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 .
Response to Amendment
Claims 1-2 and 4-14 are amended. Claim 3 is cancelled. New grounds of rejection to claims 1-2 and 4-14 under 35 U.S.C. 101, 102, and 103 are made in light of the filed claim amendments (discussed below).
Response to Arguments
Applicant's arguments with respect to the claim objections and 35 U.S.C. 112(b) claim rejections have been fully considered and are persuasive. Therefore, the claim objections and 35 U.S.C. 112 claim rejections are withdrawn.
Applicant's arguments with respect to the 35 U.S.C. 101 claim rejections have been fully considered and are not persuasive. Applicant argues “the specification does not indicate that the claim features represent any performance in the human mind or with pen and paper” thus the claim limitations of claim 1 are allegedly “not ‘directed to’ mental processes”. Examiner respectfully disagrees. The claim limitations in at least claim 1 such as “determine an integrated score …”, “determine a determination result …”, and “determine an index value …” are recited at a high level of generality, which under the Broadest Reasonable Interpretation (BRI) consistent with the specification, are reasonably analyzed as mental processes. Further, the recitation of “a memory storing instructions” and “one or more processors connected to the memory and configured to execute the instructions” is a mere instruction to implement an abstract idea or other exception on a computer, which does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Applicant further argues that at least claim 1 is not directed to mathematical concepts. In light of the claim amendments, this argument appears persuasive. However, the analysis has been updated to indicate which limitations, which were previously analyzed as mathematical concepts, have been found to recite mental processes in light of the claim amendments. Therefore, this argument is moot.
Applicant further argues “the claim features reflect an improvement over those background deficiencies by features such as ‘determine an index value of a reliability of the integrated score based on any of history information of the integrated score and feature amounts of the elements used for determining the integrated score’”. Examiner respectfully disagrees. The portions of the claims that allegedly provide an improvement to “technical deficiencies as to the validity of [class] classification” are part of the judicial exception. For example, the limitations outlined in independent claim 1 in Step 2A Prong One of the 35 U.S.C. 101 analysis of claim 1 are determined to be mental processes. See MPEP 2106.05(a) “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements”. In claim 1, the identified additional elements recite a mere instruction to apply and the insignificant extra-solution activity of mere data gathering as discussed in the 35 U.S.C. 101 analysis below. As an ordered whole, the claim is directed to the mentally performable process of determining classifications and various scores with respect to elements in series data. Therefore, the limitations of claim 1 do not integrate the judicial exception into a practical application because they are part of the judicial exception itself, and the claim is ineligible as discussed in the 35 U.S.C. 101 analysis below.
Applicant's arguments with respect to the 35 U.S.C. 102(a)(1) claim rejections have been fully considered and are not persuasive. Applicant argues “Bhattacharya [0030] nonetheless indicates determining its alleged ‘index value of a reliability of the integrated score’ features, not based on those ‘feature vectors’ or alleged ‘feature amounts’ as claimed, but instead by comparing classification results with ground truth classifications without setting forth that those ‘feature vectors’ would be any basis of that comparison”. Examiner respectfully disagrees.
See Bhattacharya Specification [0032] “a confidence score being ‘above’ or ‘higher’ than another confidence score or the confidence threshold refers to a higher confidence or likelihood that the classification is correct. In a possible implementation, a classification score ranging from 0 to 1 can be calculated for each training sample by the current classifier, where a classification score with a greater numerical value reflects a higher confidence for a positive classification and a lower confidence for a negative classification” and Specification [0044] “Instead of inputting the raw pixel data from the endoscopic image, the first specialized network classifier inputs the output of a hidden layer of the initial trained deep network classifier as a feature vector representing the endoscopic image. The first specialized network classifier classifies the endoscopic image and determines a confidence score for its classification of the endoscopic image”. Bhattacharya discloses determining a classification score ranging from 0 to 1 foe each training example (corresponds to an index value) with respect to the confidence score of the training sample (corresponds to a reliability of the integrated score). The confidence score is determined based on inputted feature vectors representing endoscopic images. Feature amounts, under the Broadest Reasonable Interpretation (BRI) can be any value used to represent features. In this case, Bhattacharya’s feature vectors include values which are used to determine confidence scores, which are further used to determine a classification score which corresponds to and anticipates the limitation of “determine an index value of a reliability of the integrated score based on any of … feature amounts of the elements used for determining the integrated score” as discussed in the 35 U.S.C. 102(a)(1) rejection of claim 1 below. Therefore, the rejection of claims 1-2 and 3-7 under 35 U.S.C. 102(a)(1) established in the previous Office Action will not be withdrawn.
