DETAILED ACTION
The following is a non-final, first office action in response to the application filed November 13, 2024. Claims 1-9 are currently pending and have been examined.
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 .
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 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Step 1: Statutory Category
(MPEP § 2106)
Regarding claims 1-7, in light of the Examiner’s claim interpretation of what is and what is not in the preamble, Claims 1-7 purports to set forth a “system” in the preamble, however the body of the claims do not recite any statutory structure that would define the “system”. All that is claimed in the body of the claims is functionally descriptive material that amounts to a program, per se, or a signal, per se. They are neither computer components nor statutory processes, as they are not ‘acts’ being performed.” MPEP §2106.01 I. Because the claims recite only abstractions that are neither “things” nor “acts,” the claims are not within one of the four statutory classes of invention. Because the claims are not within one of the four statutory classes of invention, the claims are rejected under 35 U.S.C. 101.
Regarding claim 9, in light of the Examiner’s claim interpretation of what is and what is not in the preamble, claim 9 recites a program 9 only. “program products claimed as computer listings per se, i.e., the descriptions or expressions of the programs, are not physical ‘things.' They are neither computer components nor statutory processes, as they are not ‘acts’ being performed.” MPEP §2106.01 I. Because the claims recite only abstractions that are neither “things” nor “acts,” the claims are not within one of the four statutory classes of invention. Because the claims are not within one of the four statutory classes of invention, the claims are rejected under 35 U.S.C. 101.
Claim 8 is directed towards a method. The claims are directed to a statutory category: a process, as defined under 35 U.S.C. § 101.
Regarding Claim 1:
Step 2A, Prong One: Judicial Exception – Abstract Idea
(MPEP § 2106.04)
The claim recites limitations that, when considered individually and as an ordered combination, are directed to certain methods of organizing human activity and/or mental processes implemented on a generic computer (i.e., collecting information about past meals and recommending what to eat next based on relationships in that information). In particular, the claim includes:
Acquiring event data about what a user ate (dish identification), categorizing dishes by “taste sensation,” and associating meals with meal times (i.e., collecting and classifying user consumption data).
Analyzing the event data to compute a “characteristic index” using association-analysis metrics such as support, confidence, and lift (i.e., mathematical/statistical analysis performed on data to derive relationships/patterns).
Outputting a dish candidate based on the derived index (i.e., providing a recommendation based on analyzed user data).
These limitations amount to collecting user information, classifying it, performing mathematical analysis to find correlations, and presenting a recommendation—i.e., an abstract idea of data analysis and recommendation (a form of information processing / mathematical relationships) that could be performed in the mind conceptually, and is also akin to organizing activity by guiding a user’s choices.
Step 2A, Prong Two: Integration into a Practical Application
(MPEP § 2106.04(d))
The claim does not recite additional elements that integrate the abstract idea into a practical application. The “acquirer,” “extractor,” and “recommender” are described at a functional level without specifying any improvement to computer capabilities (e.g., improved data structures, reduced computational burden, improved model training, sensor operation, or network performance), nor does the claim tie the analysis to a particular technological environment in a meaningful way beyond the field of menu/food selection. The recommendation output is the generic result of applying the mathematical association analysis to stored event data, and the claim does not require a particular transformation or use of the result to control a technical process or device. As such, the additional elements amount to generic computer implementation of collecting, analyzing, and presenting information, rather than an integration into a practical application.
Step 2B: Inventive Concept
(MPEP § 2106.05)
The claim does not include additional elements that amount to significantly more than the abstract idea. The recited “acquirer,” “extractor,” and “recommender” are generic functional components for input, processing, and output. The use of association-rule metrics (support/confidence/lift) and “time-series association analysis” is a recitation of mathematical/statistical techniques applied to user behavior data, which is itself part of the abstract idea, and the claim does not add a specific unconventional technical implementation of those techniques. Therefore, the claim lacks an inventive concept because it merely uses generic computing components to perform conventional data collection, mathematical analysis, and recommendation output.
Therefore, the claim is not directed to patent-eligible subject matter under 35 U.S.C. § 101.
Regarding Claim 8s and 9
Independent claims 8 and 9 is parallel in scope to claim 1 and ineligible for similar reasons.
Regarding Claims 2-7
Dependent claims 2-7 merely set forth further embellishments to the abstract idea, and therefore do not confer eligibility on the claimed invention and are ineligible for similar reasons to claim 1.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 and 3-9 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hadad (US 2019/0295440 A1).
