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 .
DETAILED ACTION
This action is responsive to the Application filed on 1/22/2024, which claims provisional application 63/480812. Claims 1-7 are pending in the case. Claim 1 is an independent claim.
Claim Rejections - 35 U.S.C. § 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 1-7 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (Step 1). If the claim does fall within one of the statutory categories, the second step in the analysis is to determine whether the claim is directed to a judicial exception (Step 2A). The Step 2A analysis is broken into two prongs. In the first prong (Step 2A, Prong 1), it is determined whether or not the claims recite a judicial exception (e.g., mathematical concepts, mental processes, certain methods of organizing human activity). If it is determined in Step 2A, Prong 1 that the claims recite a judicial exception, the analysis proceeds to the second prong (Step 2A, Prong 2), where it is determined whether or not the claims integrate the judicial exception into a practical application. If itis determined at step 2A, Prong 2 that the claims do not integrate the judicial exception into a practical application, the analysis proceeds to determining whether the claim is a patent-eligible application of the exception (Step 2B). If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim integrates the judicial exception into a practical application, or else amounts to significantly more than the abstract idea itself. Applicant is advised to consult the 2019 PEG for more details of the analysis.
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Claims 1-7 are drawn to a system, therefore each of these claim groups falls under one of four categories of statutory subject matter (machine/products/apparatus, process/method, manufactures and compositions of mater; Step 1). Nonetheless, the claims are directed to a judicially recognized exception of an abstract idea without significant more (Step 2A, see below).
As to claim 1:
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Yes, the limitation “to solve the PU problem using an adaptive asymmetric loss function whose level of asymmetry is dependent upon a learned label frequency of the input dataset, the learned label frequency learned during training such that the level of asymmetry is adaptive;” is the abstract idea of a mathematical relationship, as directed to “a mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words or using mathematical symbols”. See MPEP § 2106.04(a)(2)(I)(A).
Yes, the limitation “calculate a probability that a datapoint associated with the input dataset is labeled using the classifier as trained” is the abstract idea of a mathematical calculation, as directed to “a claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number”. See MPEP § 2106.04(a)(2)(I)(C).
Yes, the limitation “access an input dataset for classification, the input dataset limited to unlabeled data from a positive class and posing a positive and unlabeled (PU) problem”, “to solve the PU problem using an adaptive asymmetric loss function whose level of asymmetry is dependent upon a learned label frequency of the input dataset, the learned label frequency learned during training such that the level of asymmetry is adaptive” the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
No, this limitation “positive and unlabeled learning”, “train a classifier defined by a modified logistic regression (MLR) algorithm” are additional elements that amounts to adding the words “apply it” (or an equivalent) with the judicial exception and reciting only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is unclear how the “positive and unlabeled learning”, “train a classifier defined by a modified logistic regression (MLR) algorithm” are used nor the specification makes it clear how these actions are performed. Thus, these additional elements are recited in a manner that represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP § 2106.05(f) and § 2106.04(d).
No, this limitation “system”, “processor”, “memory” are additional elements that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process, and as such is deemed insufficient to transform the judicial exception to a patentable invention. See MPEP §§ 2106.04(d), 2106.05(f)(2).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considered as an ordered combination and as a whole.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
First, the additional elements directed to generally linking the use of a judicial exception to a particular technological environment or field of use are deemed insufficient to transform the judicial exception to a patentable invention because the claimed limitations generally link the judicial exception to the technology environment, see MPEP 2106.05(h). However, they are included below for the sake of completeness.
Second, the additional elements mere application of the abstract idea or mere instructions to implement an abstract idea on a computer are deemed insufficient to transform the judicial exception to a patentable invention because the limitations generally apply the use of a generic computer and/or process with the judicial exception. See MPEP 2106.05(f). However, they are included below for the sake of completeness.
No, this limitation “positive and unlabeled learning”, “train a classifier defined by a modified logistic regression (MLR) algorithm” are additional elements that amounts to adding the words “apply it” (or an equivalent) with the judicial exception and reciting only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is unclear how the “positive and unlabeled learning”, “train a classifier defined by a modified logistic regression (MLR) algorithm” are used nor the specification makes it clear how these actions are performed. Thus, these additional elements are recited in a manner that represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP § 2106.05(f) and § 2106.04(d).
No, this limitation “system”, “processor”, “memory” are additional elements that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process, and as such is deemed insufficient to transform the judicial exception to a patentable invention. See MPEP §§ 2106.04(d), 2106.05(f)(2).
Thus, considering the additional elements individually and in combination and the claims as a whole, the additional elements do not provide significantly more than the abstract idea. The claims are not eligible subject matter.
Therefore, in examining elements as recited by the limitations individually and as an ordered combination, as a whole the independent claim limitations do not recite what have the courts have identified as “significantly more”.
Furthermore, regarding dependent claims 2-7 which are dependent on claim 1, the claims are directed to a judicial exception without significantly more as highlighted below in the claim limitations by evaluating the claim limitations under Step 2A and 2B:
Dependent claim 2
Incorporates the rejection of independent claim
Step 2A Prong 1: does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1). Yes, the limitation “wherein the classifier is a non-traditional classifier defined by a modified logistic regression (MLR) algorithm” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A prong 2: the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d) No.