Claim Rejections - 35 USC § 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 1-2 and 4-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1,
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 1 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
determine an integrated score for binary classification of the classification target in each time one of the plurality of the elements is acquired
determine a determination result of the binary classification as a first class based on determining that the integrated score is equal to or more than an upper limit threshold value
determine the determination result as a second class based on determining that the integrated score is equal to or less than a lower limit threshold value
determine the determination result as class indetermination based on determining that the integrated score is less than the upper limit threshold value and more than the lower limit threshold value, based on comparison between the integrated score and the upper limit threshold value and the lower limit threshold value of the integrated score in each time one of the plurality of the elements is acquired
determine an index value of a reliability of the integrated score based on any of history information of the integrated score and feature amounts of the elements used for determining the integrated score
as drafted, under the broadest reasonable interpretation, covers mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
determine an integrated score for binary classification of the classification target in each time one of the plurality of the elements is acquired (corresponds to evaluation and judgment);
determine a determination result of the binary classification as a first class based on determining that the integrated score is equal to or more than an upper limit threshold value (corresponds to evaluation and judgment);
determine the determination result as a second class based on determining that the integrated score is equal to or less than a lower limit threshold value (corresponds to evaluation and judgment);
determine the determination result as class indetermination based on determining that the integrated score is less than the upper limit threshold value and more than the lower limit threshold value, based on comparison between the integrated score and the upper limit threshold value and the lower limit threshold value of the integrated score in each time one of the plurality of the elements is acquired (corresponds to evaluation and judgment);
determine an index value of a reliability of the integrated score based on any of history information of the integrated score and feature amounts of the elements used for determining the integrated score (corresponds to evaluation and judgment).
Step 2A Prong Two Analysis: This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements that amount to recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer, which do not integrate a judicial exception into a practical application. See MPEP 2106.05(f). For example, the additional element of “a memory storing instructions”, “one or more processors connected to the memory and configured to execute the instructions”, as drafted, amounts to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Moreover, the claim recites additional element(s) that amount to insignificant extra-solution activities, which do not integrate a judicial exception into a practical application. For example, the additional element of “sequentially acquire a signal indicating a plurality of elements included in series data related to a classification target” amounts to mere data gathering, which is an insignificant extra-solution activity that does not integrate a judicial exception into a practical application. See MPEP 2106.05(g). Accordingly, the 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. See MPEP 2106.04(d). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Step 2B Analysis: As discussed above with respect to integration of the abstract idea into a practical application, the claim recites additional elements that amount to recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. This has been re-evaluated under step 2B and does not amount to significantly more. See MPEP 2106.05(f). Mere instructions to apply an exception cannot provide an inventive concept. Moreover, the claim recites the additional element of “sequentially acquire a signal indicating a plurality of elements included in series data related to a classification target” that amounts to an insignificant extra-solution activity that is well-understood, routine, and conventional. This has been re-evaluated under step 2B and does not amount to significantly more. See MPEP 2106.05(d)(II) “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity…i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Intellectual Ventures v. Symantec, 838 F.3d 1307, 1321; 120 USPQ2d 1353, 1362 (Fed. Cir. 2016)”. As an ordered whole, the claim is directed to the mentally performable process of determining classifications and various scores with respect to elements in series data. Therefore, the claim is not patent eligible.
Regarding Claim 2,
Claim 2 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 2 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
perform learning of a parameter for determining the index value of the reliability
determine a feature amount of each of the plurality of the elements included in the of series data
determine the integrated score and a first score of each class based on the feature amount
perform learning of the parameter for determining the index value of the reliability of the integrated score such that the index value of the reliability is the same as or similar to a second score of a class corresponding to a correct answer among scores of respective classes by using training data in which the series data is associated with correct answer information regarding which of two classes that the classification target belongs
as drafted, under the broadest reasonable interpretation, covers mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
perform learning of a parameter for determining the index value of the reliability (corresponds to evaluation and judgment);
determine a feature amount of each of the plurality of the elements included in the of series data (corresponds to evaluation and judgment);
determine the integrated score and a first score of each class based on the feature amount (corresponds to evaluation and judgment);
perform learning of the parameter for determining the index value of the reliability of the integrated score such that the index value of the reliability is the same as or similar to a second score of a class corresponding to a correct answer among scores of respective classes by using training data in which the series data is associated with correct answer information regarding which of two classes that the classification target belongs (corresponds to evaluation and judgment).
Step 2A Prong Two Analysis: This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements that amount to recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer, which do not integrate a judicial exception into a practical application. See MPEP 2106.05(f). For example, the additional element of “the one or more processors are configured to further execute the instructions”, as drafted, amounts to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, the 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. See MPEP 2106.04(d). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Step 2B Analysis: As discussed above with respect to integration of the abstract idea into a practical application, the claim recites additional elements that amount to recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. This has been re-evaluated under step 2B and does not amount to significantly more. See MPEP 2106.05(f). Mere instructions to apply an exception cannot provide an inventive concept. Therefore, the claim is not patent eligible.
Regarding Claim 4,
Claim 4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 4 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
determine a determination result of the binary classification as one of two classes or class indetermination based on comparison between the integrated score and upper and lower limit threshold values of the integrated score and the reliability
as drafted, under the broadest reasonable interpretation, covers mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
determine a determination result of the binary classification as one of two classes or class indetermination based on comparison between the integrated score and upper and lower limit threshold values of the integrated score and the reliability (corresponds to evaluation and judgment).
