidence score for each of the mapped dietary items, creating a set of dietary items within a confidence range, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); compiling a database of plurality of dietary items, maintaining one or more dietary item and/or user profiles and updating said profiles over time, e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii); compiling a database of plurality of dietary items, storing the database one or more computer-readable memory devices, recitation of storing computerized instructions, algorithms, etc., in a computerized memory for performance of the steps recited, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv); acquiring information and preferences from a user to construct a user profile comprising preferred ingredients and dietary items or geographical locations, which under BRI includes extraction from one or more documents, e.g., electronic scanning or extracting data from a physical document, Content Extraction, MPEP 2106.05(d)(II)(v); acquiring information and preferences from a user to construct a user profile comprising preferred ingredients and dietary items or geographical locations, such as at a graphical user interface, which under BRI includes generalized input from a user interface by a user, e.g., a web browser’s back and forward button functionality, Internet Patent Corp., MPEP 2106.05(d)(II)(ii)).
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea. Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2-25 & 27, additional limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, claims 2-9, 11-16, 18, 20-21, & 23, which recite limitations relating to varying data being received and/or extracted, receiving varying profiles, receiving various tags, receiving various scores, receiving varying information associated with the dietary item such as preparation methods, location, etc., receiving varying information associated with the user including location etc., fetching information for profiles on a real-time basis such as via web through an internet protocol, receiving inputs/modifications to varying parameters from a user, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); claims 4, 5, 7, 10, 15, 17, 19, 25 & 27, which recite limitations relating to applying one or more machine learning and/or artificial intelligence algorithms for performance of the analyses recited, calculating one or more scores for various aspects of the data, patient, dietary items, etc., e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); claims 2-9, 11-16, 18, 20-21, & 23, which recite limitations relating to varying data being received and/or extracted, receiving varying profiles, receiving various tags, receiving various scores, receiving varying information associated with the dietary item such as preparation methods, location, etc., receiving varying information associated with the user including location etc., and maintaining said received data over periods of time, such as in one or more databases or records, e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii); claims 2-25 & 27, which recite limitations relating to storage of said received data, and/or storing computerized instructions, algorithms, etc., in a computerized memory for performance of the steps recited, storing one or more self-learning and/or artificial intelligence frameworks, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv); claims 2-9, 11-16, 18, 20-21, & 23, which recite limitations relating to receiving varying data which includes extraction from one or more documents, under BRI, e.g., electronic scanning or extracting data from a physical document, Content Extraction, MPEP 2106.05(d)(II)(v); claims 16, 18, 22, which recite limitations relating to one or more interfaces for receiving user information, preferences, etc. therein, e.g., a web browser’s back and forward button functionality, Internet Patent Corp., MPEP 2106.05(d)(II)(ii)). 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 (SME Test Step 2B: No).
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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 1-28 are rejected under 35 U.S.C. 103 as being unpatentable over Wolfe et al. (U.S. Patent Publication No. 2016/0267694), hereinafter “Wolfe”, in view of Hadad et al. (U.S. Patent Publication No. 2019/0295440), hereinafter “Hadad”.
Claim 1 –
Regarding Claim 1, Wolfe discloses a computer-implemented method for generating custom dietary recommendation information for a user, the method comprising:
compiling a database of plurality of dietary items (See Wolfe Par [0236] which discloses one or more ingredient information of a food element in question being obtained, such that it may be obtained from a database containing the recipe/linked to the recipe, such that a flavor platform may have access to ingredient lists for products and recipes through a third-party service or through a local database included in the flavor platform);
constructing a profile for each of the dietary item in the database (See Wolfe Par [0060] & [0121] which discloses including ingredient information for the food element and correlation information regarding the ingredient information; See Wolfe Par [0266] which discloses various characteristics of each of the food elements to be included in considering a match for a user, such that this is understood to constitute a “profile”), wherein the profile of each of the dietary item comprises:
an ingredient profile of the dietary (See Wolfe Par [0060] & [0121] which disclose including ingredient information for the food element and correlation information regarding the ingredient information; See Wolfe Par [0173] which discloses food categories and flavor marks being subdivided into groups such as based on ingredients);
a sensory profile of the dietary item (See Wolfe Par [0316]-[0318], Fig. 25 which discloses sensory data being included in the food flavor mark database, thereby constituting a sensory profile), wherein the sensory profile comprises:
a visual profile comprising visual tags depicting visual attributes of the dietary item (See Par [0316] and Fig. 25, el. 701 which discloses a content database containing food product information and images of associated food product);
a taste profile comprising taste tags depicting taste attributes of the dietary item (See Wolfe Par [0067] which discloses the profile information of each of the food elements includes flavor profile information; See Par [0227] and Table 1 which disclose an exemplary list of flavor categories, i.e. tags, such as those also listed in Figs. 3A-3B);
an aroma profile taste profile comprising taste tags depicting taste attributes of the dietary item (See Wolfe Par [0101], [0116], & [0173] and Table 1 which discloses the preferred food experiences including different smells, i.e. aromas associated with tastes of the food and categories, i.e. tags, associated therewith, i.e. in Table 1, the categories “Nutty” describing the unique flavor and “aroma” associated with all types of nuts or “Yeasty” which describes the taste and/or aroma that fill the air when fresh bread is barked or the aroma of a full-bodied beer, typifying yeasty flavors);
a texture profile comprising texture tags depicting texture attributes of the dietary item (See Wolfe Par [0068] which discloses the profile information of each of the food elements including texture profile information; See Wolfe Par [0336]-[0339] & Table 3 which discloses various texture categories, i.e. tag, representing a food element’s physical interaction with the user when consumed by the user);
a geographical profile of the dietary item, identifying at least one geographical territory associated with the dietary item (See Wolfe Par [0263] which discloses generally considering location or date or other constraints for certain foods, such as when the location is “the south”, regional foods of this area are given higher weight in the search for “foods that take less than thirty minutes”; See Wolfe Par [0301] which discloses considerations of flavor combinations on a regional level, such as state or other geographic area)
acquiring information and preferences from the user to construct user profile wherein the user profile comprises at least one preferred ingredient or one preferred dietary item or one preferred geographical location (See Wolfe Par [0171]-[0174]; Figs. 3A-3B, 5A, 6, & 13 which discloses various user preferences in terms of flavors, textures, ingredients, food items, etc. for a user and constructing a user profile of preferences over time);
mapping the user profile against the profile of a plurality of dietary items in the database (See Wolfe Par [0272]-[0273], [0323], Figs. 18A, 27A, & 31; See Wolfe Par [0066] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user);
constructing a confidence score for each of the mapped dietary items (While not “confidence score” per se, see Wolfe Par [0270]-[0273], [0323], and Figs. 18A, 27A, & 31 which disclose outputting a score, such as out of 100, that indicates compatibility of each food product to the user, such that this compatibility score could be interpreted to represent a “confidence score” under BRI, but for purposes of advancing prosecution, an additional reference has been applied below to read on “confidence score” specifically);
creating a set of dietary items having confidence score within a range, wherein the said range is calibrated with the user’s profile (While not “confidence score” per se, see Wolfe Par [0270]-[0273]; [0323]; Figs. 18A, 27A, & 31 which disclose outputting a score, such as out of 100, that indicates compatibility of the food product to the user, such that this compatibility score could be interpreted to represent a “confidence score” under BRI, such that a corresponding query from the user for food item compatibility only returns results having flavor category values matching or within a range to the corresponding category values of the user, i.e. user profile; See Wolfe Par [0149]-[0150], [0267], Figs. 17A-17B; See Wolfe Par [0066] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user);
generating recommendation information for the user, wherein the recommendation information comprises at least one dietary item selected from the set of dietary items having the confidence score within the range (See Wolfe Par [0148]; See Wolfe Par [0066] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user); and
presenting the recommendation information to the user (See Wolfe Par [0148]; See Wolfe Par [0066] & [0148] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user, and presenting the list of recommended food elements to the user).
