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 non-final rejection is responsive to the claims filed on 06/23rd/2025. Claims 1, 3, and 7-11 are pending. Claims 2, 4-6, and 12-18 are canceled. Claim 1 is independent. Claims 1, and 7-11 are amended.
Examiner's Note
The Examiner respectfully requests of the Applicant in preparing responses, to fully consider the entirety of the reference(s) as potentially teaching all or part of the claimed invention. It is noted, REFERENCES ARE RELEVANT AS PRIOR ART FOR ALL THEY CONTAIN. “The use of patents as references is not limited to what the patentees describe as their own inventions or to the problems with which they are concerned. They are part of the literature of the art, relevant for all they contain.” In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). A reference may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art, including non-preferred embodiments (see MPEP 2123). The Examiner has cited particular locations in the reference(s) as applied to the claim(s) above for the convenience of the Applicant. Although the specified citations are representative of the teachings of the art and are applied to the specific limitations within the individual claim(s), typically other passages and figures will apply as well.
Response to Arguments
The arguments on pages 6-21 dated 06/23/2025 with respect to the 35 U.S.C. 101 rejections set forth in the Non-Final have been fully considered but are not persuasive.
Applicant Argument #1
Similar to the claims found to be patent eligible in the "2019 Revised Patent Subject
Matter Eligibility Guidance," published by the USPTO on January 4, 2019 ("2019 Revised 101 Guidance"), claims 1, 3, and 7-11 are not directed to an abstract idea, and are allowable under 35 U.S.C. § 101. See Ex Parle Baba, Appeal 2019-000116 (PTAB Dec. 30, 2019). For at least the reasons established below, and because no federal circuit case has found such time series data processing technology as claimed, to be patent ineligible, claims 1, 3, and 7-11 are not directed to an abstract idea, and are allowable under 35 U.S.C. § 101.
Examiner Response #1
The examiner respectfully disagrees, PTAB appeal cases do not set precedence for cases under examination as individual cases are examined on their own merit and in light of their claimed invention and technological fields.
Applicant Argument #2
Claims 1, 3, and 7-11 stand rejected under 35 U.S. C. § 101 as allegedly "being directed to an abstract idea without significantly more." Applicants respectfully disagree with the Office's position.
Applicants respectfully disagree with the positions set forth by the Office, and submit that the above-noted rejections are traversed regarding claims 1, 3, and 7-11 as originally presented, and as amended herein, are also traversed in so far as the rejections are applicable to claims 1, 3, and 7-11 upon entry of the above amendments.
Examiner Response #2
The examiner respectfully disagrees. Pease review the updated 101 rejection below for analysis of the amended limitations that are analyzed as mental processes.
Applicant Argument #3
Prong 2: Claims 1, 3, and 7-11 are Not "Directed To" The Judicial Exception Because the Claimed Features are Integrated into a Practical Application that Imposes a "Meaningful Limit".
Examiner Response #3
The examiner respectfully disagrees. While the specification recites the following improvements:
[0003] “To lead a healthy life, there is a demand on predicting future health status in addition to treating current diseases. As such, there is being developed a method for predicting the health status at a future time by analyzing the development of changes in time series medical data over time”
[0044] “the time series data may include time series medical data, which are generated by diagnosis, treatment, or medication prescription at a medical institution and represent user's health status, such as an electronic medical record (EMR). For clarity of description, time series medical data are described as an example, but a kind of the time series data is not limited thereto. For example, the time series data may be generated in various fields such as entertainment, retail, and smart management”
[0056] “a prediction result at a specific future time may not be accurate due to time series irregularity and feature irregularity of time series data. Also, time series irregularity is trained through time series data collected in a real environment (e.g., a real medical treatment environment) where the time series data are measured or collected, the accuracy of prediction may decrease. Also, because prediction grounds for a prediction process are not provided, it may be difficult to determine the reliability or validity for a prediction result”
[0057] “may predict various measurement period points in time with respect to time series data with time series irregularity and feature irregularity, through measurement period division and change development modeling. Accordingly, in a data environment in which measurement period information is insufficient, the time series data processing device 100 may provide an accurate prediction result and accurate prediction grounds associated with a prediction time that the user wants”.
