DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This office action is in response to the amendment filed on 04/28/2026.
Claims 1-18 are currently pending in this application. Claims 1, 3, 9 and 10 are amended. Claims 12-18 are new.
Information Disclosure Statement
The information disclosure statements (IDSs) submitted on 03/16/2026, 03/18/2026 and 03/24/2026 were filed. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Examiner’s Note
Applicants are suggested to include information from figures 7 and 8 with related text into the claims to provide a better condition for an allowance.
Response to Arguments
The previous objection to claim 3 has been withdrawn in response to the applicants’ amendments/remarks.
The previous double patenting rejections have been withdrawn in response to the applicants’ filing of the terminal disclaimers, which are approved on 05/03/2026.
Regarding the previous 112(b) rejections, the applicants have amended claims 1, 9 and 10 to include “… to become familiar with the test undergone by the subject, based on the attribute data and a relationship between the attribute data and the required trial quantity … content of the test is different at each time”, and have, in page 6 of the remarks, argued that “… the amendment clarifies that the required trial quantity is objectively estimated based on ‘a relationship between … at each time …”.
The applicants’ these arguments are not persuasive.
As rejected in the previous office action, how the test can be familiar based on the attribute data (e.g., “age”, for example a test for the age of 5 or 75 is defined as familiar, etc.). Moreover, the amended limitations, “… estimate a required trial quantity … based on … a relationship between the attribute data and the required trial quantity …”, are not clear as “how to define a relationship between two different information, such as the attribute data (e.g., age) and the required trial quantity (any number). Furthermore, it is not clear how the familiarity of a test can be defined as the content of the test is different at each time. Therefore, the applicants’ amendments do not overcome all of the previous rejections and the current amendments cause the new rejections stated in the 112 rejections section below.
Regarding the 102 rejections, the applicants have amended claim1 1, 9 and 10, and have, in page 7 of the remarks, argued that “… Yamamoto fails to disclose, estimating required trial quantity … is a trial quantity to be required for the subject to become familiar with a test undergone by the subject … Yamamoto at [0021]-[0023] … Yamamoto at [0028], fig. 2 … Yamamoto fails to disclose this concept and therefore also fails to disclose, the concept of ascertaining whether the subject becoming familiar … Yamamoto also fails to disclose this feature of the pending claims …”.
Examiner respectfully disagrees with these arguments.
As stated in the previous rejections, Yamamoto clearly teaches that when the state estimation unit 102 estimates that the user is in the first state as the estimation result (S103: YES), the state estimation unit 102 inputs the feature quantity acquired by the log information acquisition unit 101 to the second state estimation model 104a2 again. The state estimation unit 102 performs an estimation process using the second state estimation model 104a2 (S104) – see par. 0039. Moreover, Yamamoto, in par. 0068 further teaches that the application and the construction of two estimation models connected in series have been described, but the present invention is not limited thereto. For example, three estimation models may be connected in series to construct an estimation model, and the estimation model may be applied to an estimation process based on feature quantities, as illustrated in fig. 9. In other words, Yamamoto teaches to estimate a required trial quantity (e.g., the estimation models have to be run), which is a trial quantity to be required for the subject to become familiar with a test undergone by the subject (e.g., the quantity, such as two/three, of the estimation models have to be connected in series to construct an estimation model for the estimation process based on feature quantities), based on the attribute data (e.g., the feature quantity) and a relationship (e.g., the information of the correct answer data) between the attribute data and the required trial quantity (see fig. 8 and paras. 0064-0067 for information of the correct answer data). Furthermore, Yamamoto, in par. 0056, teaches wherein content of the test is different at each time (e.g., the log information is information in which time, the operation history associated with each other). See the 102-rejection section below for detail. Please note that the currently amended limitations are in a condition of lack of clarity and/or capability, and the 102 rejections are based on the limitations as best understood for a prior-art examination.
Thus, the applicants’ arguments are not persuasive. Please see amended rejections below for the amended claims. This action is final.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(a):
(a) IN GENERAL. —The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1-18 are rejected under 35 U.S.C. 112(a), as failing to comply with the written description requirements (e.g., the new matter issue).
Applicants have amended the claims 1, 9 and 10 to include subject matter “… estimate a required trial quantity … required for the subject to become familiar with a test undergone by the subject, based on the attribute data and a relationship between the attribute data and the required trial quantity … wherein content of the test is different at each time”, however, these amended limitations/terms were not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention.