Step 2A Prong Two Analysis: This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements that amount to recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer, which do not integrate a judicial exception into a practical application. See MPEP 2106.05(f). For example, the additional element of “the one or more processors are configured to further execute the instructions”, as drafted, amounts to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, the 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. See MPEP 2106.04(d). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Step 2B Analysis: As discussed above with respect to integration of the abstract idea into a practical application, the claim recites additional elements that amount to recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. This has been re-evaluated under step 2B and does not amount to significantly more. See MPEP 2106.05(f). Mere instructions to apply an exception cannot provide an inventive concept. Therefore, the claim is not patent eligible.
Regarding Claim 5,
Claim 5 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 5 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
determine a class of the classification target as a third class based on determining that a predetermined end condition is established and the integrated score is less than the upper limit threshold value and more than the lower limit threshold value
as drafted, under the broadest reasonable interpretation, covers mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
determine a class of the classification target as a third class based on determining that a predetermined end condition is established and the integrated score is less than the upper limit threshold value and more than the lower limit threshold value (corresponds to evaluation and judgment).
Step 2A Prong Two Analysis: This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements that amount to recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer, which do not integrate a judicial exception into a practical application. See MPEP 2106.05(f). For example, the additional element of “the one or more processors are configured to further execute the instructions”, as drafted, amounts to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, the 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. See MPEP 2106.04(d). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Step 2B Analysis: As discussed above with respect to integration of the abstract idea into a practical application, the claim recites additional elements that amount to recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. This has been re-evaluated under step 2B and does not amount to significantly more. See MPEP 2106.05(f). Mere instructions to apply an exception cannot provide an inventive concept. Therefore, the claim is not patent eligible.
Regarding Claim 6,
Claim 6 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 6 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
determining an integrated score for binary classification of the classification target each time one of the plurality of the elements is acquired
determining a determination result of the binary classification as a first class based on determining that the integrated score is equal to or more than an upper limit threshold value
determining the determination result as a second class based on determining that the integrated score is equal to or less than the lower limit threshold value
determining the determination result as class indetermination based on determining that the integrated score is less than the upper limit threshold value and more than the lower limit threshold value, on the basis of comparison between the integrated score and the upper limit threshold value and the lower limit threshold value each time one of the elements is acquired
determining an index value of a reliability of the integrated score based on history information of the integrated score or feature amounts of the elements used for determining the integrated score
as drafted, under the broadest reasonable interpretation, covers mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
determining an integrated score for binary classification of the classification target each time one of the plurality of the elements is acquired (corresponds to evaluation and judgment);
determining a determination result of the binary classification as a first class based on determining that the integrated score is equal to or more than an upper limit threshold value (corresponds to evaluation and judgment);
determining the determination result as a second class based on determining that the integrated score is equal to or less than the lower limit threshold value (corresponds to evaluation and judgment);
determining the determination result as class indetermination based on determining that the integrated score is less than the upper limit threshold value and more than the lower limit threshold value, on the basis of comparison between the integrated score and the upper limit threshold value and the lower limit threshold value each time one of the elements is acquired (corresponds to evaluation and judgment);
determining an index value of a reliability of the integrated score based on history information of the integrated score or feature amounts of the elements used for determining the integrated score (corresponds to evaluation and judgment).
Step 2A Prong Two Analysis: This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements that amount to insignificant extra-solution activities, which do not integrate a judicial exception into a practical application. For example, the additional element of “sequentially acquiring a signal indicating a plurality of elements included in series data related to a classification target” amounts to mere data gathering, which is an insignificant extra-solution activity that does not integrate a judicial exception into a practical application. See MPEP 2106.05(g). Accordingly, the 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. See MPEP 2106.04(d). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Step 2B Analysis: As discussed above with respect to integration of the abstract idea into a practical application, the claim recites the additional element of “sequentially acquiring a signal indicating a plurality of elements included in series data related to a classification target” that amounts to an insignificant extra-solution activity that is well-understood, routine, and conventional. This has been re-evaluated under step 2B and does not amount to significantly more. See MPEP 2106.05(d)(II) “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity…i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Intellectual Ventures v. Symantec, 838 F.3d 1307, 1321; 120 USPQ2d 1353, 1362 (Fed. Cir. 2016)”. As an ordered whole, the claim is directed to the mentally performable process of determining classifications and various scores with respect to elements in series data. Therefore, the claim is not patent eligible.
