DETAILED ACTION
This action is in response to the national stage entry filed 27 February 2023.
Claims 1–9 are pending. Claims 1, 6, and 8 are independent.
Claims 1–9 are rejected.
Notice of Pre-AIA or AIA Status
The present application, filed on or after 16 March 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
The disclosure is objected to because of the following informalities:
Paragraphs 5, 7, and 63 recite “leaning” instead of “learning”.
Appropriate correction is required.
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 1–9 are rejected under 35 U.S.C. § 101 because the claimed inventions are directed to an abstract idea without significantly more.
Regarding independent claim 1, the eligibility analysis under the Mayo/Alice framework is as follows:
Step 1: The claim recites [a] learning device that comprises a memory storing instructions and one or more processors, which is a machine.
Step 2A, Prong One: The limitation of an extended objective function, in which each term indicative of a score of each classification result in an objective function of classification analysis is multiplied by a bias parameter as a parameter indicative of a degree of bias of the score of each classification result concerned, under its broadest reasonable interpretation in light of the specification, is a mathematical formula or equation. The limitations of optimize a logistic regression weight in the extended objective function and estimate the bias parameter […] using the extended objective function of logistic regression to which the optimized weight is set, under their broadest reasonable interpretations in light of the specification, are mathematical calculations. Therefore, the claim recites an abstract idea in the “mathematical concept” grouping. See MPEP § 2106.04(a)(2)(I)(A).
Step 2A, Prong Two: The additional elements of a memory storing instructions, one or more processors, and by inverse reinforcement learning amount to mere instructions to apply the abstract idea on a generic computer. See MPEP § 2106.05(f). The additional element of accept input [of an extended objective function] is insignificant extra-solution activity, namely mere data gathering. See MPEP § 2106.05(g). Therefore, the additional elements, taken individually or in combination, do not integrate the abstract idea into a practical application.
Step 2B: The additional elements of a memory storing instructions, one or more processors, and by inverse reinforcement learning amount to mere instructions to apply the abstract idea on a generic computer. See MPEP § 2106.05(f). The additional element of accept input [of an extended objective function] is insignificant extra-solution activity, namely mere data gathering. See MPEP § 2106.05(g). Furthermore, this is the well-understood, routine, conventional activity of receiving and/or transmitting data; see MPEP § 2106.05(d)(II), citing Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016), TLI Communications LLC v. AV Automotive, LLC, 823 F.3d 607 (Fed. Cir. 2016), OIP Technologies, Inc. v. Amazon.com, Inc., 788 F.3d 1359 (Fed. Cir. 2015), and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350 (Fed. Cir. 2014). Therefore, the additional elements, taken individually or in combination, do not result in the claim, as a whole, amounting to significantly more than the abstract idea.
Regarding dependent claim 2, the eligibility analysis under the Mayo/Alice framework is as follows:The limitation of an extended objective function, in which a term to calculate a score based on a first classification result and a term to calculate a score based on a second classification result in an objective function of binary classification analysis as the extended objective function are multiplied by bias parameters, under its broadest reasonable interpretation in light of the specification, is a mathematical formula or equation. Therefore, the claim recites further mathematical concepts. The limitation of accept input [of an extended objective function] is insignificant extra-solution activity and well-understood, routine, conventional activity [see rejection of claim 1]. Therefore, the additional element does not integrate the abstract idea into a practical application and does not result in the claim, as a whole, amounting to significantly more than the abstract idea.
Regarding dependent claim 3, the eligibility analysis under the Mayo/Alice framework is as follows:The limitation of an extended objective function, in which each term indicative of a score of each classification result in a cross entropy loss function as the extended objective function is multiplied by a bias parameter, under its broadest reasonable interpretation in light of the specification, is a mathematical formula or equation. Therefore, the claim recites further mathematical concepts. The limitation of accept input [of an extended objective function] is insignificant extra-solution activity and well-understood, routine, conventional activity [see rejection of claim 1]. Therefore, the additional element does not integrate the abstract idea into a practical application and does not result in the claim, as a whole, amounting to significantly more than the abstract idea.
Regarding dependent claim 4, the eligibility analysis under the Mayo/Alice framework is as follows:The limitation of update the logistic regression weight in the extended objective function by a gradient descent method using a partial derivative of the logistic regression weight to optimize the logistic regression weight, under its broadest reasonable interpretation in light of the specification, is a mathematical calculation. Therefore, the claim recites further mathematical concepts.
Regarding dependent claim 5, the eligibility analysis under the Mayo/Alice framework is as follows:The limitations of estimate a decision-making content from decision-making history data and estimate bias parameters […] to bring the estimated decision-making content close to the decision-making history data, under their broadest reasonable interpretations in light of the specification, are mathematical calculations. Therefore, the claim recites further mathematical concepts. Therefore, the claim recites further mathematical concepts. The limitation of by inverse reinforcement learning is a generic computer component [see rejection of claim 1]. Therefore, the additional element does not integrate the abstract idea into a practical application and does not result in the claim, as a whole, amounting to significantly more than the abstract idea.
Regarding independent claim 6, the eligibility analysis under the Mayo/Alice framework is as follows:
Step 1: The claim recites [a] learning method, which is a process.