There is no improvement to the functioning of a computer nor to any other technology. At best, the claimed combination amounts to an improvement to the abstract idea of pre-processing time series data, learn time series irregularity of the pre-processing data, learn feature irregularity of the pre-processing data, normalize the time series data, replace a missing value of first feature data, generate mask data, calculate a period of the time series data, convert the calculated period into a minimum unit to output a measurement period, embed the plurality of feature data of the pre-processing data, divide the measurement period into a plurality of sub periods, calculate a plurality of first prediction data, estimate a first slope, calculate one prediction data, estimate a second slope, or calculate another prediction data, rather than to an improvement on the functioning of a computer or to any other technology. See MPEP 2106.05(a). Thus, even when considering the elements in combination, the claim as a whole does not integrate the recited exception into a practical application.
The arguments on pages 21-24 dated 06/23/2025 with respect to the 35 U.S.C. 103 rejections set forth in the Non-Final have been fully considered but are moot in light of the new rejection.
Claim Rejections - 35 USC § 101
101 Rejection
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, 3, and 7-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more
Step 1 Analysis for all claims:
Claims 1, 3, and 7-11 are directed to a time series processing device, which is directed to a machine, one of the statutory categories.
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 2A Prong 1 Analysis:
Claim 1 recites in part process steps which, under the broadest reasonable interpretation, are a series of mental processes including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper. If a claim, under its broadest reasonable interpretation, covers a mental process or a mathematical concept but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. The claim recites in part:
perform, by a pre-processor of the one or more processors, pre-processing on time series data to generate pre-processing data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator sorting through data readings from sensors to identify anomalies and replace them. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a pre-processor is mere instructions to implement the exception using generic computer components.
a time series irregularity learning model circuit configured to learn time series irregularity of the pre-processing data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to learn features of the sensor data, measure the time period of the sensor data, and mask missing portions from the sensor data. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a time series irregularity learning model circuit is mere instructions to implement the exception using generic computer components.
a feature irregularity learning model circuit configured to learn feature irregularity of the pre-processing data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to learn about any anomalies. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a feature irregularity learning model circuit is mere instructions to implement the exception using generic computer components.
a normalizing circuit configured to normalize the time series data to generate a plurality of feature data Under the broadest reasonable interpretation, this limitation is a process step that covers a mathematical concept that could be performed in the human mind or with the aid of pencil and paper such as an operator applying mathematical operations on sensor data to bring them within the same numerical range. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a normalizing circuit is mere instructions to implement the exception using generic computer components.
a missing value processing circuit configured to replace a missing value of first feature data of the plurality of feature data with a specific value Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to replace any missing values. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a missing value processing circuit is mere instructions to implement the exception using generic computer components.
a missing value mask generating circuit of the pre-processor configured to generate mask data based on a missing value of the plurality of feature data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to identify missing data and create masks for the missing data. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a missing value mask generating circuit of the pre-processor is mere instructions to implement the exception using generic computer components.
a measurement period calculating circuit configured to calculate a period of the time series data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to calculate a time period over which the sensor data was collected. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a measurement period calculating circuit is mere instructions to implement the exception using generic computer components.
a measurement period converting circuit configured to convert the calculated period into a minimum unit to output a measurement period Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to convert the time period unit of the sensor data to a minimum unit. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a measurement period converting circuit is mere instructions to implement the exception using generic computer components.
a time series sequence processing circuit configured to embed the plurality of feature data of the pre-processing data to output a plurality of embedding data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to quantify non-numerical values in the sensor data. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a time series sequence processing circuit is mere instructions to implement the exception using generic computer components.