Regarding Claim 7,
Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 7 is directed to a medium, which is directed to a manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
determining an integrated score for binary classification of the classification target in each time one of the elements is acquired
determining a determination result of the binary classification as a first class based on determining that the integrated score is equal to or more than the upper limit threshold value
determining the determination result as a second class based on determining that the integrated score is equal to or less than the lower limit threshold value
determining the determination result as class indetermination based on determining that the integrated score is less than the upper limit threshold value and more than the lower limit threshold value, based on comparison between the integrated score and the upper limit threshold value and the lower limit threshold value each time one of the elements is acquired
determining an index value of a reliability of the integrated score on the basis of history information of the integrated score or feature amounts of the elements used for calculating the integrated score
as drafted, under the broadest reasonable interpretation, covers mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) and/or mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
determining an integrated score for binary classification of the classification target in each time one of the elements is acquired (corresponds to evaluation and judgment);
determining a determination result of the binary classification as a first class based on determining that the integrated score is equal to or more than the upper limit threshold value (corresponds to evaluation and judgment);
determining the determination result as a second class based on determining that the integrated score is equal to or less than the lower limit threshold value (corresponds to evaluation and judgment);
determining the determination result as class indetermination based on determining that the integrated score is less than the upper limit threshold value and more than the lower limit threshold value, based on comparison between the integrated score and the upper limit threshold value and the lower limit threshold value each time one of the elements is acquired (corresponds to evaluation and judgment);
determining an index value of a reliability of the integrated score on the basis of history information of the integrated score or feature amounts of the elements used for calculating the integrated score (corresponds to evaluation and judgment).
Step 2A Prong Two Analysis: This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements that amount to recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer, which do not integrate a judicial exception into a practical application. See MPEP 2106.05(f). For example, the additional element of “A non-transitory recording medium storing a program causing a computer to execute”, as drafted, amounts to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Moreover, the claim recites additional element(s) that amount to insignificant extra-solution activities, which do not integrate a judicial exception into a practical application. For example, the additional element of “sequentially acquiring a signal indicating a plurality of elements included in series data related to a classification target” amounts to mere data gathering, which is an insignificant extra-solution activity that does not integrate a judicial exception into a practical application. See MPEP 2106.05(g). Accordingly, the 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. See MPEP 2106.04(d). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Step 2B Analysis: As discussed above with respect to integration of the abstract idea into a practical application, the claim recites additional elements that amount to recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. This has been re-evaluated under step 2B and does not amount to significantly more. See MPEP 2106.05(f). Mere instructions to apply an exception cannot provide an inventive concept. Moreover, the claim recites the additional element of “sequentially acquiring a signal indicating a plurality of elements included in series data related to a classification target” that amounts to an insignificant extra-solution activity that is well-understood, routine, and conventional. This has been re-evaluated under step 2B and does not amount to significantly more. See MPEP 2106.05(d)(II) “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity…i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Intellectual Ventures v. Symantec, 838 F.3d 1307, 1321; 120 USPQ2d 1353, 1362 (Fed. Cir. 2016)”. As an ordered whole, the claim is directed to the mentally performable process of determining classifications and various scores with respect to elements in series data. Therefore, the claim is not patent eligible.
Regarding Claim 8,
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 8 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
the index value of the reliability of the integrated score includes at least one of a standard deviation of the integrated score, a variance of the integrated score, a reciprocal of the standard deviation, and a reciprocal of the variance
as drafted, under the broadest reasonable interpretation, covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
the index value of the reliability of the integrated score includes at least one of a standard deviation of the integrated score, a variance of the integrated score, a reciprocal of the standard deviation, and a reciprocal of the variance (corresponds to mathematical calculations).
Step 2A Prong Two Analysis: See corresponding analysis of claim 1.
Step 2B Analysis: See corresponding analysis of claim 1.
Regarding Claim 9,
Claim 9 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 9 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
the index value of the reliability of the integrated score includes a standard deviation of the integrated score
as drafted, under the broadest reasonable interpretation, covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
the index value of the reliability of the integrated score includes a standard deviation of the integrated score (corresponds to mathematical calculations).
Step 2A Prong Two Analysis: See corresponding analysis of claim 1.
Step 2B Analysis: See corresponding analysis of claim 1.
Regarding Claim 10,
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 10 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
the index value of the reliability of the integrated score includes a variance of the integrated score
as drafted, under the broadest reasonable interpretation, covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
the index value of the reliability of the integrated score includes a variance of the integrated score (corresponds to mathematical calculations).
Step 2A Prong Two Analysis: See corresponding analysis of claim 1.
Step 2B Analysis: See corresponding analysis of claim 1.
Regarding Claim 11,
Claim 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 11 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
the index value of the reliability of the integrated score includes a reciprocal of a standard deviation of the integrated score
as drafted, under the broadest reasonable interpretation, covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
the index value of the reliability of the integrated score includes a reciprocal of a standard deviation of the integrated score (corresponds to mathematical calculations).
Step 2A Prong Two Analysis: See corresponding analysis of claim 1.
Step 2B Analysis: See corresponding analysis of claim 1.
Regarding Claim 12,
Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 12 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The following limitation:
the index value of the reliability of the integrated score includes a reciprocal of a variance of the integrated score
as drafted, under the broadest reasonable interpretation, covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) but for the recitation of mere instructions to apply an exception language and insignificant extra-solution activity language. In particular, the above limitation in the context of this claim encompasses:
the index value of the reliability of the integrated score includes a reciprocal of a variance of the integrated score (corresponds to mathematical calculations).