Regarding claims 1, 8, and 9, Hadad discloses a food recommendation system comprising:
an acquirer that acquires in advance event data including dish identification information on a dish a user has eaten, dish type information including taste sensation information that classifies the dish by taste sensation, and meal time information (Hadad: paragraph [0301] - FIGS. 33A-33C illustrate exemplary windows of the GUI-based software interface showing multiple features. As shown in FIG. 33A, the window may display which food item the user has consumed (e.g. Pear Smoothie), how many ingredients are found or predicted to be present in the food item (e.g., Mangos, Goji Berries, Green Anjou Pear, etc), a generic or specific picture of the food item (e.g. directly imported from a respective restaurant's website), as well as a continuous tracking of the user's blood glucose level and insulin injection(s).);
an extractor that extracts a specific characteristic index corresponding to specific dish type information input from the user by calculating a characteristic index including at least one of a support level, a confidence level and a lift value related to eating habits of the user through time-series association analysis based on the event data (Hadad: paragraph [0211] - The food analysis system 210 can use at least a probabilistic model to estimate ingredients that must or may appear in the foods (e.g. a restaurant dish). The food analysis system also can calculate a probability (or confidence level) of the foods having the estimated ingredients, as well as the expected ranged of amounts of each estimated ingredient);
a recommender that outputs a dish candidate to be suggested to the user based on the specific characteristic index (Hadad: paragraph [0029] - (2) provide food and health recommendations to a user, and to gain an understanding of the user's taste profile).
Regarding claim 3, Hadad discloses all of the limitations as noted above in claim 1. Hadad further discloses wherein the event data includes ingredient information on the dish the user has eaten (Hadad: paragraph [0023] - In some embodiments, one or more categories of the food-related data can comprise food dishes, and the food dishes can comprise restaurant dishes. The statistical model of one or more algorithms can determine a probability of one or more ingredients appearing in the restaurant dishes, and an expected distribution of an amount of each ingredient.).
Regarding claim 4, Hadad discloses all of the limitations as noted above in claim 1. Hadad further discloses wherein the event data includes at least one of the dish identification information and the ingredient information, and the dish type information that are associated with each other (Hadad: paragraph [0023] - In some embodiments, one or more categories of the food-related data can comprise food dishes, and the food dishes can comprise restaurant dishes. The statistical model of one or more algorithms can determine a probability of one or more ingredients appearing in the restaurant dishes, and an expected distribution of an amount of each ingredient.).
Regarding claim 5, Hadad discloses all of the limitations as noted above in claim 1. Hadad further discloses wherein the extractor extracts the specific characteristic index by further using at least one of avoided ingredient information and preference information of the user (Hadad: paragraph [0267] - . From the recommendations, the user can find out specifically which food items the user's blood glucose level is most responsive to, which food items to avoid or consume more, an optimized time interval for insulin injection, etc. In an example, a recommendation may suggest that, “When you added avocado to your sandwiches your glucose response was over 30% lower [occurred 5 out of 6 times].”-).
Regarding claim 6, Hadad discloses all of the limitations as noted above in claim 1. Hadad further discloses wherein the recommender analyzes characteristics of eating habits of another user, and searches for the dish candidate based on the specific characteristic index of the user and a characteristic index of the another user (Hadad: Figure 20).
Regarding claim 7, Hadad discloses all of the limitations as noted above in claim 1. Hadad further discloses wherein the recommender outputs eating habit data that represents a time relationship of the event data by using a node and an edge based on the specific characteristic index (Hadad: Figure 21).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Hadad (US 2019/0295440 A1) in view of Sakamoto et al (US 2018/0322864 A1).
Regarding claim 2, Hadad discloses all of the limitations as noted above in claim 1. Hadad does not expressly disclose wherein the taste sensation information includes onomatopoeia information representing the taste sensation. Sakamoto discloses wherein the taste sensation information includes onomatopoeia information representing the taste sensation (Sakamoto: paragraph [0067] - In the case of food as illustrated in FIG. 3B, a plurality of samples having various values of evaluation scales are prepared, a plurality of subjects taste the samples in a blindfold state (also in a state where the subject cannot smell the sample if possible), and the subjects declare the sound symbolism word (onomatopoeia) that is imaged when tasting the sample.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and apparatus of Sullivan to have included wherein the taste sensation information includes onomatopoeia information representing the taste sensation, as taught by Hadad because it would help describe a taste (Sakamoto: paragraph [0004]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
PTO-892 Reference U discloses Recommend My Dish: A multi-sensory food recommender.
US 11/830,603 B1, Lee et al discloses System and method for providing nutrition information using artificial intelligence.
US 2023/0008912 A1, Aso et al discloses MENU RECOMMENDATION SYSTEM, MENU RECOMMENDATION METHOD, RECORDING MEDIUM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE.
US 2021/004891 A1, Abutair et al discloses PERSONA BASED FOOD RECOMMENDATION SYSTEMS AND METHODS.
US 2020/0303055 A1, Leifer et al discloses METHOD AND SYSTEM FOR PREFERENCE-DRIVEN FOOD PERSONALIZATION.
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KATHLEEN GAGE PALAVECINO
Primary Examiner
Art Unit 3688
/KATHLEEN PALAVECINO/Primary Examiner, Art Unit 3688