a measurement period processor processing circuit configured to divide the measurement period into a plurality of sub periods Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to divide the measurement period into sub periods. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a measurement period processor processing circuit is mere instructions to implement the exception using generic computer components.
a time series calculating device circuit configured to calculate a plurality of first prediction data respectively associated with the plurality of sub periods based on first embedding data of the plurality of embedding data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to predict data for a sub period based on a quantified non-numerical data. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a time series calculating device circuit is mere instructions to implement the exception using generic computer components.
wherein the time series calculating circuit is configured to: estimate a first slope based on a first sub period of the plurality of sub periods and the first embedding data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to estimate a slope based on a sub period and a data embedding. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a time series calculating circuit is mere instructions to implement the exception using generic computer components.
wherein the time series calculating circuit is configured to: calculate one prediction data of the plurality of first prediction data based on the first slope, the first sub period, and the first embedding data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to calculate a prediction based on a slope, a sub period, and a data embedding. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a time series calculating circuit is mere instructions to implement the exception using generic computer components.
wherein the time series calculating circuit is configured to: estimate a second slope based on a second sub period of the plurality of sub periods and the one prediction data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to estimate a slope based on a sub period and a data embedding. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a time series calculating circuit is mere instructions to implement the exception using generic computer components.
wherein the time series calculating circuit is configured to: calculate another prediction data of the plurality of first prediction data based on the second slope, the second sub period, and the one prediction data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to calculate a prediction based on a slope, a sub period, and a data embedding. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a time series calculating circuit is mere instructions to implement the exception using generic computer components.
Step 2A Prong 2 Analysis:
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional element of:
A time series data processing device, comprising: one or more processors respectively comprising processing circuitry; and a memory storing code is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
create or update a feature model through machine learning by a learning circuit, for the pre-processing data is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
wherein the pre-processing data comprises the plurality of feature data, the measurement period, and the mask data is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
wherein each of the sub periods is shorter than the minimum unit is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
Step 2B Analysis:
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the additional elements of:
A time series data processing device, comprising: one or more processors respectively comprising processing circuitry; and a memory storing code is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
create or update a feature model through machine learning by a learning circuit, for the pre-processing data is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
wherein the pre-processing data comprises the plurality of feature data, the measurement period, and the mask data is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
wherein each of the sub periods is shorter than the minimum unit is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
For the reasons above, claim 1 is rejected as being directed to non-patentable subject matter under §101.
The additional limitations of the dependent claims contain no additional elements that provide a practical application or amount to significantly more than the abstract idea and are addressed briefly below.
Dependent claim 3 recites:
Step 2A Prong 2: The judicial exception is not integrated into a practical application. In particular, the additional element of:
Wherein the specific value is decided based on at least one of a value corresponding to next feature data associated with a feature corresponding to the missing value of the first feature data of the plurality of feature data, an average value, a median value, a central value, a maximum value, or a minimum value, a value based on a machine learning technique is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
Step 2B: In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
Wherein the specific value is decided based on at least one of a value corresponding to next feature data associated with a feature corresponding to the missing value of the first feature data of the plurality of feature data, an average value, a median value, a central value, a maximum value, or a minimum value, a value based on a machine learning technique is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. Furthermore, the courts have found limitations directed to linking data to a field of use, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II)).
For the reasons above, claim 3 is rejected as being directed to non-patentable subject matter under §101.
Dependent claim 7 recites:
Step 2A Prong 2: The judicial exception is not integrated into a practical application. In particular, the additional element of:
wherein the first slope and the second slope are estimated based on a neural network estimating a function of a slope of a distribution of the plurality of feature data is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Step 2B: In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
wherein the first slope and the second slope are estimated based on a neural network estimating a function of a slope of a distribution of the plurality of feature data is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
For the reasons above, claim 7 is rejected as being directed to non-patentable subject matter under §101.
