DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This action is responsive to the following communication: Original claims filed 12/29/2022. This action is made non-final.
3. Claims 1-15 are pending in the case. Claims 1, 6 and 11 are independent claims.
Claim Rejections - 35 USC § 101
4. 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.
Claim 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claim 1 is a system type claim. Claim 11 is a non-transitory claim. Claim 16 is a method claim. Therefore, claims 1-20 are directed to either a process, machine, manufacture or composition of matter.
With respect to claim 1, 11, 13, 16:
2A Prong 1:
wherein the metric is identified by a metric identifier that is stored in association with a label identifier that identifies a label, the label indicating a source of the data value (mental process – a user can identify a metric via a label);
access a data value of the metric for which an anomaly prediction is to be made (mental process – a user can access a data value of a metric);
generate, via the plurality of models, a plurality of anomaly scores comprising at least a first anomaly score generated by the first model based on the first behavior of the historical data values of the metric and at least a second anomaly score generated by the second model based on the second behavior of the historical data values of the metric (mental process – a user can generate a plurality of scores based on an anomaly score and historical data);
generate an aggregate anomaly score based on the plurality of anomaly scores, the aggregate anomaly score representing an aggregate prediction that the data value is anomalous (mental process – a user can generate an aggregate score based on a plurality of scores);
identify a mitigative action based on the aggregate anomaly score (mental process – a user can identify a mitigative action based on a score);
perform a lookup of a stored association of a metric identifier and label identifier pair based on the metric identifier to identify a source of the data value using the metric identifier and the label identifier (mental process – a user can identify a mitigative action based on a score);
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
a plurality of machine learning models comprising at least a first model trained via a first machine learning technique to detect one or more anomalies based on a first behavior of historical data values of a metric and a second model trained via a second machine learning technique to detect the one or more anomalies based on a second behavior of the historical data values of the metric (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
a processor programmed to (mere instructions to apply the exception using a generic computer component);
provide the data value to the plurality of machine learning models (Adding insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g));
wherein each anomaly score from among the plurality of anomaly scores represents a prediction that the data value is anomalous based on a respective machine learning model that models a corresponding behavior of the historical data values of the metric; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
generate for display an indication of the mitigative action and the identified source based on the stored association (Adding insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g));
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
a plurality of machine learning models comprising at least a first model trained via a first machine learning technique to detect one or more anomalies based on a first behavior of historical data values of a metric and a second model trained via a second machine learning technique to detect the one or more anomalies based on a second behavior of the historical data values of the metric (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
a processor programmed to (mere instructions to apply the exception using a generic computer component);
provide the data value to the plurality of machine learning models (can be categorized as well understood, routine and conventional activity of “transmitting or receiving data over a network” and therefore does not provide significantly more. MPEP 2106.05(d)(ii));
wherein each anomaly score from among the plurality of anomaly scores represents a prediction that the data value is anomalous based on a respective machine learning model that models a corresponding behavior of the historical data values of the metric; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
generate for display an indication of the mitigative action and the identified source based on the stored association (can be categorized as well understood, routine and conventional activity of “transmitting or receiving data over a network” and therefore does not provide significantly more. MPEP 2106.05(d)(ii)).
With respect to claim 2, 12, 17 :
2A Prong 1:
determine a duration of time that an anomaly relating to the metric has persisted based on a prior determination that a prior data value of the metric was anomalous (mental process – a user can determine a duration of time)
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
generate a duration score based on the duration of time, wherein the aggregate anomaly score is positively correlated with the duration of time (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
generate a duration score based on the duration of time, wherein the aggregate anomaly score is positively correlated with the duration of time (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
With respect to claim 3, 14, 18:
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
wherein the plurality of machine learning models are pluggable, and wherein the processor is further programmed to: remove the second model from among the pluggable plurality of machine learning models (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
add a third model to the pluggable plurality of machine learning models to generate an updated pluggable plurality of machine learning models, the third model being trained via a third machine learning technique to detect the one or more anomalies based on a third behavior of the historical data values Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
wherein the plurality of machine learning models are pluggable, and wherein the processor is further programmed to: remove the second model from among the pluggable plurality of machine learning models (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
add a third model to the pluggable plurality of machine learning models to generate an updated pluggable plurality of machine learning models, the third model being trained via a third machine learning technique to detect the one or more anomalies based on a third behavior of the historical data values Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
With respect to claim 4, 19:
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
access a second data value for which a second anomaly prediction is to be made; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
provide the second data value to the updated pluggable plurality of machine learning models, the updated pluggable plurality of machine learning models now comprising at least the first model and the third model, but not the second model; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
generate, via the updated pluggable plurality of models, an updated plurality of anomaly scores comprising at least a first updated anomaly score generated by the first model based on the first behavior and at least a third anomaly score generated by the third model based on the third behavior, wherein each updated anomaly score from among the updated plurality of anomaly scores represents a prediction that the second data value is anomalous based on a respective behavior of the historical data values; and (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