Step 2A Prong Two Analysis: See corresponding analysis of claim 1.
Step 2B Analysis: See corresponding analysis of claim 1.
Regarding Claim 13,
Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 13 is directed to a device, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements that amount to insignificant extra-solution activities, which do not integrate a judicial exception into a practical application. For example, the additional element of “the series data includes a moving image, and the plurality of the elements includes a frame of the moving image, and wherein sequentially acquiring includes sequentially acquiring the plurality of elements” amounts to mere data gathering, which is an insignificant extra-solution activity that does not integrate a judicial exception into a practical application. See MPEP 2106.05(g). Accordingly, the 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. See MPEP 2106.04(d). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Step 2B Analysis: As discussed above with respect to integration of the abstract idea into a practical application, the claim recites additional element of “the series data includes a moving image, and the plurality of the elements includes a frame of the moving image, and wherein sequentially acquiring includes sequentially acquiring the plurality of elements” which amounts to an insignificant extra-solution activity that is well-understood, routine, and conventional. This has been re-evaluated under step 2B and does not amount to significantly more. See MPEP 2106.05(d)(II) “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity…i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Intellectual Ventures v. Symantec, 838 F.3d 1307, 1321; 120 USPQ2d 1353, 1362 (Fed. Cir. 2016)”. Therefore, the claim is not patent eligible.
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 1-2, 4-7, and 13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bhattacharya et al. (WO 2017055412 A1 (Published 2017); hereinafter Bhattacharya).
Regarding Claim 1,
Bhattacharya discloses a determination device comprising:
a memory storing instructions (Bhattacharya Specification [0063] “The computer program instructions may be stored in a storage device 912 (e.g., magnetic disk) and loaded into memory 910 when execution of the computer program instructions is desired”; discloses a memory storing instructions); and
one or more processors connected to the memory and configured to execute the instructions (Bhattacharya Specification [0063] “the computer program instructions stored in the memory 910 and/or storage 912 and controlled by the processor 904 executing the computer program instructions”; discloses a processor executing program instructions in memory (corresponds to one or more processors connected to the memory and configured to execute the instructions)) to:
sequentially acquire a signal indicating a plurality of elements included in series data related to a classification target (Bhattacharya Specification [0007] “a plurality of endoscopic images are received. Each of the plurality of endoscopic images is classified and a confidence score is determined for each of the plurality of endoscopic images using an initial trained deep network classifier”; Specification [0040] “The endoscopic image can be a frame of a video acquired by the endoscopic probe. In this case, the endoscopic image is one of a plurality of endoscopic images in a stream of endoscopic images”; discloses receiving a plurality of endoscopic images in a stream of images (corresponds to sequentially acquire a signal indicating a plurality of elements included in series data) where the endoscopic images are being classified by a trained deep network classifier (corresponds to related to a classification target));
determine an integrated score for binary classification of the classification target each time one of the plurality of the elements is acquired (Bhattacharya Specification [0027] “The training data is a set of endoscopic images with known classifications, including a set of positive training samples and a set of negative training samples”; Specification [0032] “a confidence score being "above" or "higher" than another confidence score or the confidence threshold refers to a higher confidence or likelihood that the classification is correct. In a possible implementation, a classification score ranging from 0 to 1 can be calculated for each training sample by the current classifier”; Specification [0041] “The initial trained deep network classifier can perform a binary classification that classifies the endoscopic image into one of two classes, such as positive or negative”; discloses calculating a confidence score (corresponds to determine an integrated score) which determines a positive or negative confidence in a binary classification (corresponds to binary classification of the classification target). A score is calculated for each training sample of the classifier (corresponds to each time one of the plurality of the elements is acquired));
determine a determination result of the binary classification as a first class based on determining that the integrated score is equal to or more than the upper limit threshold value (Bhattacharya Specification [0032] “the classification score can be used as the confidence score for all training samples, … an upper threshold being defined above which no positively classified training samples in the validation dataset were incorrectly classified as negative”; discloses a classification score being higher than an upper threshold (corresponds to based on determining that the integrated score is equal to or more than the upper limit threshold value) which indicates no positively classified training samples were incorrectly classified as negative (corresponds to determine a determination result of the binary classification as a first class)), determine the determination result as a second class based on determining that the integrated score is equal to or less than a lower limit threshold value (Bhattacharya Specification [0032] “the classification score can be used as the confidence score for all training samples, with a lower threshold being defined below which no negatively classified training samples in the validation dataset were incorrectly classified as positive”; discloses a classification score being lower than a lower threshold (corresponds to based on determining that the integrated score is equal to or less than a lower limit threshold value) which indicates no negatively classified training samples were incorrectly classified as positive (corresponds to determine the determination result as a second class)), and determine the determination result as class indetermination based on determining that the integrated score is less than the upper limit threshold value and more than the lower limit threshold value, based on comparison between the integrated score and the upper limit threshold value and the lower limit threshold value of the integrated score in each time one of the plurality of the elements is acquired (Bhattacharya Specification [0033] “samples classified with classification scores between the thresholds 508 and 510 are considered low confidence (confused) samples”; Specification [0032] “a classification score ranging from 0 to 1 can be calculated for each training sample by the current classifier”; discloses a case where a classification score is between two thresholds (corresponds to based on determining that the integrated score is less than the upper limit threshold value and more than the lower limit threshold value, based on comparison between the integrated score and the upper limit threshold value and the lower limit threshold value of the integrated score). This calculation of classification score is performed for each training sample (corresponds to each time one of the plurality of the elements is acquired). Samples with a classification score that falls between the upper and lower thresholds are considered “confused” samples where the confidence is low for the classification of a particular sample (corresponds to determine the determination result as class indetermination)); and