Step 2A, Prong One: The limitation of an extended objective function, in which each term indicative of a score of each classification result in an objective function of classification analysis is multiplied by a bias parameter as a parameter indicative of a degree of bias of the score of each classification result concerned, under its broadest reasonable interpretation in light of the specification, is a mathematical formula or equation. The limitations of optimize a logistic regression weight in the extended objective function and estimate the bias parameter […] using the extended objective function of logistic regression to which the optimized weight is set, under their broadest reasonable interpretations in light of the specification, are mathematical calculations. Therefore, the claim recites an abstract idea in the “mathematical concept” grouping. See MPEP § 2106.04(a)(2)(I)(A).
Step 2A, Prong Two: The additional elements of a computer and by inverse reinforcement learning amount to mere instructions to apply the abstract idea on a generic computer. See MPEP § 2106.05(f). The additional element of accept input [of an extended objective function] is insignificant extra-solution activity, namely mere data gathering. See MPEP § 2106.05(g). Therefore, the additional elements, taken individually or in combination, do not integrate the abstract idea into a practical application.
Step 2B: The additional elements of a computer and by inverse reinforcement learning amount to mere instructions to apply the abstract idea on a generic computer. See MPEP § 2106.05(f). The additional element of accept input [of an extended objective function] is insignificant extra-solution activity, namely mere data gathering. See MPEP § 2106.05(g). Furthermore, this is the well-understood, routine, conventional activity of receiving and/or transmitting data; see MPEP § 2106.05(d)(II), citing Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016), TLI Communications LLC v. AV Automotive, LLC, 823 F.3d 607 (Fed. Cir. 2016), OIP Technologies, Inc. v. Amazon.com, Inc., 788 F.3d 1359 (Fed. Cir. 2015), and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350 (Fed. Cir. 2014). Therefore, the additional elements, taken individually or in combination, do not result in the claim, as a whole, amounting to significantly more than the abstract idea.
Regarding dependent claim 7, the eligibility analysis under the Mayo/Alice framework is as follows:The limitation of an extended objective function, in which a term to calculate a score based on a first classification result and a term to calculate a score based on a second classification result in an objective function of binary classification analysis as the extended objective function are multiplied by bias parameters, under its broadest reasonable interpretation in light of the specification, is a mathematical formula or equation. Therefore, the claim recites further mathematical concepts. The limitation of the computer is a generic computer component. The limitation of accept input [of an extended objective function] is insignificant extra-solution activity and well-understood, routine, conventional activity [see rejection of claim 1]. Therefore, the additional element does not integrate the abstract idea into a practical application and does not result in the claim, as a whole, amounting to significantly more than the abstract idea.
Regarding independent claim 8, the eligibility analysis under the Mayo/Alice framework is as follows:
Step 1: The claim recites [a] non-transitory computer readable information recording medium, which is a manufacture.
Step 2A, Prong One: The limitation of an extended objective function, in which each term indicative of a score of each classification result in an objective function of classification analysis is multiplied by a bias parameter as a parameter indicative of a degree of bias of the score of each classification result concerned, under its broadest reasonable interpretation in light of the specification, is a mathematical formula or equation. The limitations of optimization processing to optimize a logistic regression weight in the extended objective function and estimation processing to estimate the bias parameter […] using the extended objective function of logistic regression to which the optimized weight is set, under their broadest reasonable interpretations in light of the specification, are mathematical calculations. Therefore, the claim recites an abstract idea in the “mathematical concept” grouping. See MPEP § 2106.04(a)(2)(I)(A).
Step 2A, Prong Two: The additional elements of a non-transitory computer readable information recording medium and by inverse reinforcement learning amount to mere instructions to apply the abstract idea on a generic computer. See MPEP § 2106.05(f). The additional element of input processing to accept input [of an extended objective function] is insignificant extra-solution activity, namely mere data gathering. See MPEP § 2106.05(g). Therefore, the additional elements, taken individually or in combination, do not integrate the abstract idea into a practical application.
Step 2B: The additional elements of a non-transitory computer readable information recording medium and by inverse reinforcement learning amount to mere instructions to apply the abstract idea on a generic computer. See MPEP § 2106.05(f). The additional element of input processing to accept input [of an extended objective function] is insignificant extra-solution activity, namely mere data gathering. See MPEP § 2106.05(g). Furthermore, this is the well-understood, routine, conventional activity of receiving and/or transmitting data; see MPEP § 2106.05(d)(II), citing Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016), TLI Communications LLC v. AV Automotive, LLC, 823 F.3d 607 (Fed. Cir. 2016), OIP Technologies, Inc. v. Amazon.com, Inc., 788 F.3d 1359 (Fed. Cir. 2015), and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350 (Fed. Cir. 2014). Therefore, the additional elements, taken individually or in combination, do not result in the claim, as a whole, amounting to significantly more than the abstract idea.
Regarding dependent claim 9, the eligibility analysis under the Mayo/Alice framework is as follows:The limitation of an extended objective function, in which a term to calculate a score based on a first classification result and a term to calculate a score based on a second classification result in an objective function of binary classification analysis as the extended objective function are multiplied by bias parameters, under its broadest reasonable interpretation in light of the specification, is a mathematical formula or equation. Therefore, the claim recites further mathematical concepts. The limitation of the computer is a generic computer component. The limitation of input processing to accept input [of an extended objective function] is insignificant extra-solution activity and well-understood, routine, conventional activity [see rejection of claim 1]. Therefore, the additional elements do not integrate the abstract idea into a practical application and does not result in the claim, as a whole, amounting to significantly more than the abstract idea.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure.
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/Tyler Schallhorn/Examiner, Art Unit 2144
/TAMARA T KYLE/Supervisory Patent Examiner, Art Unit 2144
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