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 .
DETAILED ACTION
2. This office action is in response to the original filing of 11/22/2022. Claim 1-20 are pending and have been considered below.
3. 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more.
Claim 1:
Step 1: The claim is directed to a method, falling under one of the four statutory categories of invention.
Step 2A Prong 1: The claim recites following abstract ideas:
The limitation “training, using a first dataset of labeled data, a model, wherein the training comprises adjusting a feature extractor parameter of the model, a classifier parameter of the model, and a discriminator parameter of the model”;
“scoring, using the discriminator parameter and a parametric function of the feature extractor parameter, a plurality of samples of a dataset of unlabeled data, the scoring resulting in a scored plurality of samples”; “selecting, for labeling, a subset of the scored plurality of samples, the selecting resulting in a selected subset of the scored plurality of samples”;
“augmenting, responsive to receiving a label of each of the selected subset of the scored plurality of samples, the first dataset of labeled data with the selected subset of the scored plurality of samples and the label of each of the selected subset of the scored plurality of samples, the augmenting resulting in an augmented dataset of labeled data” and “retraining, using the augmented dataset of labeled data, the model, wherein the retraining comprises further adjusting the feature extractor parameter of the model, the classifier parameter of the model, and the discriminator parameter of the model” under broadest reasonable interpretation covers a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper.
Step 2A Prong 2: The following limitations recite additional elements:
“computer-implemented …” ” amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrate by: Relevant court decision: the followings are examples of court decisions demonstrating well-understood, routine and conventional activities, see e.g., MPEP 2106.05(d)(II) and MPEP 2106.05(f)(2): Computer comprising instructions to implement a method, e.g., see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Step 2B: Furthermore, the additional elements do not amount to significantly more than the judicial exception.
As previously discussed, the additional elements “computer-implemented …” amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrate by: Relevant court decision: the followings are examples of court decisions demonstrating well-understood, routine and conventional activities, see e.g., MPEP 2106.05(d)(II) and MPEP 2106.05(f)(2): Computer comprising instructions to implement a method, e.g., see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Accordingly, the claim does not recite any additional elements that amount to significantly more than the judicial exception.
Claim 9:
Step 1: The claim is directed to a computer program product, falling under one of the four statutory categories of invention.
Step 2A Prong 1: The claim recites following abstract ideas:
The limitation “training, using a first dataset of labeled data, a model, wherein the training comprises adjusting a feature extractor parameter of the model, a classifier parameter of the model, and a discriminator parameter of the model”;
“scoring, using the discriminator parameter and a parametric function of the feature extractor parameter, a plurality of samples of a dataset of unlabeled data, the scoring resulting in a scored plurality of samples”; “selecting, for labeling, a subset of the scored plurality of samples, the selecting resulting in a selected subset of the scored plurality of samples”;
“augmenting, responsive to receiving a label of each of the selected subset of the scored plurality of samples, the first dataset of labeled data with the selected subset of the scored plurality of samples and the label of each of the selected subset of the scored plurality of samples, the augmenting resulting in an augmented dataset of labeled data” and “retraining, using the augmented dataset of labeled data, the model, wherein the retraining comprises further adjusting the feature extractor parameter of the model, the classifier parameter of the model, and the discriminator parameter of the model” under broadest reasonable interpretation covers a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper.
Step 2A Prong 2: The following limitations recite additional elements:
“computer readable storage medium, and program instructions collectively stored on the one or more computer readable storage medium, the program instructions executable by a processor to cause the processor to perform…” ” amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrate by: Relevant court decision: the followings are examples of court decisions demonstrating well-understood, routine and conventional activities, see e.g., MPEP 2106.05(d)(II) and MPEP 2106.05(f)(2): Computer readable storage media comprising instructions to implement a method, e.g., see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Step 2B: Furthermore, the additional elements do not amount to significantly more than the judicial exception.
As previously discussed, the additional elements “computer readable storage medium, and program instructions collectively stored on the one or more computer readable storage medium, the program instructions executable by a processor to cause the processor to perform…” amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrate by: Relevant court decision: the followings are examples of court decisions demonstrating well-understood, routine and conventional activities, see e.g., MPEP 2106.05(d)(II) and MPEP 2106.05(f)(2): Computer readable storage media comprising instructions to implement a method, e.g., see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Accordingly, the claim does not recite any additional elements that amount to significantly more than the judicial exception.
Claim 20:
Step 1: The claim is directed to a system, falling under one of the four statutory categories of invention.
