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 .
Status of Claim(s)
Claims 1-20 have been examined. Claims 1-3, 5-6, 8, 10-11, 13, and 19 have been amended.
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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ochiai et al. (US20210391051A1 hereinafter Ochiai) in view of Kang et al. (US20170148162A1 hereinafter Kang).
With respect to claim 1, Ochiai electronic apparatus comprising:
memory storing one or more computer programs; and
one or more processors communicatively coupled to the memory,
wherein the one or more computer programs include computer-executable instructions executed by the one or more processors, and
wherein the one or more processors configured to:
receive a user input for a food (‘051; Para 0043: by disclosure, Ochiai describes the users UA and UB may register the user information by performing an input operation on a predetermined application running on a smartphone SP illustrated in FIG. 1),
acquire food information corresponding to the food from the received user input (‘051; Para 0056: he storage unit 400 includes a food information DB 410, an ingredient information DB 420, and a user information DB 430. In addition, the storage unit 400 stores an order history of each user. The order history is a history of food orders placed by each user),
acquire nutritional ingredient information of the acquired food information by inputting the acquired food information into a nutritional ingredient circuitry (‘051; Para 0057: the food information DB 410 stores food information data regarding each food. The food information includes a recipe corresponding to each food. The ingredient information DB 420 stores ingredient information data including information regarding each ingredient. The information regarding each ingredient includes, for example, information regarding a nutritional value of each ingredient. The user information DB 430 stores user information data including information regarding a predetermined ingredient of the user. Details of each of the above-described databases),
Kang discloses
acquire candidate food probability information for a candidate food by inputting the nutritional ingredient information into a candidate food probability circuitry (‘162; Para 0132: : A list, from which one of the food type candidates is selected based on the feature information of the extracted food, may be displayed in the order of the weights assigned to the food types. If a specific kind of food is selected from the list according to a user input, the extracted food image may be recognized as the selected food type),
acquire food group probability information and preliminary food group capacity information by inputting the acquired nutritional ingredient information and the acquired candidate food probability information respectively into a food group probability circuitry and a food group capacity circuitry (‘162; Para 0067: As shown in FIG. 2, on a screen 22 in which the S-Health application is being executed, the processor 130 may compare the feature information of the type of food included in captured image 23 and feature information database of a plurality of food types stored in the storage 120, and display a list 24 of food types having similar difference is within a threshold value) feature information to the feature information of the food type included in the captured image 23. The list 24 of food types having similar feature information may include, for example, whole milk, low-fat milk, soy milk, banana milk, etc. Having similar feature information may indicate that the difference between the two values is within a threshold value).
wherein the preliminary food group capacity information and the final food group capacity information includes at least one of mass information, weight information or volume information. (‘162; Para 0061: the processor 130 may apply respective weights to the 100 food types that the user mainly eats. Thereafter, when the processor 130 detects a food type of the extracted food image from the captured image, there may be a case where, due to a similarity of feature information, the corresponding food image is detected as mushroom spaghetti, to which a weight is applied as food that the user regularly eats, or seafood spaghetti, to which no weight is applied as food having no history of the user having eaten it. In this example, the processor 130 may determine the food type included in the food image as the mushroom spaghetti because of the applied weight, thereby applying a higher detection probability to the types of food that the user eats more frequently.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of claimed invention to modify the information processing apparatus of Ochiai with the technique of control method as thaught by Kang and the motivation is to provide food group probability information and preliminary food group capacity information.
Ochiai in view of Kang discloses
acquire filtered food group probability information by removing a probability value less than a predetermined threshold value from the acquired food group probability information (‘051; Para 0124: FIG. 13, first, the control unit 200 acquires an order condition from the input unit 100 (S1101). Next, the control unit 200 extracts recipes corresponding to the order condition from the food information DB 410 on the basis of the order condition acquired in Step S1101 (S1102). Next, in a case where the number of items ordered by the user is less than or equal to a predetermined value (S1103: YES), the control unit 200 extracts a recipe whose “timing” is a main dish among recipes extracted in Step S1102 (S1104)), and
acquire final food group capacity information by coupling the filtered food group probability information with the preliminary food group capacity information (‘051; Para 0055: a function of determining a recipe on the basis of the food order acquired from the input unit 100. Specifically, the control unit 200 analyzes a content of the food order acquired from the input unit 100 and determines a content input by the user. Further, the control unit 200 may determine a recipe on the basis of other information in addition to the food order. The other information is stored in, for example, the storage unit 400 as described later. The control unit 200 appropriately acquires information from the storage unit 400 and determines a recipe. Further, the control unit 200 can update data stored in the storage unit 400. Note that the control unit 200 is included in the information processing apparatus that is independent of the input unit 100, the cooking unit 500, and the output unit).