Examiner noted that the specification describes that “The familiarity determination unit 17 determines whether or not the subject is familiar with the test based on the required trial quantity estimated by the trial quantity estimation unit 16 and the history information regarding the tests undergone by the subject …” – see par. 0041; and “… Fig. 6 shows the results of an experiment showing the average correct answer rate for a test conducted by subjects … All the tests undergone by the subjects … the contents themselves are different at each time” – see par. 0050. Please note that the information of par. 0050 and fig. 6 is for “the average correct answer rate”, NOT for estimating a required trial quantity for familiarity.
However, this information does not provide to support or describe the amended limitations, “… estimate a required trial quantity … required for the subject to become familiar with a test undergone by the subject, based on the attribute data and a relationship between the attribute data and the required trial quantity … wherein content of the test is different at each time”.
Claims 2-8 and 11-18 depend from the claim 1, 9 or 10, and are analyzed and rejected accordingly.
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 1-18 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 applicant regards as the invention.
Claim 1 (claims 9 and 10 include similar limitations) recites:
“… to be required for the subject to become familiar with a test undergone by the subject based on the attribute data and a relationship between the attribute data and the required trial quantity … wherein content of the test is different at each time”; however, it is not clear (1) how to define whether it is familiar or not based on the attribute data (e.g., a test for the age of 5 is defined as familiar, etc.) and a relationship between two different information, such as the attribute data (e.g., age) and the required trial quantity (any number); (2) how to estimate a required trial quantity .. based on … the required trial quantity (e.g., it is NOT possible to estimate a required trial quantity because it needs the required trial quantity, or to get a result it needs the result);
“… to become familiar with a test undergone by the subject based on the attribute data and a relationship between the attribute data and the required trial quantity … wherein content of the test is different at each time”, however, it is not clear (1) how the familiarity can be defined for a test with different contents; (2) how to change the content for a test at each time – or it is not clear to define a boundary of the limitations.
Claims 2-8 and 11-18 depend from the claim 1, 9 or 10, and are analyzed and rejected accordingly.
Claim 12 recites:
“… wherein the relationship between the attribute data and the required trial quantity is defined … acquire input data corresponding to attribute information of a sample provider from training data …”, however, it is not clear (1) whether the “attribute information” is the same as “attribute data” included before or not – or it is not clear to define a boundary of the limitations; (2) whether “a sample provider” is a “content provider” (see the different content at each time in the claim 1) or not; (3) whether the training data is the data for training the determination device or not – or omitting necessary step/component which causes the limitations unclear;
“… generate feature data conforming to an input format … update parameters of the trial quantity inference model such that an error between the required trial quantity … and a correct answer indicated by correct answer data corresponding to the input data …”, however, it is not clear (1) whether the feature data and the parameters have any relationship with the attribute data or not – or it is not clear to define a boundary of the limitations; (2) how to define the correct answer (data) of the input data (e.g., the correct answer of the relationship, etc.) – or omitting necessary step/component which cause the limitations unclear.
Claims 13, 14 and 15 recite “… determined to be familiar with the test when the trial quantity … is equal to or higher than the required trial quantity”, however, it is not clear how the trial quantity for the familiarity, which is defined as the required trial quantity in the claim 1, can be higher than the required trial quantity (e.g., how the two same-quantity can be higher than the other).
Claim Rejections - 35 USC § 102
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 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 1-18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Yamamoto et al. (US 2022/0148729 A1).
As per claim 1, Yamamoto teaches a determination device [see figs. 1, 10] comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to:
acquire attribute data indicating an attribute of a subject; estimate a required trial quantity, which is a trial quantity to be required for the subject to become familiar with a test undergone by the subject, based on the attribute data and a relationship between the attribute data and the required trial quantity [figs. 1, 3, 8; par. 0030, lines 1-6; par. 0038, lines 1-7; par. 0039, lines 1-7; par. 0040, lines 1-7; par. 0056, lines 1-8; par. 0068, lines 1-8 of Yamamoto teaches to acquire attribute data (e.g., the feature quantity) indicating an attribute of a subject (e.g., the operation information of a communication terminal); estimate a required trial quantity (e.g., the estimation models have to be run), which is a trial quantity to be required for the subject to become familiar with a test undergone by the subject (e.g., the quantity, such as two/three, of the estimation models have to be connected in series to construct an estimation model for the estimation process based on feature quantities), based on the attribute data (e.g., the feature quantity) and a relationship (e.g., the information of the correct answer data) between the attribute data and the required trial quantity (see fig. 8 and paras. 0064-0067 for information of the correct answer data)]; and
determine whether or not the subject is familiar with the test, based on the required trial quantity, wherein content of the test is different at each time [figs. 1, 3; par. 0030, lines 1-6; par. 0039, lines 1-7; par. 0040, lines 1-7; par. 0056, lines 1-8; par. 0075, lines 1-12; par. 0076, lines 1-4 of Yamamoto teaches to determine whether or not the subject is familiar (e.g., having the granularity of state estimation) with the test, based on the required trial quantity (e.g., the estimation models have to be run), wherein content of the test is different at each time (e.g., the log information is information in which time, the operation history associated with each other)].