determine an index value of a reliability of the integrated score based on any of history information of the integrated score and feature amounts1 of the elements used for determining the integrated score (Bhattacharya Specification [0032] “a confidence score being ‘above’ or ‘higher’ than another confidence score or the confidence threshold refers to a higher confidence or likelihood that the classification is correct. In a possible implementation, a classification score ranging from 0 to 1 can be calculated for each training sample by the current classifier, where a classification score with a greater numerical value reflects a higher confidence for a positive classification and a lower confidence for a negative classification”; Specification [0044] “the first specialized network classifier inputs the output of a hidden layer of the initial trained deep network classifier as a feature vector representing the endoscopic image. The first specialized network classifier classifies the endoscopic image and determines a confidence score for its classification of the endoscopic image”; discloses a classification score being calculated for each training sample ranging from 0 to 1 (corresponds to determine an index value of a reliability of the integrated score). The confidence score for determining a classification score is calculated on the basis of a generated feature vector representing an endoscopic image where a feature vector would represent “amounts” or values of a particular endoscopic image (corresponds to based on any of … feature amounts of the elements used for determining the integrated score)).
Regarding Claim 2,
Bhattacharya discloses the determination device according to claim 1 and further teaches wherein the one or more processors are configured to further execute the instructions to:
perform learning of a parameter for determining the index value of the reliability (Bhattacharya Specification [0042] “the confidence score calculated for the endoscopic image is compared with a learned confidence threshold. As described in connection with step 408 of FIG. 4, the learned confidence threshold is learned in the training phase by determining a confidence score threshold above which there are no confusion cases (i.e., no incorrect classifications in a set of training samples)”; discloses learning a confidence threshold used to compare a confidence score which is used for determining a reliability as a confidence represented by a value between 0 and 1 (corresponds to perform learning of a parameter for determining the index value of the reliability; for more on the confidence score please see Bhattacharya Specification [0032]));
determine a feature amount of each of the plurality of the elements included in the series data (Bhattacharya Specification [0044] “the endoscopic image is classified by a subsequent specialized network classifier … the first specialized network classifier inputs the output of a hidden layer of the initial trained deep network classifier as a feature vector representing the endoscopic image”; Specification [0048] “the method of FIG. 6 classifies all of the endoscopic images with the initial trained deep classifier, compares a confidence score calculated by the initial trained deep classifier for each endoscopic image with a learned confidence threshold”; discloses generating feature vectors representing an endoscopic image for each image which is used for calculating confidence scores (corresponds to determine a feature amount of each of the plurality of the elements included in the series data));
determine the integrated score and a first score of each class based on the feature amount (Bhattacharya Specification [0044] “the endoscopic image is classified by a subsequent specialized network classifier … the first specialized network classifier inputs the output of a hidden layer of the initial trained deep network classifier as a feature vector representing the endoscopic image”; Specification [0048] “the method of FIG. 6 classifies all of the endoscopic images with the initial trained deep classifier, compares a confidence score calculated by the initial trained deep classifier for each endoscopic image with a learned confidence threshold”; discloses generating feature vectors (corresponds to the feature amount) representing an endoscopic image for each image which is used for calculating confidence scores which indicate a confidence of a particular image belonging to a positive or negative class (corresponds to determine the integrated score and a first score of each class based on the feature amount; for more please see Bhattacharya Specification [0032])); and
perform learning of the parameter for determining the index value of the reliability of the integrated score such that the index value of the reliability is the same as or similar to a second score of a class corresponding to a correct answer among scores of respective classes by using training data in which the series data is associated with correct answer information regarding which of two classes that the classification target belongs (Bhattacharya Specification [0042] “the confidence score calculated for the endoscopic image is compared with a learned confidence threshold. As described in connection with step 408 of FIG. 4, the learned confidence threshold is learned in the training phase by determining a confidence score threshold above which there are no confusion cases (i.e., no incorrect classifications in a set of training samples)”; discloses learning a confidence threshold used to compare a confidence score which is used for determining a reliability as a confidence represented by a value between 0 and 1 (corresponds to perform learning of a parameter for determining the index value of the reliability of the integrated score). Bhattacharya Specification [0032] “a classification score ranging from 0 to 1 can be calculated for each training sample by the current classifier, where a classification score with a greater numerical value reflects a higher confidence for a positive classification and a lower confidence for a negative classification, and a classification score with a smaller numerical value reflects a higher confidence for a negative classification and a lower confidence for a positive classification”; Specification [0030] “The classification results for the training samples in the validation dataset are compared with the ground truth classifications for the training samples in the validation dataset to determine which training samples in the validation dataset have been incorrectly classified. The confidence scores calculated for the incorrectly classified training samples in the validation dataset provide a range of confidence scores at which incorrect classification occurred in the current classification stage”; discloses a classification score which indicates whether a particular training sample reflects a negative classification or a positive classification (corresponds to the same as or similar to a second score of a class corresponding to a correct answer among scores of respective classes by using training data). The classification of training samples if compared with ground truth classifications (corresponds to correct answer information) which indicates whether a particular training sample was correctly classified and a confidence score is calculated (corresponds to series data is associated with correct answer information regarding which of two classes that the classification target belongs)).