Claim 11 and 19 are rejected as the same reason with claim 1.
With respect to claim 2, the combined art teaches the apparatus of claim 1, wherein the one or more processors are further configured to
acquire food group threshold value information including the threshold value corresponding to each of a plurality of food groups (‘051; Para 0045); and
acquire the filtered food group probability information by removing the probability value less than the threshold value included in the food group threshold value information from the acquired food group probability information for each of the plurality of food groups (‘051; Para 0124).
Claims 12 and 20 are rejected as the same reason with claim 2.
With respect to claim 3, the combined art teaches the apparatus of claim 1, wherein the one or more processors are further configured to acquire the preliminary food group capacity information indicating capacity information for each of a plurality of food groups by inputting the nutritional ingredient information and the candidate food probability information into the food group capacity circuitry (‘051; Para 0057).
Claim 13 is rejected as the same reason with claim 3.
With respect to claim 4, the combined art teaches the apparatus of claim 1, wherein the user input for the food includes at least one of text information, image information, or audio information, indicating a specific food (‘051; Para 0072: the example of the completed form stored in the “completed food image” column may be, for example, photographic data).
Claim 14 is rejected as the same reason with claim 4.
With respect to claim 5, the combined art teaches the apparatus of claim 1, wherein the one or more processors are further configured to
store, in the memory, a user history including accumulated capacity information for each of a plurality of food groups consumed by a user during a predetermined time period, and update the user history by accumulating a capacity value for each of the plurality of food groups that is included in the final food group capacity information (‘162; Abstract).
Claim 15 is rejected as the same reason with claim 5.
With respect to claim 6, the combined art teaches the apparatus of claim 5, wherein the one or more processors are further configured to acquire score information related to a user eating habit by comparing reference capacity information with the accumulated capacity information for each of a plurality of food groups that is included in the updated user history (‘162; Para 0076).
Claim 16 is rejected as the same reason with claim 6.
With respect to claim 7, the combined art teaches the apparatus of claim 6, wherein the score information includes at least one of a user eating habit score, a user age, or an average score of the user age (‘162; Para 0106: an eating habit management module).
Claim 17 is rejected as the same reason with claim 7.
With respect to claim 8, the combined art teaches the apparatus of claim 6, wherein the one or more processors are further configured to provide guide information indicating a recommended eating habit for a first food group by comparing a first capacity value of the first food group that is included in the updated user history with a first reference value corresponding to the first food group that is included in the reference capacity information (‘162; Para 0080. 0110, 0139).
Claim 18 is rejected as the same reason with claim 8.
With respect to claim 9, the combined art teaches the apparatus of claim 8, wherein the guide information includes at least one of information related to an insufficient food group or information related to an excessively consumed food group (‘162; Para 0067).
With respect to claim 10, the combined art teaches the apparatus of claim 1, further comprising: a display, wherein the one or more processors are further configured to control the display to display a guide screen including the food information and the final food group capacity information (‘051; Paras 0076).
Response to Arguments
Applicant's arguments filed 10/14/2025 have been fully considered but they are not persuasive.
In the Remark filed 10/14/2025, the Applicant argued that the combined art Ochiai/Kang does not disclose to acquire candidate food probability information for a candidate food by inputting the nutritional ingredient information into a candidate food probability circuitry.
In response to the Applicant’s argument, the Examiner respectfully gives the broadest reasonable interpretation of the amended claims. In fact, Kang discloses a list, from which one of the food type candidates is selected based on the feature information of the extracted food, may be displayed in the order of the weights assigned to the food types. If a specific kind of food is selected from the list according to a user input, the extracted food image may be recognized as the selected food type (‘162; Para 0132). Kang further discloses the processor 130 may apply respective weights to the 100 food types that the user mainly eats. Thereafter, when the processor 130 detects a food type of the extracted food image from the captured image, there may be a case where, due to a similarity of feature information, the corresponding food image is detected as mushroom spaghetti, to which a weight is applied as food that the user regularly eats, or seafood spaghetti, to which no weight is applied as food having no history of the user having eaten it. In this example, the processor 130 may determine the food type included in the food image as the mushroom spaghetti because of the applied weight, thereby applying a higher detection probability to the types of food that the user eats more frequently (‘162; Para 0061).
Given broadest reasonable interpretation of the recited claims, it is submitted that the food type candidates is selected based on the feature information of the extracted food as taught by Kang is in a form as described in the invention.
Therefore, the Examiner maintains rejection of all claims.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HIEP VAN NGUYEN whose telephone number is (571)270-5211. The examiner can normally be reached Monday through Friday between 8:00AM and 5:00PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jason B Dunham can be reached at 5712728109. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/HIEP V NGUYEN/Primary Examiner, Art Unit 3686