Step 2B: the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05. and Is the additional element recognized as well-understood, routine, and conventional? No.
Dependent claim 3
Incorporates the rejection of independent claim
Step 2A Prong 1: does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1). Yes, the limitation “wherein the adaptive asymmetric loss function is based on the structure of the input dataset” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A prong 2: the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d) No.
Step 2B: the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05. and Is the additional element recognized as well-understood, routine, and conventional? No.
Dependent claim 4
Incorporates the rejection of independent claim
Step 2A Prong 1: does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1). Yes, the limitation “determine a probability that each datapoint of the input dataset is positively labeled; and determine the learned label frequency of the input dataset.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A prong 2: the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d) No.
Step 2B: the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05. and Is the additional element recognized as well-understood, routine, and conventional? No.
Dependent claim 5
Incorporates the rejection of independent claim
Step 2A Prong 1: does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1). Incorporate the abstract idea of independent claim.
Step 2A prong 2: the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d) No, this limitation “a deep neural network” is an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception and reciting only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is unclear how the “a deep neural network” is used nor the specification makes it clear how these actions are performed. Thus, these additional elements are recited in a manner that represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP § 2106.05(f) and § 2106.04(d). This limitation “wherein the classifier incorporates an exponentiated output” amounts to mere data gathering. It is necessary to acquire the data in order to use the recited judicial exception to perform “classifier”. Therefore, the additional limitation is insignificant extra-solution activity to the judicial exception, and as such is deemed insufficient to transform the judicial exception to a patentable invention. See MPEP §§ 2106.04(d), 2106.05(g).
Step 2B: the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05. and Is the additional element recognized as well-understood, routine, and conventional? No, this limitation “a deep neural network” is an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception and reciting only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is unclear how the “a deep neural network” is used nor the specification makes it clear how these actions are performed. Thus, these additional elements are recited in a manner that represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP § 2106.05(f) and § 2106.04(d). This limitation “wherein the classifier incorporates an exponentiated output” amounts to mere data gathering. It is necessary to acquire the data in order to use the recited judicial exception to perform “classifier”. Therefore, the additional limitation is insignificant extra-solution activity to the judicial exception, and as such is deemed insufficient to transform the judicial exception to a patentable invention. See MPEP §§ 2106.04(d), 2106.05(g). Furthermore the additional element is directed to receiving or transmitting data over a network / performing repetitive calculations / electronic recordkeeping / storing and retrieving information in memory / electronically scanning or extracting data from a physical document, which the courts have recognized as well‐understood, routine, and conventional when they are claimed in a generic manner. See MPEP § 2106.05(d)(II).
Dependent claim 6
Incorporates the rejection of independent claim
Step 2A Prong 1: does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1). Yes, the limitation “wherein the processor pairs a linear transform with an output of the adaptive asymmetric loss function such that the classifier as trained is inductive and does not require an estimate of a prior class.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A prong 2: the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d) No.
Step 2B: the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05. and Is the additional element recognized as well-understood, routine, and conventional? No.
Dependent claim 7
Incorporates the rejection of independent claim
Step 2A Prong 1: does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1). Yes, the limitation “wherein the linear transform converts the classifier from a non-traditional classifier to a traditional classifier.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A prong 2: the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d) No.
Step 2B: the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05. and Is the additional element recognized as well-understood, routine, and conventional? No.
The dependent claims as analyzed above, do not recite limitations that integrated the judicial exception into a practical application. In addition, the claim limitations do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B). Therefore, the claims do not recite any limitations, when considered individually or as a whole, that recite what the courts have identified as “significantly more”, see MPEP 2106.05; and therefore, as a whole the claims are not patent eligible.
As shown above, the dependent claims do not provide any additional elements that when considered individually or as an ordered combination, amount to significantly more than the abstract idea identified. Therefore, as a whole the dependent claims do not recite what the courts have identified as “significantly more” than the recited judicial exception.
Therefore, claims 1-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception and does not recite, when claim elements are examined individually and as a whole, elements that the courts have identified as “significantly more” than the recited judicial exception.
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, 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 1-5 are rejected under 35 U.S.C. 103 as being unpatentable over “Learning From Positive and Unlabeled Data: A Survey”, Bekker et al, 5/18/2020 in view of “A MODIFIED LOGISTIC REGRESSION FOR POSITIVE AND UNLABELED LEARNING”, Jaskie et al, 2007 and in further view of “A SYMMETRICLOSSFORPOSITIVE-UNLABELEDLEARNING”, Wang et al, 2021.