While Wolfe generally discloses generating a compatibility score for each of potential dietary items for a user, Wolfe does not explicitly mention a “confidence” score per se, as required by the following limitations:
constructing a confidence score for each of the mapped dietary items;
creating a set of dietary items having confidence score within a range, wherein the said range is calibrated with the user’s profile.
However, Hadad discloses constructing a confidence score for each of the mapped dietary items (See Hadad Par [0214], [0238], & [0260] which discloses the food classification for each dietary item including a confidence score, such that a confidence threshold can be set, and further, algorithms success can be determined by said measures of confidence that the predictions are correct; See Hadad Par [0196] & [0206]-[0209] which also discloses a method of using said determined confidence score for determining potential ingredients in one or more foods for accurately determining appropriate foods for users with potential food allergies or restrictions) and creating a set of dietary items having confidence score within a range, wherein the said range is calibrated with the user’s profile (See Hadad Par [0214], [0238], & [0260] which discloses the food classification for each dietary item including a confidence score, such that a confidence threshold can be set, and further, algorithms success can be determined by said measures of confidence that the predictions are correct; See Hadad Par [0196] & [0206]-[0209] which also discloses a method of using said determined confidence score for determining potential ingredients in one or more foods for accurately determining appropriate foods for users with potential food allergies or restrictions). The disclosure of Hadad is directly applicable to the disclosure of Wolfe because both disclosures share limitations and capabilities, such as being directed towards personalization of dietary ingredients/foods for a user based on attributes of those ingredients/food.
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 disclosure of Wolfe, which already discloses generating a compatibility score for each of potential dietary items for a user based on attributes of the food, to further include a confidence score in particular, as disclosed by Hadad, because this can be used to filter or add human verification input for results and/or allows for scoring and thereby accurately determining appropriate foods for users with potential food allergies or restrictions (See Hadad Par [0260] & [0206]-[0209]).
Claim 2 –
Regarding Claim 2, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said dietary items in the database includes cuisines, fruits, vegetables, ingredients, beverages, meat, edible plants or extracts thereof, etc. (See Wolfe Par [0173] which discloses various ingredients/items such as meats, vegetables, dairy, spices, ingredients, etc.; See Table 3 which discloses various textures and/or dietary items such as varying foods or beverages).
Claim 3 –
Regarding Claim 3, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said ingredient profile comprises information about the kind, quantity, and quality of the ingredients in the dietary item including information about the molecular ingredients, micronutrients, phytonutrients, macronutrients, chemicals, additives, antioxidants, and spices used in the dietary item (See Wolfe Par [0130], [0142], & [0266] which discloses food elements includes at least one of temperature, preparation time, allergens, ingredients, which is understood to naturally include chemicals, additives, antioxidants, and/or spices in a complete list of ingredients, texture, caloric value, fat value, carbohydrate value, i.e. macronutrients, vitamin value, i.e. macronutrients/phytonutrients, health rating; See Wolfe Par [0330] which specifically mentions considerations of “spices” and a match score for the user flavor profile).
Claim 4 –
Regarding Claim 4, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said visual profile, taste profile, aroma profile, and texture profile comprises intensity scores associated with the visual tags, taste tags, aroma tags, and texture tags respectively of the dietary item (See Wolfe Par [0167] & [0177] which discloses a food element flavor mark for a product or recipe may be represented by perceived intensity of relative categories (visual, taste, aroma, texture, etc.) to other categories).
Claim 5 –
Regarding Claim 5, Wolfe and Hadad disclose the method of claim 4 in its entirety. Wolfe further discloses a method, wherein:
the said intensity scores are in the form of range of values (See Wolfe Par [0167] & [0177] which discloses a food element flavor mark for a product or recipe may be represented by perceived intensity of relative categories (visual, taste, aroma, texture, etc.) to other categories; See Wolfe Par [0270] which discloses the query only returning results having flavor category values, for instance, matching or within a range to the corresponding category values of the user, and would include the intensity values described in Wolfe Par [0167] & [0177]).
Claim 6 –
Regarding Claim 6, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said profile of each of the dietary item further comprises information about a recipe for preparation of the dietary item including information about cooking, roasting, processing, chopping, mixing, grinding, serving, etc. of all the ingredients (See Wolfe Par [0173] which discloses further information/categories regarding cooking methods of the various foods/ingredients, such as baking, dicing, garnishing, etc.).