Regarding Claim 4,
Bhattacharya discloses the determination device according to claim 1, and further teaches wherein the one or more processors are configured to further execute the instructions to determine the determination result of the binary classification as one of two classes or class indetermination based on comparison between the integrated score and upper and lower limit threshold values of the integrated score and the reliability (Bhattacharya Specification [0032] “the classification score can be used as the confidence score for all training samples, with a lower threshold being defined below which no negatively classified training samples in the validation dataset were incorrectly classified as positive and an upper threshold being defined above which no positively classified training samples in the validation dataset were incorrectly classified as negative”; Bhattacharya Specification [0033] “samples classified with classification scores between the thresholds 508 and 510 are considered low confidence (confused) samples”; Specification [0032] “a classification score ranging from 0 to 1 can be calculated for each training sample by the current classifier”; as discussed above in claim 1, Bhattacharya discloses comparing a classification score of training samples to an upper threshold and lower threshold where a value below the lower threshold is defined as no negatively classified training sample was incorrectly classified and positive (corresponds to the binary classification as one of two classes), a value above the upper threshold is defined as no positively classified training sample was incorrectly classified as negative (corresponds to the binary classification as one of two classes), and a value between the two threshold is considered a low confidence or “confused” sample effectively indicating a low reliability of classification (corresponds to class indetermination based on comparison between the integrated score and upper and lower limit threshold values of the integrated score and the reliability)).
Regarding Claim 5,
Bhattacharya discloses the determination device according to claim 1, and further teaches wherein the one or more processors are configured to further execute the instructions to determine a class of the classification target as a third class based on determining that a predetermined end condition is established and the integrated score is less than the upper limit threshold value and more than the lower limit threshold value Bhattacharya Specification [0033] “samples classified with classification scores between the thresholds 508 and 510 are considered low confidence (confused) samples”; Specification [0025] “The classification of a large number of samples (endoscopic images) by the initial deep network 310 results in a set of highly confident samples from class A, a set of highly confident samples from class B, and set of samples with low confidence, which are referred to herein as the confused samples”; Specification [0032] “a classification score ranging from 0 to 1 can be calculated for each training sample by the current classifier”; discloses samples with classification scores falling between the upper and lower thresholds as low confidence or “confused” samples effectively indicating that the reliability of classification is low (corresponds to determining that a predetermined end condition is established and the integrated score is less than the upper limit threshold value and more than the lower limit threshold value). This classification of a “confused” sample acts as a third class (corresponds to determine a class of the classification target as a third class)).
Regarding Claim 6,
Claim 6 is substantially similar in scope to claim 1, and is rejected on the same grounds as claim 1. Per claim 6, Bhattacharya discloses a determination method (Bhattacharya Specification [0005] “The present disclosure provides a method and system for classifying endoscopic images using a deep decision network”; discloses a determination method).
Regarding Claim 7,
Claim 7 is substantially similar in scope to claim 1, and is rejected on the same grounds as claim 1. Per claim 7, Bhattacharya discloses a non-transitory recording medium storing a program (Bhattacharya Specification [0063] “The computer program instructions may be stored in a storage device 912 (e.g., magnetic disk) and loaded into memory 910 when execution of the computer program instructions is desired”; discloses a non-transitory recording medium storing a program).