generate a second aggregate anomaly score based on the updated plurality of anomaly scores, the second aggregate anomaly score representing an aggregate prediction that the second data value is anomalous. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
access a second data value for which a second anomaly prediction is to be made; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
provide the second data value to the updated pluggable plurality of machine learning models, the updated pluggable plurality of machine learning models now comprising at least the first model and the third model, but not the second model; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
generate, via the updated pluggable plurality of models, an updated plurality of anomaly scores comprising at least a first updated anomaly score generated by the first model based on the first behavior and at least a third anomaly score generated by the third model based on the third behavior, wherein each updated anomaly score from among the updated plurality of anomaly scores represents a prediction that the second data value is anomalous based on a respective behavior of the historical data values; and (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
generate a second aggregate anomaly score based on the updated plurality of anomaly scores, the second aggregate anomaly score representing an aggregate prediction that the second data value is anomalous. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
With respect to claim 5:
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
a seasonal and trend behavior for a time series of the historical data values, wherein the first anomaly score is based on a deviation of the data value from an upper and lower bound of the time series of the historical data values. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
a seasonal and trend behavior for a time series of the historical data values, wherein the first anomaly score is based on a deviation of the data value from an upper and lower bound of the time series of the historical data values. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
With respect to claim 6:
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
a rarest occurrence behavior modeled via robust covariance of the historical data values, wherein the second anomaly score is based on a determination of whether the data value belongs to the distribution of the historical data values. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
a rarest occurrence behavior modeled via robust covariance of the historical data values, wherein the second anomaly score is based on a determination of whether the data value belongs to the distribution of the historical data values. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
With respect to claim 7:
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
wherein the plurality of machine learning models comprises a third model that models a third behavior of the historical data values and generates a third anomaly score for the data value, the processor further programmed to: identify at least one related metric that is related to the metric; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
determine whether the data value is consistent with a combination of related historical data values of the at least one metric and the historical data values, wherein the third anomaly score is based on the determination of whether the data value is consistent with a combination of related historical data values of the at least one metric and the historical data values (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
wherein the plurality of machine learning models comprises a third model that models a third behavior of the historical data values and generates a third anomaly score for the data value, the processor further programmed to: identify at least one related metric that is related to the metric; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
determine whether the data value is consistent with a combination of related historical data values of the at least one metric and the historical data values, wherein the third anomaly score is based on the determination of whether the data value is consistent with a combination of related historical data values of the at least one metric and the historical data values (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
With respect to claim 8:
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
aggregate the first anomaly score, the second anomaly score, and the third anomaly score with a duration score to generate the aggregate anomaly score. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
aggregate the first anomaly score, the second anomaly score, and the third anomaly score with a duration score to generate the aggregate anomaly score. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
With respect to claim 9, 15:
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
normalize each of the first anomaly score, the second anomaly score, the third anomaly score, and the duration score to a common scoring scale; and (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
generate a sum of the normalized first anomaly score, the normalized second anomaly score, the normalized third anomaly score, and the normalized duration score (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
normalize each of the first anomaly score, the second anomaly score, the third anomaly score, and the duration score to a common scoring scale; and (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
generate a sum of the normalized first anomaly score, the normalized second anomaly score, the normalized third anomaly score, and the normalized duration score (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
With respect to claim 10:
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
wherein the mitigative action comprises an indication to investigate, warn, or escalate. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
wherein the mitigative action comprises an indication to investigate, warn, or escalate (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
With respect to claim 20:
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
receiving, via an input to a user interface, an indication that a third model is to be added to the plurality of machine learning models, wherein the third model is trained to learn a third behavior of the historical data values of the metric; and (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
adding the third model to the plurality of machine learning models, wherein the aggregate anomaly score is based on a third anomaly score output by the third model (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
receiving, via an input to a user interface, an indication that a third model is to be added to the plurality of machine learning models, wherein the third model is trained to learn a third behavior of the historical data values of the metric; and (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
adding the third model to the plurality of machine learning models, wherein the aggregate anomaly score is based on a third anomaly score output by the third model (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f)).
Allowable Subject Matter
5. Claims 1-20 are allowable subject matter.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID E CHOI whose telephone number is (571)270-3780. The examiner can normally be reached on M-F: 7-2, 7-10 (PST). If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bechtold, Michelle T. can be reached on (571) 431-0762. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DAVID E CHOI/Primary Examiner, Art Unit 2148