Claim 7 –
Regarding Claim 7, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said taste profile comprises tags and corresponding intensity score for a mouthfeel experience of the prepared dietary item after a requisite cooking, roasting, processing, chopping, mixing, grinding, etc. of the ingredients as per a recipe (See Wolfe Par [0173] which discloses further information/categories regarding cooking methods of the various foods/ingredients, such as baking, dicing, garnishing, etc.; See Wolfe Par [0167] & [0177] which discloses a food element flavor mark for a product or recipe may be represented by perceived intensity of relative categories (visual, taste, aroma, texture, etc.) to other categories; See Wolfe Par [0270] which discloses the query only returning results having flavor category values, for instance, matching or within a range to the corresponding category values of the user, and would include the intensity values described in Wolfe Par [0167] & [0177]).
Claim 8 –
Regarding Claim 8, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said sensory profile further comprises a somatosensory profile and an auditory profile of the dietary item (See Wolfe Par [0318] which discloses the inclusion/consideration of sensory data; See Table 3 which discloses considerations of a sound, e.g. crack, that is heard when associated with the texture of crispy/crunchy food, constituting auditory information/profile of the item; “Somatosensory” in light of Applicant’s Specification is understood to constitute mere feelings or sensations experienced when eating food, therefore see Wolfe Par [0173] which discloses the consideration of a preferred food experience, including textures, smells, feelings, tastes, and temperatures which would constitute a somatosensory profile via the various feelings, textures, smells, temperatures, i.e. sensations of the food).
Claim 9 –
Regarding Claim 9, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said geographical location in the profile of dietary item is in the form of name of a city, district, state, country, continent, restaurant, hotel, outlet, etc. preferably the location which the dietary item is considered to be native to or is most commonly associated with (See Wolfe Par [0214] which discloses a predicted food style based on demographic or location, i.e. geographical territory, associated with the food item/style; See Wolfe Par [0263] which discloses generally considering location or date or other constraints for certain foods, such as when the location is “the south”, regional foods of this area are given higher weight in the search for “foods that take less than thirty minutes”; See Wolfe Par [0301] which discloses considerations of flavor combinations on a regional level, such as state or other geographic area; Although not relied upon since Wolfe fully discloses the limitations above since the elected locations are no specifically included/elected see Hadad Par [0026] which discloses the use of reastuarant menus, food manufacturers, etc., as well for generation ).
Claim 10 –
Regarding Claim 10, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe and Hadad further discloses a method, wherein:
the said profile of each dietary item is constructed, curated, modified, managed, stored, processed, and presented by an automated computer implemented device enabled with techniques of self-learning and artificial intelligence (See Wolfe Par [0245] & [0343] which discloses the use of a computer-based system comprising various processing units and/or engines for performing embodiments recited throughout Wolfe, i.e. automated; See Hadad Par [0058] for unsupervised learning models, i.e. self-learning; See Hadad Par [0150]-[0152] & [0190] which discloses the food analysis system leveraging one or more automated computer algorithms comprising at least one machine learning algorithm to abstract information and abstraction layers/metadata tags/labels of foods, such that the algorithm can comprise include artificial intelligence (AI), deep learning, or optical character recognition (OCR) capabilities).
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 already-combined disclosure of Wolfe and Hadad which discloses the use of computer-based system comprising various processing units and/or engines for performing automated embodiments of food-based recommendation and steps associated therewith to further specifically include techniques of self-learning and artificial intelligence, as disclosed by Hadad, because food categories and information relating to said categories may possess certain gaps or limitations that can be addressed by said algorithms (See Hadad Par [0150]-[0152] & [0190]).
Claim 11 –
Regarding Claim 11, Wolfe and Hadad disclose the method of claim 10 in its entirety. Wolfe and Hadad further disclose a method, wherein:
the said automated computer implemented device is connected with the web to through an internet protocol, wherein the device is configured to fetch the information about the dietary items from the existing databases to construct profiles on a real-time basis (See Wolfe Par [0245] & [0343] which discloses the use of a computer-based system comprising various processing units and/or engines for performing embodiments recited throughout Wolfe, i.e. automated; See Hadad Par [0150]-[0152] & [0190] which discloses the food analysis system leveraging one or more automated computer algorithms comprising at least one machine learning algorithm to abstract information and abstraction layers/metadata tags/labels of foods, such that the algorithm can comprise include artificial intelligence (AI), deep learning, or optical character recognition (OCR) capabilities; See Hadad Par [0025]-[0028] & [0168] which discloses the food analysis system connecting to the internet and possibly using one or more automated web-crawlers to search for portions of food-related data from internet sources).
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 already-combined disclosure of Wolfe and Hadad which discloses the use of computer-based systems comprising various processing units and/or engines for performing automated embodiments of food-based recommendation, such as via machine learning and/or artificial intelligence, to further include the said automated computer implemented device is connected with the web to through an internet protocol for fetching information about the dietary items, as further disclosed by Wolfe and Hadad, because this allows for searching the Internet sources in a continuous manner and updating the food ontology substantially in real-time and for access to increased magnitudes of food-related data due to data being obtained from internet sources and not just local storages (See Hadad Par [0025]-[0028]).
Claim 12 –
Regarding Claim 12, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said user profile includes information about external factors such as user's current location, weather conditions, time of the day, occasion, space, ambience, etc. (See Wolfe Par [0134] which discloses constraint inputs for a user requesting a query further including time of the query, weather at the location of the query, location of the query; See Wolfe Par [0229] which discloses a step of obtaining demographic information and/or food consumption context information including time, feelings, meal, weather, cooking methods, temperatures of food, etc.; See Wolfe Par [0252] which discloses certain food elements being selected based on the season, weather, location, popular trends, etc.).
Claim 13 –
Regarding Claim 13, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said user profile includes information gathered from user's cognitive behaviour and patterns such as emotions, moods, health goals, allergies, medical conditions, food habits, etc. (See Wolfe Par [0244] which discloses considerations of user preferences and behaviors when developing recommendations for users such as to be used by companies/organizations; See Wolfe Par [00249] which specifies user flavor profile data including varying data relating to demographic information, allergy information, health eating preferences, i.e. food habits; See Wolfe Par [0266] which discloses a user having diabetes, i.e. medical conditions, such that the health rating of a sugary food element could be low which a health rating of green beans, for example, could be high).