Referring to claim 1, Bekker discloses a system for positive and unlabeled learning, comprising: a processor in communication with a memory, the memory including instructions executable by the processor to:
access an input dataset for classification, the input dataset limited to unlabeled data from a positive class and posing a positive and unlabeled (PU) problem; (page 7 of Bekker, input data as PU data, using unlabeled data) and
train a classifier defined by a <weighted logistic regression> algorithm to solve the PU problem using an <function> whose level of asymmetry is dependent upon a learned label frequency of the input dataset, the learned label frequency learned during training such that the level of asymmetry is adaptive; (page 6 of Bekker, input data as PU data, using unlabeled data and “The class prior α and the label frequency c are closely related to each other. Given a PU dataset, if one is known, the expected value of the other can be calculated. The label frequency is defined as the fraction of positive examples that are labeled in all the data”) and
calculate a probability that a datapoint associated with the input dataset is labeled using the classifier as trained. (page 6 of Bekker, probability of labeled data using classification)
Bekker does not specifically discloses <weighted logistic regression> being “modified logistic regression (MLR)”.
However, Jaskie discloses modified logistic regression being used for PU labeling dataset. (page 3, section 3.2 Modified logistic regression).
Bekker and Jaskie are analogous art because both references concern PU label dataset. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Bekker’s using weighted logistic regression algorithm with modified logistic regression (MLR) algorithm as taught by Jaskie. The motivation for doing so would have been being able to use different algorithms to calculate PU label training.
However, Bekker in view of Jaskie do not specifically disclose <function> being “adaptive asymmetric loss function”.
However, Wang discloses using adaptive asymmetric loss function to solve PU problem.
Bekker and Jaskie and Wang are analogous art because both references concern PU label dataset. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Bekker’s using weighted logistic regression algorithm with modified logistic regression (MLR) algorithm as taught by Jaskie and adaptive asymmetric loss function as taught by Wang. The motivation for doing so would have been being able to use different algorithms to calculate PU label training.
Referring to claim 2, Bekker in view of Jaskie and Wang disclose the system of claim 1, wherein the classifier is a non-traditional classifier defined by a modified logistic regression (MLR) algorithm. (page 23 of Bekker, weighted dataset is generated by non-traditional classifier)
Referring to claim 3, Bekker in view of Jaskie and Wang disclose the system of claim 1, wherein the adaptive asymmetric loss function is based on the structure of the input dataset. (The Specification is silent as to what is the “structure” of the input dataset, under BRI, it is interpreted as any information related to input dataset. page 12, Fig. 4 of Bekker, PU dataset is separated by a classifier related to the input dataset)
Referring to claim 4, Bekker in view of Jaskie and Wang disclose the system of claim 1, the memory further including instructions executable by the processor to: determine a probability that each datapoint of the input dataset is positively labeled; and determine the learned label frequency of the input dataset. (page 17 of Bekker, “The Positive examples and Negative examples Labeling Heuristic (PNLH)aimstoextract both reliable negative and positive examples. First, reliable negatives are extracted using features that more frequently occur in positive data. Subsequently, the sets of reliable positives and negatives are iteratively enlarged by clustering the reliable negatives. Examples that are close to the positive cluster and to no negative cluster are added to the reliable positives. Examples that are close to a negative cluster and not to the positive one are added to the reliable negatives”)
Referring to claim 5, Bekker in view of Jaskie and Wang disclose the system of claim 1, wherein the classifier incorporates an exponentiated output of a deep neural network. (page 23 of Bekker, “Empirical-Risk-Minimization based-methods, such as SVMs, logistic regression and deep networks, minimize the empirical risk,”)
Allowable Subject Matter
Claims 6 and 7 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. 101 rejections still stand.
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure:
Yadav et al (US 20200202181 A1): The technology disclosed includes a system to perform multi-label support vector machine (SVM) classification of a document. The system creates document features representing frequencies or semantics of words in the document. Trained SVM classification parameters for a plurality of labels are applied to the document features for the document. The system determines positive and negative distances between SVM hyperplanes for the labels and the feature vector. Labels with positive distance to the feature vector are harvested. When the distribution of negative distances is characterized by a mean and standard deviation, the system further harvests the labels with a negative distance such that the harvested labels include the labels with a negative distance between the mean negative distance and zero and separated from the mean negative distance by a predetermined first number of standard deviations.
Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 U.S.P.Q. 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 U.S.P.Q. 275, 277 (C.C.P.A. 1968)).
In the interests of compact prosecution, Applicant is invited to contact the examiner via electronic media pursuant to USPTO policy outlined MPEP § 502.03. All electronic communication must be authorized in writing. Applicant may wish to file an Internet Communications Authorization Form PTO/SB/439. Applicant may wish to request an interview using the Interview Practice website: http://;www.uspto.gov/patent/laws-and-regulations/interview-practice.
Applicant is reminded Internet e-mail may not be used for communication for matters under 35 U.S.C. § 132 or which otherwise require a signature. A reply to an Office action may NOT be communicated by Applicant to the USPTO via Internet e- mail. If such a reply is submitted by Applicant via Internet e-mail, a paper copy will be placed in the appropriate patent application file with an indication that the reply is NOT ENTERED. See MPEP § 502.03(II).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAIMEI JIANG whose telephone number is (571)270-1590. The examiner can normally be reached M-F 9-5pm.
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, Mariela D Reyes can be reached at 571-270-1006. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HAIMEI JIANG/Primary Examiner, Art Unit 2142
Prosecution Insights