As per claim 2, Yamamoto teaches the determination device according to claim 1.
Yamamoto further teaches wherein the at least one processor is configured to estimate the required trial quantity based on the attribute data and an inference model, and wherein the inference model is a model which learned a relation between data based on the attribute data and the required trial quantity [figs. 6, 8, 9; par. 0057, lines 1-7; par. 0072, lines 1-11; par. 0075, lines 1-12 of Yamamoto teaches to estimate the required trial quantity (e.g., the estimation models have to be run) based on the attribute data (e.g., the feature quantity) and an inference model (e.g., the description estimation model), and wherein the inference model is a model which learned a relation between data based on the attribute data (e.g., the feature quantity) and the required trial quantity (e.g., the estimation models have to be run)].
As per claim 3, Yamamoto teaches the determination device according to claim 1.
Yamamoto further teaches wherein the at least one processor is configured to estimate the required trial quantity based on the attribute data, an inference model, and a test result of the test, and wherein the inference model is a model which learned, by machine learning, a relation between data based on the attribute data and the test result and the required trial quantity [figs. 1, 3, 8; par. 0026, lines 1-4; par. 0057, lines 1-7; par. 0072, lines 1-11; par. 0075, lines 1-12 of Yamamoto teaches to estimate the required trial quantity (e.g., the estimation models have to be run) based on the attribute data (e.g., the feature quantity), an inference model (e.g., the description estimation model), and a test result (e.g., how detailed state estimation, or estimation granularity) of the test, and wherein the inference model is a model which learned, by machine learning, a relation between data based on the attribute data and the test result and the required trial quantity].
As per claim 4, Yamamoto teaches the determination device according to claim 3.
Yamamoto further teaches wherein the test result is time-series results of the test that the subject underwent in the past [par. 0071, lines 1-8; par. 0081, lines 1-6 of Yamamoto teaches wherein the test result is time-series results of the test that the subject underwent in the past (e.g., in the previous stage)].
As per claim 5, Yamamoto teaches the determination device according to claim 1.
Yamamoto further teaches wherein the at least one processor is configured to estimate the required trial quantity from the attribute data, based on a table in which each of candidates for the attribute is associated with the required trial quantity corresponding to the each of the candidates [par. 0104, lines 1-7 of Yamamoto teaches to estimate the required trial quantity from the attribute data, based on a table in which each of candidates for the attribute (e.g., the input information) is associated with the required trial quantity (e.g., the output information) corresponding to the each of the candidates (e.g., the input information) – see also rejections to the claim 1].
As per claim 6, Yamamoto teaches the determination device according to claim 1.
Yamamoto further teaches wherein the at least one processor is further configured to output a test result of the test based on a determination result of whether or not the subject is familiar with the test [par. 0075, lines 1-12; par. 0076, lines 1-4; par. 0078, lines 1-11 of Yamamoto teaches to output a test result of the test based on a determination result (e.g., determining that it is necessary to perform more detailed state estimation) of whether or not the subject is familiar with the test (e.g., whether or not the granularity of the state estimation is fine)].
As per claim 7, Yamamoto teaches the determination device according to claim 6.
Yamamoto further teaches wherein the at least one processor is configured to determine that the test result of the test is invalid if the determination result indicates that the subject is not familiar with the test [par. 0075, lines 1-12; par. 0076, lines 1-4; par. 0078, lines 1-11 of Yamamoto teaches to determine that the test result of the test is invalid (e.g., it is necessary to perform more detailed state estimation) if the determination result indicates that the subject is not familiar with the test (e.g., determining that the granularity of the state estimation is not fine)].
As per claim 8, Yamamoto teaches the determination device according to claim 6.
Yamamoto further teaches wherein the least one processor is configured to display or output, by audio, a determination result of validity of the test based on the determination result of whether or not the subject is familiar with the test [fig. 10; par. 0097, lines 4-8 of Yamamoto teaches to display or output, by audio (e.g., output by a display, a speaker or an LED lamp), a determination result of validity of the test based on the determination result of whether or not the subject is familiar with the test – see also rejections to the claims 1, 5 and 6].
Claims 9 and 10 are method and medium claims that correspond to the device claim 1, and are analyzed and rejected accordingly.