Claim 14 –
Regarding Claim 14, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said user profile is updated each time the user exercises and expresses a choice with respect to a dietary item whether recommended or otherwise (See Wolfe Par [0170] & [0216] which discloses receiving information regarding a user over time and updating a user’s flavor and/or profile preferences over time , See Hadad Par [0036]-[0038] & [0131] which discloses the plurality of physiological inputs can relate to sleep patterns, exercise, blood test, etc. for determinations recognizing effects on a user’s metabolism).
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 already-combined disclosure of Wolfe and Hadad which discloses the collection of various user information over time to create and update a user profile over time, such that information regarding a user exercising can be received, as disclosed by Hadad, because this directly affects a user’s typical food, drink, or nutritional intakes due to recognized effects on a user’s metabolism (See Hadad Par [0036]).
Claim 15 –
Regarding Claim 15, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the user profile also includes a score depicting amenability of the user to experiment and try dietary items outside the comfort range for the user (See Wolfe Par [0214] which discloses determining food neophobia of the user, i.e. aggregability to new food or food experiences, See Wolfe Par [0251] which discloses various attributes being given certain weight for a weighing algorithm, i.e. scoring, algorithm, such as if the user has low food neophobia, i.e. the user is willing to try a good that may have a slightly different flavor profile, etc.; See Table 2 which specifically states an assigned score of food neophobia as a value of “13”), and wherein
the said score is visible to the user and can be adjusted by the user (See Wolfe Par [0214] which discloses determining food neophobia of the user, i.e. aggregability to new food or food experiences, See Wolfe Par [0251] which discloses various attributes being given certain weight for a weighing algorithm, i.e. scoring, algorithm, such as if the user has low food neophobia, i.e. the user is willing to try a good that may have a slightly different flavor profile, etc.; See Table 2 which specifically states an assigned score of food neophobia as a value of “13”; See Wolfe Par [0199] & [0252] which discloses results can be adjusted based on predetermined factors that are selected by the user).
Claim 16 –
Regarding Claim 16, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said acquisition of information and preferences from the user to construct the user profile is carried out through an application interface on an electronic device (See Wolfe Par [0201] which discloses receiving information via the user preference input unit, i.e. interface, using mobile devices, such as a tablet computer, etc.; See Wolfe Figs. 11A-11C for associated user interface to receive inputs), preferably a mobile/handheld device connected with the internet and configured with an application to display and receive information from the user on a real-time basis (See Wolfe Par [0201] which discloses receiving information via the user preference input unit, i.e. interface, using mobile devices, such as a tablet computer, etc.; See Wolfe Figs. 11A-11C for associated user interface to receive inputs).
Claim 17 –
Regarding Claim 17, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe and Hadad further disclose a method, wherein:
the said user profile is constructed, curated, modified, managed, stored, and presented by an automated computer implemented device enabled with techniques of self-learning and artificial intelligence (See Wolfe Par [0245] & [0343] which discloses the use of a computer-based system comprising various processing units and/or engines for performing embodiments recited throughout Wolfe, i.e. automated; See Hadad Par [0058] for unsupervised learning models, i.e. self-learning; See Hadad Par [0150]-[0152] & [0190] which discloses the food analysis system leveraging one or more automated computer algorithms comprising at least one machine learning algorithm to abstract information and abstraction layers/metadata tags/labels of foods, such that the algorithm can comprise include artificial intelligence (AI), deep learning, or optical character recognition (OCR) capabilities).
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 already-combined disclosure of Wolfe and Hadad which discloses the use of computer-based system comprising various processing units and/or engines for performing automated embodiments of food-based recommendation and steps associated therewith to further specifically include techniques of self-learning and artificial intelligence, as disclosed by Hadad, because food categories and information relating to said categories may possess certain gaps or limitations that can be addressed by said algorithms (See Hadad Par [0150]-[0152] & [0190]).
Claim 18 –
Regarding Claim 18, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe and Hadad further disclose a method, wherein:
the said automated computer implemented device is connected with the user through an internet protocol and an application interface (See Wolfe Par [0245] & [0343] which discloses the use of a computer-based system comprising various processing units and/or engines for performing embodiments recited throughout Wolfe, i.e. automated; See Wolfe Par [0201] which discloses receiving information via the user preference input unit, i.e. interface, using mobile devices, such as a tablet computer, etc.; See Wolfe Figs. 11A-11C for associated user interface to receive inputs; See Wolfe Par [0272] & [0321] which discloses the application providing implementation of the various algorithms and interfacing with a website, i.e. internet, such as to provide an interface for the user; See Wolfe Par [0353] which discloses a communication network being coupled to the system, such as the internet), wherein
the device is configured to receive the information from the user for constructing, curating, modifying, managing, storing, and presenting the user profile on a real-time basis (See Wolfe Par [0245] & [0343] which discloses the use of a computer-based system comprising various processing units and/or engines for performing embodiments recited throughout Wolfe, i.e. automated; See Hadad Par [0025]-[0028], [0168], & [0210]-[0211] which discloses the food analysis system mapping various data onto the food ontology substantially in real-time).
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 already-combined disclosure of Wolfe and Hadad which discloses the use of computer-based systems comprising various processing units and/or engines for performing automated embodiments of food-based recommendation, such as via machine learning and/or artificial intelligence, to further include performing actions in real-time, as disclosed by Hadad, because this allows for real time updating of a user’s preferences with regards to potential foods to be consumed, such as at a restaurant, such that the food analysis system can automatically estimate types and amounts of unknown ingredients based on the known ingredients specified in the obtained data or other similar foods in the food ontology and/or use at least a probabilistic model to estimate ingredients that must or may appear in the foods to determine whether a potential food is favorable for a user’s preferences in that environment in real-time (See Hadad Par [0210]-[0211]).