Step 2A Prong 1: The claim recites following abstract ideas:
The limitation “training, using a first dataset of labeled data, a model, wherein the training comprises adjusting a feature extractor parameter of the model, a classifier parameter of the model, and a discriminator parameter of the model”;
“scoring, using the discriminator parameter and a parametric function of the feature extractor parameter, a plurality of samples of a dataset of unlabeled data, the scoring resulting in a scored plurality of samples”; “selecting, for labeling, a subset of the scored plurality of samples, the selecting resulting in a selected subset of the scored plurality of samples”;
“augmenting, responsive to receiving a label of each of the selected subset of the scored plurality of samples, the first dataset of labeled data with the selected subset of the scored plurality of samples and the label of each of the selected subset of the scored plurality of samples, the augmenting resulting in an augmented dataset of labeled data” and “retraining, using the augmented dataset of labeled data, the model, wherein the retraining comprises further adjusting the feature extractor parameter of the model, the classifier parameter of the model, and the discriminator parameter of the model” under broadest reasonable interpretation covers a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper.
Step 2A Prong 2: The following limitations recite additional elements:
“a processor and one or more computer readable storage medium, …” ” amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrate by: Relevant court decision: the followings are examples of court decisions demonstrating well-understood, routine and conventional activities, see e.g., MPEP 2106.05(d)(II) and MPEP 2106.05(f)(2): Computer readable storage media comprising instructions to implement a method, e.g., see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Step 2B: Furthermore, the additional elements do not amount to significantly more than the judicial exception.
As previously discussed, the additional elements “a processor and one or more computer readable storage medium, …” amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrate by: Relevant court decision: the followings are examples of court decisions demonstrating well-understood, routine and conventional activities, see e.g., MPEP 2106.05(d)(II) and MPEP 2106.05(f)(2): Computer readable storage media comprising instructions to implement a method, e.g., see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Accordingly, the claim does not recite any additional elements that amount to significantly more than the judicial exception.
Claim 2 recites “wherein the discriminator parameter of the model is adjusted using a quantization loss of the model” amount to mathematical relationships, formulas, calculations, and optimization functions fall within the category of mathematical concepts.
Claim 3 recites “wherein scoring the plurality of samples of a dataset of unlabeled data comprises combining an uncertainty score, a diversity score and a class imbalance score of a sample in the plurality of samples” which amounts to data-gathering steps, and which is considered to be insignificant extra-solution activity, (See MPEP 2106.05(g)).
Claim 4 recites “wherein the uncertainty score is computed using a weighted sum, each addend in the weighted sum comprising an upper bound of losses incurred on an unlabeled data point divided by the number of data points belonging to a particular class of data points” amount to mathematical relationships, formulas, calculations, and optimization functions fall within the category of mathematical concepts.
Claim 5 recites “wherein the diversity score is computed using a number of data points in the first dataset of labeled data, a number of data points in the selected subset of the scored plurality of samples, and the parametric function, the parametric function quantifying how well the first dataset of labeled data represents a combined dataset, the combined dataset comprising the first dataset of labeled data and the dataset of unlabeled data” amount to mathematical relationships, formulas, calculations, and optimization functions fall within the category of mathematical concepts.
Claim 6 recites “wherein the class imbalance score is computed using a weighted sum, each addend in the weighted sum comprising a result of performing the model divided by the cube root of the number of data points belonging to a particular class of data points” amount to mathematical relationships, formulas, calculations, and optimization functions fall within the category of mathematical concepts.
Claim 7 recites “subtracting, from a query budget, a number of samples in the selected subset of the scored plurality of samples” which amounts to data-gathering steps, and which is considered to be insignificant extra-solution activity, (See MPEP 2106.05(g)).
Claim 8 recites “causing, responsive to determining that the query budget is greater than zero, labeling of the selected subset of the scored plurality of samples” which amounts to data-gathering steps, and which is considered to be insignificant extra-solution activity, (See MPEP 2106.05(g)).
Claim 10 recites “wherein the stored program instructions are transferred over a network from a remote data processing system” amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrate by: Relevant court decision: the followings are examples of court decisions demonstrating well-understood, routine and conventional activities, see e.g., MPEP 2106.05(d)(II).
Claim 11 recites “further comprising: program instructions to meter use of the program instructions associated with the request; and program instructions to generate an invoice based on the metered use” which amounts to data-gathering steps, and which is considered to be insignificant extra-solution activity, (See MPEP 2106.05(g)).
Claims 12-18 and 20 are similar in scope as claims 2-8, respectively; therefore, they are rejected under the same rationale.