Dependent claim 8 recites:
Step 2A Prong 2: The judicial exception is not integrated into a practical application. In particular, the additional element of:
Wherein the feature irregularity learning model circuit comprises: a missing value mask processing circuit configured to generate masked prediction data based on last prediction data of the plurality of first prediction data and the mask data; and a missing value replacement applying circuit configured to generate replacement data by replacing a missing value of feature data corresponding to the masked prediction data from among the plurality of feature data, based on the masked prediction data is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Step 2B: In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
Wherein the feature irregularity learning model circuit comprises: a missing value mask processing circuit configured to generate masked prediction data based on last prediction data of the plurality of first prediction data and the mask data; and a missing value replacement applying circuit configured to generate replacement data by replacing a missing value of feature data corresponding to the masked prediction data from among the plurality of feature data, based on the masked prediction data is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
For the reasons above, claim 8 is rejected as being directed to non-patentable subject matter under §101.
Dependent claim 9 recites:
Step 2A Prong 1: The judicial exception is not integrated into a practical application. In particular, the additional element of:
wherein the time series calculating circuit is further configured to: calculate a plurality of second prediction data respectively associated with the plurality of sub periods based on the replacement data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper such as an operator evaluating sensor data to calculate a prediction based on a sub period, and replacement data. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. Furthermore, the recitation of a time series calculating circuit is mere instructions to implement the exception using generic computer components.
Steps 2A Prong 2 and Step 2B:
The clam does not recite any additional elements that integrate the abstract idea into a practical application or that amount to significantly more than the abstract idea.
For the reasons above, claim 9 is rejected as being directed to non-patentable subject matter under §101.
Dependent claim 10 recites:
Step 2A Prong 2: The judicial exception is not integrated into a practical application. In particular, the additional element of:
a feature ground processing circuit is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
perform a first neural network operation on the plurality of first prediction data and the plurality of second prediction data to decide a feature weight is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
apply the feature weight to the plurality of first prediction data and the plurality of second prediction data to generate data to which the feature weight is applied is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
wherein the feature weight indicates a correlation between the plurality of feature data is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. Furthermore, the courts have found limitations directed to linking data to a field of use, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II)).
Step 2B: In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
a feature ground processing circuit is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
perform a first neural network operation on the plurality of first prediction data and the plurality of second prediction data to decide a feature weight is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
apply the feature weight to the plurality of first prediction data and the plurality of second prediction data to generate data to which the feature weight is applied is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
wherein the feature weight indicates a correlation between the plurality of feature data is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. Furthermore, the courts have found limitations directed to linking data to a field of use, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II)).
For the reasons above, claim 10 is rejected as being directed to non-patentable subject matter under §101.
Dependent claim 11 recites:
Step 2A Prong 2: The judicial exception is not integrated into a practical application. In particular, the additional element of:
a time series ground processing circuit is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
perform a second neural network operation on the plurality of first prediction data and the plurality of second prediction data to decide a time series weight is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
apply the time series weight to the plurality of first prediction data and the plurality of second prediction data to generate data to which the time series weight is applied is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
wherein the time series weight indicates a correlation associated with the period of the time series data is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. Furthermore, the courts have found limitations directed to linking data to a field of use, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II)).
Step 2B: In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
a time series ground processing circuit is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
perform a second neural network operation on the plurality of first prediction data and the plurality of second prediction data to decide a time series weight is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
apply the time series weight to the plurality of first prediction data and the plurality of second prediction data to generate data to which the time series weight is applied is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
wherein the time series weight indicates a correlation associated with the period of the time series data is recited at a high-level of generality and amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use MPEP 2106.05(h). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. Furthermore, the courts have found limitations directed to linking data to a field of use, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II)).
For the reasons above, claim 11 is rejected as being directed to non-patentable subject matter under §101.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
KURASAWA, SHAKUR, and Ding
Claims 1, 3, 6-12, and 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over US 20190228291 A1, referenced herein as KURASAWA, in view of US 20190059763 A1, referenced herein as SHAKUR, further in view of US20200380353A1, referenced herein as Ding.