Claim 19 –
Regarding Claim 19, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe and Hadad further discloses a method, wherein:
the said mapping of the user profile against the profile of a plurality of dietary items is carried out by an automated computer implemented device configured with techniques of self-learning and artificial intelligence wherein the said mapping, construction of confidence scores, and selection of dietary items having confidence score within a range is carried out on a real-time basis (See Wolfe Par [0245] & [0343] which discloses the use of a computer-based system comprising various processing units and/or engines for performing embodiments recited throughout Wolfe, i.e. automated; See Hadad Par [0214], [0238], & [0260] which discloses the food classification for each dietary item including a confidence score, such that a confidence threshold can be set, and further, algorithms success can be determined by said measures of confidence that the predictions are correct; See Hadad Par [0196] & [0206]-[0209] which also discloses a method of using said determined confidence score for determining potential ingredients in one or more foods for accurately determining appropriate foods for users with potential food allergies or restrictions; See Hadad Par [0058] for unsupervised learning models, i.e. self-learning; See Hadad Par [0150]-[0152] & [0190] which discloses the food analysis system leveraging one or more automated computer algorithms comprising at least one machine learning algorithm to abstract information and abstraction layers/metadata tags/labels of foods, such that the algorithm can comprise include artificial intelligence (AI), deep learning, or optical character recognition (OCR) capabilities).
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 already-combined disclosure of Wolfe and Hadad which discloses the use of computer-based system comprising various processing units and/or engines for performing automated embodiments of food-based recommendation and steps associated therewith to further specifically include techniques of self-learning and artificial intelligence, as disclosed by Hadad, because food categories and information relating to said categories may possess certain gaps or limitations that can be addressed by said algorithms (See Hadad Par [0150]-[0152] & [0190]).
Claim 20 –
Regarding Claim 20, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the dietary recommendation information includes name, description, characteristics, ingredients, profile, image, recipe, or nutritional value of one or more dietary items or a restaurant, geographical location, or a dietary plan, etc. (See Wolfe Par [0060] & [0121] which discloses including ingredient information for the food element and correlation information regarding the ingredient information; See Wolfe Par [0266] which discloses various characteristics of each of the food elements to be included in considering a match for a user, such that this is understood to constitute a “profile”; See Wolfe Par [0130], [0142], & [0266] which discloses food elements includes at least one of temperature, preparation time, allergens, ingredients, which is understood to naturally include chemicals, additives, antioxidants, and/or spices in a complete list of ingredients, texture, caloric value, fat value, carbohydrate value, i.e. macronutrients, vitamin value, i.e. macronutrients/phytonutrients, health rating; See Wolfe Par [0166]-[0169] which discloses the dietary recommendation information for one or more food elements or foods including attributes thereof, recipe, nutritional value, ingredients therein, etc.).
Claim 21 –
Regarding Claim 21, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the dietary items included in the said recommendation information are to enhance the sensory experience of the user (See Wolfe Par [0002] which discloses the embodiments relating generally to providing flavor advertisement and enhancement, i.e. enhance sensory experience of the user; See Wolfe Par [0170] which discloses the user flavor mark being a dynamic representation that is updated as the user’s flavor preferences are updated to better determine or enhance the user’s flavor preferences or desired foods associated therewith over time; See Wolfe Par [0277] which disclose various flavor circles that inspire users to try new flavors).
Claim 22 –
Regarding Claim 22, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said recommendation information is displayed to the user through an interactive application interface on an electronic device, preferably a mobile/handheld device connected with the internet (See Wolfe Par [0201] which discloses receiving information via the user preference input unit, i.e. interface, using mobile devices, such as a tablet computer, etc.; See Wolfe Figs. 11A-11C for associated user interface to receive inputs; See Wolfe Par [0272] & [0321] which discloses the application providing implementation of the various algorithms and interfacing with a website, i.e. internet, such as to provide an interface for the user; See Wolfe Par [0353] which discloses a communication network being coupled to the system, such as the internet).
Claim 23 –
Regarding Claim 23, Wolfe and Hadad discloses the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said database is searchable by the user on the parameters of ingredients, taste, aroma, texture, visuals, geographical region, recipe, mood, emotions, occasion, nutritional value, allergies, restaurant, cooking method, etc. (See Wolfe Par [0246] which discloses a user being able to search a food mark storage database for food elements and corresponding data for each oft eh food elements including example, recipes, food products, dinner menus, culinary dishes, sides, main courses, ingredients, etc.; See Wolfe Par [0275] which discloses the user entering various terms to be presented with recommendations regarding certain flavors, preferences, etc., that match the user’s needs/preferences; See Wolfe Par [0244] which discloses considerations of user preferences and behaviors when developing recommendations for users such as to be used by companies/organizations; See Wolfe Par [00249] which specifies user flavor profile data including varying data relating to demographic information, allergy information, health eating preferences, i.e. food habits; See Wolfe Par [0266] which discloses a user having diabetes, i.e. medical conditions, such that the health rating of a sugary food element could be low which a health rating of green beans, for example, could be high; See Wolfe Par [0333] which discloses categories for a food such as cooking contexts, including baking, grilling, etc.).
Claim 24 –
Regarding Claim 24, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe further discloses a method, wherein:
the said user constitutes a plurality of individuals such that the dietary recommendation generated is for the individuals to dine together (See Wolfe Par [0171] which specifies the user preference profile may be organizing for a single user or for a group of users, such as a household; See Wolfe Par [0277] which discloses a flavor circle where users, i.e. multiple users, can be used to discover other users having similar flavor preference and encouraging or inspiring users to mingle, e.g. dine together, with other like-minded cooks; See Wolfe Par [0249]-[0250] & Table 2 which discloses user flavor profile information being used in a group context, such as for a family, for recommendations when dining together).
Claim 25 –
Regarding Claim 25, Wolfe and Hadad disclose the method of claim 1 in its entirety. Wolfe and Hadad further disclose a method, wherein:
the said confidence score is visible to the user to assist in making a decision (While not “confidence score” per se, see Wolfe Par [0270]-[0273]; [0323]; Figs. 18A, 27A, & 31 which disclose outputting a score, such as out of 100, that indicates compatibility of the food product to the user, such that this compatibility score could be interpreted to represent a “confidence score” under BRI, such that a corresponding query from the user for food item compatibility only returns results having flavor category values matching or within a range to the corresponding category values of the user, i.e. user profile, and further explicitly states in [0323] that the flavor mark of a recipe is shown along with the match score, displayed as a percentage, i.e. visible to the user to assist in making a decision; See Hadad Par [0214], [0238], & [0260] which discloses the food classification for each dietary item including a confidence score, such that a confidence threshold can be set, and further, algorithms success can be determined by said measures of confidence that the predictions are correct; See Hadad Par [0196] & [0206]-[0209] which also discloses a method of using said determined confidence score for determining potential ingredients in one or more foods for accurately determining appropriate foods for users with potential food allergies or restrictions; See Hadad Par [0214] & [0238] & Fig. 12B which discloses a confidence score that can be used to add human verification for input, such that the score is thereby presented such as in the table 1220 presented to the user for verification).