As per claim 11, Yamamoto teaches the determination device according to claim 6.
Yamamoto further teaches wherein the at least one processor is configured to output advice information for a manager of the subject to perform a decision-making regarding whether or not to continue to conduct the test [par. 0097, lines 4-8; par. 0104, lines 1-7 of Yamamoto teaches to output advice information for a manager (e.g., output for the management) of the subject to perform a decision-making regarding whether or not to continue to conduct the test (e.g., to overwritten, update, additionally written, etc.)].
As per claim 12, Yamamoto teaches the determination device according to claim 1.
Yamamoto further teaches:
wherein the relationship between the attribute data and the required trial quantity is defined by a trial quantity inference model, and wherein the at least one processor is further configured to execute the instructions to: acquire input data corresponding to attribute information of a sample provider from training data; generate feature data conforming to an input format of the trial quantity inference model from the acquired input data [figs. 1, 6-8; par. 0023, lines 1-8; par. 0026, lines 1-4; par. 0029, lines 1-17; par. 0057, lines 1-7; par. 0072, lines 1-11; par. 0075, lines 1-12 of Yamamoto teaches wherein the relationship (e.g., having a paired/correspondence relationship) between the attribute data (e.g., the feature quantity) and the required trial quantity (e.g., the number of estimation models have to be run) is defined by a trial quantity inference model (e.g., the description estimation model), and wherein the at least one processor is further configured to execute the instructions to: acquire input data (e.g., same input data or log information for the feature quantity) corresponding to attribute information of a sample provider from training data (e.g., the data for constructing the model); generate feature data conforming to an input format (e.g., the predetermined feature quantity format) of the trial quantity inference model from the acquired input data (e.g., the log information)];
update parameters of the trial quantity inference model such that an error between the required trial quantity to be outputted by the trial quantity inference model when the feature data is inputted and a correct answer indicated by correct answer data corresponding to the input data is minimized [figs. 7, 8; par. 0057, lines 1-13; par. 0058, lines 1-7; par. 0063, lines 1-9; par. 0065, lines 1-12; par. 0066, lines 1-8; par. 0067, lines 1-11; par. 0075, lines 1-12 of Yamamoto teaches to update parameters (e.g., replacing the correct answer corresponding to the feature quantities) of the trial quantity inference model such that an error between the required trial quantity to be outputted by the trial quantity inference model when the feature data is inputted and a correct answer indicated by correct answer data corresponding to the input data is minimized (e.g., connecting in series of the estimation models with replacing value of correct answer makes the granularity of state estimation finer/minimal)].
As per claim 13, Yamamoto teaches the determination device according to claim 1.
Yamamoto further teaches wherein the subject is determined to be familiar with the test when the trial quantity the subject has undergone is equal to or higher than the required trial quantity [figs. 3, 4; par. 0038, lines 1-7; par. 0039, lines 1-7; par. 0040, lines 1-7; par. 0048, lines 1-13 of Yamamoto teaches wherein the subject is determined to be familiar with the test when the trial quantity the subject has undergone (e.g., the trial quantity, such as two/three, of the estimation models have to be connected in series to construct an estimation model for the estimation process based on feature quantities) is equal to or higher than the required trial quantity (e.g., the number of estimation models have to be run)] – see also the rejections to the claim 1.
Claims 14 and 15 are method and medium claims that correspond to the device claim 13, and are analyzed and rejected accordingly.
As per claim 16, Yamamoto teaches the determination device according to claim 1.
Yamamoto further teaches wherein the subject is determined to be familiar with the test when a total number of trials undergone by the subject or a total time spent on the test by the subject is equal to or greater than the required trial quantity, the required trial quantity being a required number of trials or a required time for the test [figs. 3, 4; par. 0038, lines 1-7; par. 0039, lines 1-7; par. 0040, lines 1-7; par. 0048, lines 1-13 of Yamamoto teaches wherein the subject is determined to be familiar with the test when a total number of trials undergone by the subject (e.g., the trial quantity, such as two/three, of the estimation models have to be connected in series to construct an estimation model for the estimation process based on feature quantities) or a total time spent on the test by the subject is equal to or greater than the required trial quantity, the required trial quantity being a required number of trials (e.g., the number of estimation models have to be run) or a required time for the test].
Claims 17 and 18 are method and medium claims that correspond to the device claim 16, and are analyzed and rejected accordingly.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAUNG T LWIN whose telephone number is (571)270-7845. The examiner can normally be reached on Monday - Friday 10:00 am - 6:00 pm.
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/MAUNG T LWIN/Primary Examiner, Art Unit 2495
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