Regarding Claim 13,
Bhattacharya discloses the determination device according to claim 1, wherein the series data includes a moving image, and the plurality of the elements includes a frame of the moving image, and wherein sequentially acquiring includes sequentially acquiring the plurality of the elements (Bhattacharya Specification [0040] “The endoscopic image can be a frame of a video acquired by the endoscopic probe. In this case, the endoscopic image is one of a plurality of endoscopic images in a stream of endoscopic images. In one embodiment, endoscopic images are received from the endoscopic probe in real time as the endoscopic images are acquired and the endoscopic images are classified in real time using the trained deep decision network”; discloses a stream of endoscopic images made up of frames of video acquired by an endoscopic probe (corresponds to the series data includes a moving image, and the plurality of the elements includes a frame of the moving image) where the endoscopic images are sequentially acquired frames of real time video captured by the endoscopic probe (corresponds to sequentially acquiring includes sequentially acquiring the plurality of elements)).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 8-12 are rejected under 35 U.S.C. 103 as being unpatentable over Bhattacharya et al. (WO 2017055412 A1 (Published 2017); hereinafter Bhattacharya) in view of Sumi et al. (US 20190129026 A1 (Published 2019); hereinafter Sumi).
Regarding Claim 8,
Bhattacharya discloses the determination device according to claim 1, but appears to not disclose explicitly the limitations of claim 8.
However, Sumi teaches the index value of the reliability of the integrated score includes at least one of a standard deviation of the integrated score, a variance of the integrated score, a reciprocal of the standard deviation, and a reciprocal of the variance (Sumi Specification [0624] “The standard deviations or variances of the observation objects can be estimated by establishing the error model (standard deviation or variance) of the sensing signals themselves to be directly observed as well as the respective observation objects (strain tensor, temperature, current density vector, respective physical properties, etc.), which were used for increasing the measurement accuracies … the reciprocals of standard deviations or variances were used for weighting the confidence of respective equations comprising a system of equations about the spatio-temporal distributions of various observation objects such as a displacement vector”; discloses determining standard deviation and variance of observation objects which used to weight confidence of a system of equations for objects such as a vector (corresponds to the index value of the reliability of the integrated score). In this case, standard deviation, variance, and the reciprocals of both standard deviation and variance are used (corresponds to at least one of at least one of a standard deviation of the integrated score, a variance of the integrated score, a reciprocal of the standard deviation, and a reciprocal of the variance)).
Bhattacharya and Sumi are considered to be analogous to the claimed invention because they are in the same field of utilizing machine learning methods in image processing. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bhattacharya to incorporate the teachings of Sumi. Doing so would assist in statistically determining the confidence or reliability of equations used for image processing in Bhattacharya, as suggested by Sumi (Sumi [0624] “The standard deviations or variances of the observation objects can be estimated by establishing the error model … which were used for increasing the measurement accuracies”; Specification [0732] “When the displacement measurement includes errors caused by the above phase errors, the estimation errors also occur”).
Regarding Claim 9,
Claim 9 is substantially similar in scope to claim 8, therefore claim 9 is rejected on the same grounds as claim 8 applying the teachings of Bhattacharya in view of Sumi as discussed in the 35 U.S.C. 103 rejection of claim 8.
Regarding Claim 10,
Claim 10 is substantially similar in scope to claim 8, therefore claim 10 is rejected on the same grounds as claim 8 applying the teachings of Bhattacharya in view of Sumi as discussed in the 35 U.S.C. 103 rejection of claim 8.
Regarding Claim 11,
Claim 11 is substantially similar in scope to claim 8, therefore claim 11 is rejected on the same grounds as claim 8 applying the teachings of Bhattacharya in view of Sumi as discussed in the 35 U.S.C. 103 rejection of claim 8.
Regarding Claim 12,
Claim 12 is substantially similar in scope to claim 8, therefore claim 12 is rejected on the same grounds as claim 8 applying the teachings of Bhattacharya in view of Sumi as discussed in the 35 U.S.C. 103 rejection of claim 8.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Bhattacharya et al. (WO 2017055412 A1 (Published 2017); hereinafter Bhattacharya) in view of Pal et al. (US 20190220438 A1 (Published 2019); hereinafter Pal).
Regarding Claim 14,
Bhattacharya discloses the determination device according to claim 1, but appears to not disclose explicitly the limitations of claim 14.
However, Pal teaches determining the index value of the reliability of the integrated score is based on at least the history information of the integrated score (Pal Specification [0037] “a confidence score can be based on history data indicating user activity. The history data may describe a number of times a user has selected a particular application, or a number of times the user has selected a particular application in association with a particular keyword”; discloses calculating a confidence score (corresponds to determining the index value of the reliability) by considering history data of a user’s activity which includes a number indicating a number of time the user has selected an application (corresponds to the integrated score is based on at least the history information of the integrated score)).
Bhattacharya and Pal are considered to be analogous to the claimed invention because they are in the same field of utilizing machine learning models. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bhattacharya to incorporate the teachings of Pal. Doing so could better assist in calculating confidence scores for input data for models in Bhattacharya by taking historical data into consideration, as suggested by Pal (Pal Specification [0037] “machine learning algorithms can be utilized to determine a confidence score for each individual application. The individual applications can be ranked based on a confidence score”).
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.
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/KAMRAN AFSHAR/Supervisory Patent Examiner, Art Unit 2125
1 Under the broadest reasonable interpretation (BRI), “feature amounts” can be any values indicating features, e.g., a feature vector.
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