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 combined disclosure of Wolfe and Hadad, which already discloses generating a confidence score for each of potential dietary items for a user based on attributes of the food, to further include a confidence score that is visible to the user, in particular, as disclosed by Hadad, because this can be used to filter or add human verification input for results and/or allows for scoring and thereby accurately determining appropriate foods for users with potential food allergies or restrictions and verification thereof by the user (See Hadad Par [0260], [0206]-[0209], & [0238]).
Claim 26 –
Regarding Claim 26, Hadad discloses a system comprising:
one or more computer-readable memory devices storing data and instructions (See Wolfe Par [0342] which discloses computer-readable instructions being stored in non-transitory electronic memories or other storage media and executed by a computer program; See Wolfe Par [0316] which discloses the use of a number of different databases for storing various data associated with patients, food, etc.);
one or more input-output devices with graphic user interfaces (See Wolfe Par [0342] which discloses computer-readable instructions being stored in non-transitory electronic memories or other storage media and executed by a computer program; See Wolfe Par [0201] which discloses receiving information via the user preference input unit, i.e. interface, using mobile devices, such as a tablet computer, etc.; See Wolfe Figs. 11A-11C for associated graphical user interface to receive inputs);
one or more data processing apparatuses configured to interact with one or more memory devices and input-output devices, wherein upon execution of the instructions stored in the memory devices the system perform operations (See Wolfe Par [0342] which discloses computer-readable instructions being stored in non-transitory electronic memories or other storage media and executed by a computer program) including:
compiling a database of plurality of dietary items and storing it in one or more computer-readable memory devices (See Wolfe Par [0236] which discloses one or more ingredient information of a food element in question being obtained, such that it may be obtained from a database containing the recipe/linked to the recipe, such that a flavor platform may have access to ingredient lists for products and recipes through a third-party service or through a local database included in the flavor platform; See Wolfe Par [0316] which discloses the use of a number of different databases for storing various data associated with patients, food, etc.);
constructing a profile for each of the dietary item in the database (See Wolfe Par [0060] & [0121] which discloses including ingredient information for the food element and correlation information regarding the ingredient information; See Wolfe Par [0266] which discloses various characteristics of each of the food elements to be included in considering a match for a user, such that this is understood to constitute a “profile”), wherein the profile of each of the dietary item comprises:
(i) an ingredient profile of the dietary item (See Wolfe Par [0060] & [0121] which disclose including ingredient information for the food element and correlation information regarding the ingredient information; See Wolfe Par [0173] which discloses food categories and flavor marks being subdivided into groups such as based on ingredients);
(ii) a sensory profile of the dietary item (See Wolfe Par [0316]-[0318], Fig. 25 which discloses sensory data being included in the food flavor mark database, thereby constituting a sensory profile), wherein the sensory profile comprises:
a visual profile comprising visual tags depicting visual attributes of the dietary item (See Par [0316] and Fig. 25, el. 701 which discloses a content database containing food product information and images of associated food product);
a taste profile comprising taste tags depicting taste attributes of the dietary item (See Wolfe Par [0067] which discloses the profile information of each of the food elements includes flavor profile information; See Par [0227] and Table 1 which disclose an exemplary list of flavor categories, i.e. tags, such as those also listed in Figs. 3A-3B);
an aroma profile taste profile comprising taste tags depicting taste attributes of the dietary item (See Wolfe Par [0101], [0116], & [0173] and Table 1 which discloses the preferred food experiences including different smells, i.e. aromas associated with tastes of the food and categories, i.e. tags, associated therewith, i.e. in Table 1, the categories “Nutty” describing the unique flavor and “aroma” associated with all types of nuts or “Yeasty” which describes the taste and/or aroma that fill the air when fresh bread is barked or the aroma of a full-bodied beer, typifying yeasty flavors);
a texture profile comprising texture tags depicting texture attributes of the dietary item (See Wolfe Par [0068] which discloses the profile information of each of the food elements including texture profile information; See Wolfe Par [0336]-[0339] & Table 3 which discloses various texture categories, i.e. tag, representing a food element’s physical interaction with the user when consumed by the user
(iii) a geographical profile of the dietary item, identifying at least one geographical territory associated with the dietary item (See Wolfe Par [0263] which discloses generally considering location or date or other constraints for certain foods, such as when the location is “the south”, regional foods of this area are given higher weight in the search for “foods that take less than thirty minutes”; See Wolfe Par [0301] which discloses considerations of flavor combinations on a regional level, such as state or other geographic area);
acquiring, through an input-output device with a graphic user interface, information and preferences from the user to construct user profile wherein the user profile comprises at least:
one preferred ingredient or one preferred dietary item or one preferred geographical location (See Wolfe Par [0171]-[0174]; Figs. 3A-3B, 5A, 6, & 13 which discloses various user preferences in terms of flavors, textures, ingredients, food items, etc. for a user and constructing a user profile of preferences over time);
mapping the user profile against the profile of a plurality of dietary items in the database by the processing apparatus (See Wolfe Par [0272]-[0273], [0323], Figs. 18A, 27A, & 31; See Wolfe Par [0066] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user);
constructing a confidence score for each of the mapped dietary items (While not “confidence score” per se, see Wolfe Par [0270]-[0273], [0323], and Figs. 18A, 27A, & 31 which disclose outputting a score, such as out of 100, that indicates compatibility of each food product to the user, such that this compatibility score could be interpreted to represent a “confidence score” under BRI, but for purposes of advancing prosecution, an additional reference has been applied below to read on “confidence score” specifically);
creating a set of dietary items having confidence score within a range, wherein the said range is calibrated with the user's profile (While not “confidence score” per se, see Wolfe Par [0270]-[0273]; [0323]; Figs. 18A, 27A, & 31 which disclose outputting a score, such as out of 100, that indicates compatibility of the food product to the user, such that this compatibility score could be interpreted to represent a “confidence score” under BRI, such that a corresponding query from the user for food item compatibility only returns results having flavor category values matching or within a range to the corresponding category values of the user, i.e. user profile; See Wolfe Par [0149]-[0150], [0267], Figs. 17A-17B; See Wolfe Par [0066] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user);
generating recommendation information for the user wherein the recommendation information comprises at least one dietary item selected from the set of dietary items having the confidence score within the range (See Wolfe Par [0148]; See Wolfe Par [0066] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user); and
presenting the recommendation information to the user through the input-output device with a graphic user interface (See Wolfe Par [0342] which discloses computer-readable instructions being stored in non-transitory electronic memories or other storage media and executed by a computer program; See Wolfe Par [0201] which discloses receiving information via the user preference input unit, i.e. interface, using mobile devices, such as a tablet computer, etc.; See Wolfe Figs. 11A-11C for associated graphical user interface to receive inputs; See Wolfe Par [0148] which discloses a display unit presenting the list of recommended elements to the user; See Wolfe Par [0066] & [0148] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user, and presenting the list of recommended food elements to the user).