Claim 1
KURASAWA teaches “A time series data processing device, comprising” ([0001], KURASAWA: “The present invention relates to a time-series-data feature extraction device”; Examiner’s Note (EN): As written and in light of the instant specification, the BRI of feature extraction is encompassed by data processing).
KURASAWA further teaches “one or more processors respectively comprising processing circuitry; and a memory storing code, which upon execution by the one or more processors, configures the one or more processors to” ([0017], KURASAWA: “program according to one aspect of the present invention is for causing a computer to function as the aforementioned time-series-data feature extraction device”; (EN): A computer is reasonably understood to comprise one or more processors which are operably coupled to memory. A program is encompassed in the BRI of code).
KURASAWA further teaches “perform, by a pre-processor of the one or more processors, pre-processing on time series data to generate pre-processing data” ([0014], KURASAWA: “a data processing unit that processes the received unevenly spaced time-series-data group into an evenly spaced time-series-data group and an omission information group based on the received input time-series data length and the received minimum observation interval”; (EN): As discussed above, as written and in light of the instant specification and the 112(f) invocations outlined above, the BRI of a pre-processor encompasses a data processing unit. Similarly, the BRI of pre-processing encompasses processing unevenly spaced data into data which has been manipulated. Thus, by teaching a data processing unit that processes time-series-data in order to generate an evenly spaced time-series-data group and an omission information group, KURASAWA teaches a pre-processor configured to perform pre-processing on time series data to generate pre-processing data).
KURASAWA further teaches “and create or update a feature model through machine learning by a learning circuit, for the pre-processing data” ([0014], KURASAWA: “and a feature extraction unit that receives time-series data [sic] of a feature extraction target, calculates a value of the intermediate layer of the model with use of the model parameter stored in the storage unit by inputting the received time-series data [sic] of the feature extraction target into the model , and outputs the calculated value of the intermediate layer as a feature that represents temporal changes in data”; (EN): With reference to the input to the model, KURASAWA discloses “a matrix obtained by combining the evenly spaced time-series-data group including omissions and the omission information group indicating presence or absence of omissions being input to the input layer” ([0014], KURASAWA). As written and in light of the instant specification and 112(f) invocations outlined above, the BRI of a feature extraction unit which utilizes a model and time-series data is encompassed by a learner configured to create or update a feature model through machine learning for the pre-processing data).
KURASAWA further teaches “wherein the learning circuit comprises: a time series irregularity learning model circuit configured to learn time series irregularity of the pre-processing data” ([0030], KURASAWA: “The training data receiving unit 11 receives (receives an input of) an unevenly spaced time-series-data group for training. The model design receiving unit 12 receives (receives an input of) a time-series data length, an observation minimum interval, and a feature extraction size. The data processing unit 13 processes the unevenly spaced time-series-data group received by the training data receiving unit 11 into an evenly spaced time-series-data group including omissions, and an omission information group indicating the presence or absence of omissions, on the basis of the input time-series data length and the received minimum observation interval received by the model design receiving unit 12”; (EN): As written and in light of the instant specification and 112(f) invocations outlined above, the BRI of a time series irregularity learning model encompasses a unit which receives information about the data set, including the time-series data, and determines time series irregularities, or omissions as taught by KURASAWA).
KURASAWA further teaches “wherein the pre-processor of the one or more processors comprises: a normalizing circuit configured to normalize the time series data to generate a plurality of feature data” ([0036], KURASAWA: “The data processing unit 13 processes the time-series data group for training into an evenly spaced time-series-data group including omissions, and an omission information group indicating the presence or absence of omissions”; (EN): As written and in light of the instant specification and 112(f) invocations outlined above, the BRI of data normalization includes any translation or modification of data to ensure it meets an outlined requirement, such as rounding or smoothing a dataset. As such, by teaching a processor which processes the time series data to produce evenly spaced data, KURASAWA tea