Claim Rejections - 35 USC § 102
4. 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
5. Claim(s) 1, 9-11 and 19 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Jain et al. (US 2023/0267175).
Claim 1. Jain discloses a computer-implemented method comprising:
training, using a first dataset of labeled data, a model, wherein the training comprises adjusting a feature extractor parameter of the model (evaluation and potential correction), a classifier parameter of the model, and a discriminator parameter of the model ([0043]-[0044], [0048]);
scoring, using the discriminator parameter and a parametric function of the feature extractor parameter, a plurality of samples of a dataset of unlabeled data, the scoring resulting in a scored plurality of samples ([0011]-[0012]);
selecting, for labeling, a subset of the scored plurality of samples, the selecting resulting in a selected subset of the scored plurality of samples (The input dataset for each subsequent iteration may comprise an augmented set of labeled examples from the current iteration and a selected subset of unlabeled examples) ([0008]);
augmenting, responsive to receiving a label of each of the selected subset of the scored plurality of samples, the first dataset of labeled data with the selected subset of the scored plurality of samples and the label of each of the selected subset of the scored plurality of samples, the augmenting resulting in an augmented dataset of labeled data (The input dataset for each subsequent iteration may comprise an augmented set of labeled examples from the current iteration and a selected subset of unlabeled examples.) ([0008]…[0045],[0057]); and
retraining, using the augmented dataset of labeled data, the model, wherein the retraining comprises further adjusting the feature extractor parameter of the model, the classifier parameter of the model, and the discriminator parameter of the model (The set of labeled training data 52 is augmented through the successive iterations until a set of labeled training data 56 that can be used to train the ML classifier 58 is generated.) ([0045]-[0046]).
Claim 10. Jain discloses the computer program product of claim 9, wherein the stored program instructions are stored in a computer readable storage device in a data processing system, and wherein the stored program instructions are transferred over a network from a remote data processing system ([0178]).
Claim 11. Jain discloses the computer program product of claim 9, wherein the stored program instructions are stored in a computer readable storage device in a server data processing system, and wherein the stored program instructions are downloaded in response to a request over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system, further comprising: program instructions to meter use of the program instructions associated with the request ([0006]); and program instructions to generate an invoice (cost) based on the metered use ([0006]).
Claims 9 and 19 are similar in scope as claim 1; therefore, they are rejected under the same rationale.
Claim Rejections - 35 USC § 103
6. 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.
7. Claim(s) 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Jain et al. (US 2023/0267175) in view of He et al. (US 9,009,147).
Claim 7. Jain discloses the computer-implemented method of claim 1, but fails to explicitly disclose further comprising: subtracting, from a query budget, a number of samples in the selected subset of the scored plurality of samples.
However, He discloses subtracting, from a query budget, a number of samples in the selected subset of the scored plurality of samples (..subtracting f (S) from f (S, i) to obtain the marginal contribution score s (i) for the each data item i, adding to the subset S one or more of the data items i based on the marginal contribution scores for the data items i until the subset S has k data items)(claim 1). Therefore, It would have been obvious to one of ordinary skill in the art, at or before the effective filing date of the instant application, to use the feature of He in the system of Jain. One would have been motivated to find the global optimal solutions.
Claim 8. Jain and He disclose the computer-implemented method of claim 7, He further discloses comprising: causing, responsive to determining that the query budget is greater than zero, labeling of the selected subset of the scored plurality of samples (subtracting f (S) from f (S, i) to obtain the marginal contribution score s (i) for the each data item i, adding to the subset S one or more of the data items i based on the marginal contribution scores for the data items i until the subset S has k data items, and wherein said relevance/diversity score f (S) for the subset S includes a defined measure of specified similarities that each of the data items in the subset S has to one or more of others of the of data items in the subset S; and wherein at least one of said identifying and forming a subset of the data items is carried out by a computer device) (claim 1). One would have been motivated to find the global optimal solutions.
Allowable Subject Matter
8. Claims 2-6 and 12-16 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
9. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure (See PTO-892).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Phenuel S. Salomon whose telephone number is (571) 270-1699. The examiner can normally be reached on Mon-Fri 7:00 A.M. to 4:00 P.M. (Alternate Friday Off) EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Usmaan Saeed can be reached on (571) 272-4046. The fax phone number for the organization where this application or proceeding is assigned is 571-273-3800.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/PHENUEL S SALOMON/Primary Examiner, Art Unit 2146
Prosecution Insights