While Wolfe generally discloses generating a compatibility score for each of potential dietary items for a user, Wolfe does not explicitly mention a “confidence” score per se, as required by the following limitations:
constructing a confidence score for each of the mapped dietary items;
creating a set of dietary items having confidence score within a range, wherein the said range is calibrated with the user’s profile.
However, Hadad discloses constructing a confidence score for each of the mapped dietary items (See Hadad Par [0214], [0238], & [0260] which discloses the food classification for each dietary item including a confidence score, such that a confidence threshold can be set, and further, algorithms success can be determined by said measures of confidence that the predictions are correct; See Hadad Par [0196] & [0206]-[0209] which also discloses a method of using said determined confidence score for determining potential ingredients in one or more foods for accurately determining appropriate foods for users with potential food allergies or restrictions) and creating a set of dietary items having confidence score within a range, wherein the said range is calibrated with the user’s profile (See Hadad Par [0214], [0238], & [0260] which discloses the food classification for each dietary item including a confidence score, such that a confidence threshold can be set, and further, algorithms success can be determined by said measures of confidence that the predictions are correct; See Hadad Par [0196] & [0206]-[0209] which also discloses a method of using said determined confidence score for determining potential ingredients in one or more foods for accurately determining appropriate foods for users with potential food allergies or restrictions).
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 disclosure of Wolfe, which already discloses generating a compatibility score for each of potential dietary items for a user based on attributes of the food, to further include a confidence score in particular, as disclosed by Hadad, because this can be used to filter or add human verification input for results and/or allows for scoring and thereby accurately determining appropriate foods for users with potential food allergies or restrictions (See Hadad Par [0260] & [0206]-[0209]).
Claim 27 –
Regarding Claim 27, Wolfe and Hadad discloses the system of claim 26 in its entirety. Wolfe and Hadad further disclose a system, wherein:
the said one or more computer-readable memory devices and processing apparatus are configured to store and process techniques of self-learning and artificial intelligence (See Wolfe Par [0245] & [0343] which discloses the use of a computer-based system comprising various processing units and/or engines for performing embodiments recited throughout Wolfe, i.e. automated; See Hadad Par [0058] for unsupervised learning models, i.e. self-learning; See Hadad Par [0150]-[0152] & [0190] which discloses the food analysis system leveraging one or more automated computer algorithms comprising at least one machine learning algorithm to abstract information and abstraction layers/metadata tags/labels of foods, such that the algorithm can comprise include artificial intelligence (AI), deep learning, or optical character recognition (OCR) capabilities).
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 already-combined disclosure of Wolfe and Hadad which discloses the use of computer-based system comprising various processing units and/or engines for performing automated embodiments of food-based recommendation and steps associated therewith to further specifically include techniques of self-learning and artificial intelligence, as disclosed by Hadad, because food categories and information relating to said categories may possess certain gaps or limitations that can be addressed by said algorithms (See Hadad Par [0150]-[0152] & [0190]).
Claim 28 -
Regarding Claim 28, Hadad discloses a system for generating custom dietary recommendation information for a user, the system comprising:
a computer readable storage device storing a database of a plurality of dietary items (See Wolfe Par [0342] which discloses computer-readable instructions being stored in non-transitory electronic memories or other storage media and executed by a computer program; See Wolfe Par [0316] which discloses the use of a number of different databases for storing various data associated with patients, food, etc.);
a device configured to generate and store profile of each dietary items in the database (See Wolfe Par [0060] & [0121] which discloses including ingredient information for the food element and correlation information regarding the ingredient information; See Wolfe Par [0266] which discloses various characteristics of each of the food elements to be included in considering a match for a user, such that this is understood to constitute a “profile”; See Wolfe Par [0342] which discloses computer-readable instructions being stored in non-transitory electronic memories or other storage media and executed by a computer program; See Wolfe Par [0201] which discloses receiving information via the user preference input unit, i.e. interface, using mobile devices, such as a tablet computer, etc.; See Wolfe Figs. 11A-11C for associated graphical user interface to receive inputs; See Wolfe Par [0316] which discloses the use of a number of different databases for storing various data associated with patients, food, etc.), wherein the profile of each dietary item comprises:
i. an ingredient profile of the dietary item (See Wolfe Par [0060] & [0121] which disclose including ingredient information for the food element and correlation information regarding the ingredient information; See Wolfe Par [0173] which discloses food categories and flavor marks being subdivided into groups such as based on ingredients);
ii. a sensory profile of the dietary item, wherein the sensory profile comprises a visual profile comprising
visual tags depicting visual attributes of the dietary item (See Wolfe Par [0316]-[0318], Fig. 25 which discloses sensory data being included in the food flavor mark database, thereby constituting a sensory profile)
a taste profile comprising taste tags depicting taste attributes of the dietary item (See Wolfe Par [0067] which discloses the profile information of each of the food elements includes flavor profile information; See Par [0227] and Table 1 which disclose an exemplary list of flavor categories, i.e. tags, such as those also listed in Figs. 3A-3B);
an aroma profile comprising aroma tags depicting aroma attributes of the dietary item (See Wolfe Par [0101], [0116], & [0173] and Table 1 which discloses the preferred food experiences including different smells, i.e. aromas associated with tastes of the food and categories, i.e. tags, associated therewith, i.e. in Table 1, the categories “Nutty” describing the unique flavor and “aroma” associated with all types of nuts or “Yeasty” which describes the taste and/or aroma that fill the air when fresh bread is barked or the aroma of a full-bodied beer, typifying yeasty flavors);
a texture profile comprising texture tags depicting texture attributes of the dietary item (See Wolfe Par [0068] which discloses the profile information of each of the food elements including texture profile information; See Wolfe Par [0336]-[0339] & Table 3 which discloses various texture categories, i.e. tag, representing a food element’s physical interaction with the user when consumed by the user); and
a geographical profile of the dietary item, identifying at least one geographical territory associated with the dietary item (See Wolfe Par [0263] which discloses generally considering location or date or other constraints for certain foods, such as when the location is “the south”, regional foods of this area are given higher weight in the search for “foods that take less than thirty minutes”; See Wolfe Par [0301] which discloses considerations of flavor combinations on a regional level, such as state or other geographic area);
a graphic user interface (GUI) configured to interact with the user to receive the user's preferences and shared recommendations (See Wolfe Par [0201] which discloses receiving information via the user preference input unit, i.e. interface, using mobile devices, such as a tablet computer, etc.; See Wolfe Figs. 11A-11C for associated graphical user interface to receive inputs; See Wolfe Par [0316] which discloses the use of a number of different databases for storing various data associated with patients, food, etc.);
a device configured to generate profile of the user based on the preferences shared by the user, wherein the use profile comprises at least: one preferred ingredient or one preferred dietary item or one preferred geographical location (See Wolfe Par [0347] which discloses one or more processors arranged for a multi-processing arrangement for execution of sequences of instructions, such that a separate processing device for each step could be employed, reading on each individualized computer device recited in the claim hereinafter; See Wolfe Par [0171]-[0174]; Figs. 3A-3B, 5A, 6, & 13 which discloses various user preferences in terms of flavors, textures, ingredients, food items, etc. for a user and constructing a user profile of preferences over time);
a mapping device configured to map the user profile against the profile of a plurality of dietary items in the database (See Wolfe Par [0272]-[0273], [0323], Figs. 18A, 27A, & 31; See Wolfe Par [0066] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user); and
a processor device coupled with the mapping device to constructing a confidence score for each of the mapped dietary items and to segregate the information of dietary items having confidence score within a range, wherein the said range is calibrated with the user's profile (While not “confidence score” per se, see Wolfe Par [0270]-[0273]; [0323]; Figs. 18A, 27A, & 31 which disclose outputting a score, such as out of 100, that indicates compatibility of the food product to the user, such that this compatibility score could be interpreted to represent a “confidence score” under BRI, such that a corresponding query from the user for food item compatibility only returns results having flavor category values matching or within a range to the corresponding category values of the user, i.e. user profile; See Wolfe Par [0149]-[0150], [0267], Figs. 17A-17B; See Wolfe Par [0066] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user);
a device to generate recommendation information for the user wherein the recommendation information comprises at least one dietary item selected from the set of dietary items having the confidence score within the range (See Wolfe Par [0148]; See Wolfe Par [0066] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user); and
an input/output device to transmit the generated recommendation to user's graphic user interface and to receive the user's response for analysis (See Wolfe Par [0342] which discloses computer-readable instructions being stored in non-transitory electronic memories or other storage media and executed by a computer program; See Wolfe Par [0201] which discloses receiving information via the user preference input unit, i.e. interface, using mobile devices, such as a tablet computer, etc.; See Wolfe Figs. 11A-11C for associated graphical user interface to receive inputs; See Wolfe Par [0148] which discloses a display unit presenting the list of recommended elements to the user; See Wolfe Par [0066] & [0148] which discloses that each of the profile information of each of the food elements are compared against the profile information of the user to determine food elements having a greatest positive correlation and to generate a list of recommended food elements to the user, and presenting the list of recommended food elements to the user).
However, Hadad discloses constructing a confidence score for each of the mapped dietary items and to segregate the information of dietary items having confidence score within a range (See Hadad Par [0214], [0238], & [0260] which discloses the food classification for each dietary item including a confidence score, such that a confidence threshold can be set, and further, algorithms success can be determined by said measures of confidence that the predictions are correct; See Hadad Par [0196] & [0206]-[0209] which also discloses a method of using said determined confidence score for determining potential ingredients in one or more foods for accurately determining appropriate foods for users with potential food allergies or restrictions) and the recommendation information comprises at least one dietary item selected from the set of dietary items having the confidence score within the range (See Hadad Par [0214], [0238], & [0260] which discloses the food classification for each dietary item including a confidence score, such that a confidence threshold can be set, and further, algorithms success can be determined by said measures of confidence that the predictions are correct; See Hadad Par [0196] & [0206]-[0209] which also discloses a method of using said determined confidence score for determining potential ingredients in one or more foods for accurately determining appropriate foods for users with potential food allergies or restrictions; See Hadad Par [0049] & [0296] which discloses generating a list of available foods for 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 disclosure of Wolfe, which already discloses generating a compatibility score for each of potential dietary items for a user based on attributes of the food, to further include a confidence score in particular, as disclosed by Hadad, because this can be used to filter or add human verification input for results and/or allows for scoring and thereby accurately determining appropriate foods for users with potential food allergies or restrictions (See Hadad Par [0260] & [0206]-[0209]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Riley et al. (U.S. Patent Publication No. 2021/0134434) discloses a system for improving a user's food selections by comparing one or more attributes of a food selection, such as nutritional profile, to one or more subjective criteria, such as a user's medical conditions, food allergies, and preferences for certain types of foods (vegan or vegetarian), and/or objective criteria;
Leifer et al. (U.S. Patent Publication No. 2019/0228856) discloses a method for improving food-related personalization for a user including determining food-related preferences associated with a plurality of users to generate a user food preferences database;
Murdoch et al. (U.S. Patent Publication No. 2020/0090060) discloses a method of operating a food preference algorithm involves retrieving a meal framework including at least one food component category from a meal framework database through operation of a meal selector configured by a preferences profile in a user profile, and based on the food item’s attributes.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUNTER J RASNIC whose telephone number is (571)270-5801. The examiner can normally be reached M-F 8am-5:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shahid Merchant can be reached at (571) 270-1360. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/H.R./Examiner, Art Unit 3684
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684