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 .
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 1,3,6-12,15,16,18-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) mental processes – concepts performed in the human mind and mathematical concepts..
Regarding claim 1, with the exception of the recitation of the limitations ‘processing circuitry; memory coupled to the processing circuitry and having instruction stored therein that are executable by the processing circuitry’, the claim recites concepts performed in the human mind.
The limitations ‘determining a plurality of categories associated with a plurality of features of the ML model, wherein the plurality of features include input data associated with performance of a communications network and the issue associated with the label generated by the ML model includes an issue in the communications network; determining a causality relationship between each category of the plurality of categories; determining data associated with each feature of the plurality of features’ are mental processes performed by observation, evaluation, judgement, and/or opinion. The limitation ‘determining the root cause of the issue using a model explainer with ordering constraints based on the causality relationship between each category of the plurality of categories, wherein determining the root cause of the issue comprises using an asymmetric Shapley Additive Explanation (SHAP) procedure as the model explainer with ordering constraints based the causality relationship between each category of the plurality of categories rather than between individual features of the plurality of features of the ML model, thereby reducing computational complexity and improving scalability for RCA in a communications network’ is using math, as disclosed throughout the specification, to determine the root cause.
Step 2A: Prong two
This judicial exception is not integrated into a practical application because the additional element ‘performing an action associated with the issue based on the root cause of the issue’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements ‘processing circuitry; memory coupled to the processing circuitry and having instruction stored therein that are executable by the processing circuitry; via a network interface’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instruction to apply the exception using generic computer components (MPEP 2106.05(f)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements ‘wherein performing the action comprises transmitting instructions to a network node to identified based on the root cause to change a configuration management (CM) parameter associated with antenna configuration, spectrum allocation, or cell dimensioning’ are simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, MPEP 2106.05(d). TW201351910A - Conventional approaches are time consuming and not suitable for dynamically changing antenna configuration parameters in order to react, for example, to channel environment changes, flow load changes, or other changes.; JPH1135531A - However, in the conventional wireless communication network system, when the base station is defective (failure or the like), the cell configuration is changed, or the communication service time is changed, the entire system is stopped. There is a problem that the priority table needs to be changed.
Regarding claim 3, the limitation ‘determining a label based on the data using the ML model; and determining the issue based on the label’ are mental processes performed by observation, evaluation, judgement, and/or opinion.
Regarding claim 6, the limitation ‘wherein the network node comprises at least one of: a core network (CN) node; a radio access network (RAN) node; a RAN controller; and an orchestrator’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instruction to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 7, the limitation ‘performing the action comprises: outputting an indication to a network operator, the indication comprising at least one of: a latent feature of the communications network that had at least a threshold impact on the issue; a suggested reconfiguration of the communications network; and an amount that a feature of the plurality of features affected the issue’ is merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Regarding claim 8, the limitation ‘performing the action comprises: requesting additional data associated with a specific feature of the communications network’ is merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Regarding claim 9, the limitation ‘determining the data comprises at least one of: measuring the data; and receiving the data from a network node of the communications network’ is merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Regarding claim 10, the limitation ‘the plurality of features comprise at least one of: an input performance management (PM) metric associated with an activity of a communication device in the communications network; a configuration management (CM) metric associated with a parameter of the communications network; and a latent parameter that is not currently measured’ are mental processes performed by observation, evaluation, judgement, and/or opinion.
Regarding claim 11, the limitation ‘the input PM metric comprises at least one of: service consumption; traffic generated; mobility; cell load; radio quality; and service performance, wherein the CM metric comprises at least one of: spectrum; antenna configuration; and cell dimensioning, and wherein the latent parameter comprises at least one of: a licensed measurement report; and a third party data service’ are mental processes performed by observation, evaluation, judgement, and/or opinion.
Regarding claim 12, the claim recites concepts performed in the human mind.
The limitations ‘determining an issue in a communication network associated with a label of the ML model based on input data associated with performance of the communication network; determining a plurality of categories associated with a plurality of features of the ML model; determining a causality relationship between each category of the plurality of categories’ are mental processes performed by observation, evaluation, judgement, and/or opinion. The limitation ‘determining a root cause of the issue based on the causality relationship between each category of the plurality of categories, wherein determining the root cause of the issue comprises using an asymmetric Shapley Additive Explanation (SHAP) procedure as the model explainer with ordering constraints based on the causality relationship between each category of the plurality of categories rather than between individual features of the plurality of features of the ML model, thereby reducing computational complexity and improving scalability for RCA in a communications network’ is using math, as disclosed throughout the specification, to determine the root cause.
Step 2A: Prong two
This judicial exception is not integrated into a practical application because the additional element ‘performing an action associated with the issue based on the root cause of the issue’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements ‘via a network interface’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instruction to apply the exception using generic computer components (MPEP 2106.05(f)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements ‘wherein performing the action comprises transmitting instructions to a network node to identified based on the root cause to change a configuration management (CM) parameter associated with antenna configuration, spectrum allocation, or cell dimensioning’ are simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, MPEP 2106.05(d). TW201351910A - Conventional approaches are time consuming and not suitable for dynamically changing antenna configuration parameters in order to react, for example, to channel environment changes, flow load changes, or other changes.; JPH1135531A - However, in the conventional wireless communication network system, when the base station is defective (failure or the like), the cell configuration is changed, or the communication service time is changed, the entire system is stopped. There is a problem that the priority table needs to be changed.
Regarding claim 15, the limitation ‘the ML model is configured to evaluate the communications network, wherein the plurality of features comprise at least one of: a performance management (PM) metric associated with an activity of a communication device in the communications network; a configuration management (CM) metric associated with a parameter of the communications network; and a latent parameter that is not currently measured’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instruction to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 16, the limitation ‘the PM metric comprises at least one of: service consumption; traffic generated; mobility; cell load; radio quality; and service performance, wherein the CM metric comprises at least one of: spectrum; antenna configuration; and cell dimensioning, and wherein the latent parameter comprises at least one of: a licensed measurement report; and a third party data service’ are mental processes performed by observation, evaluation, judgement, and/or opinion.
Regarding claim 18, the limitation ‘performing the action comprises outputting an indication of at least one of: a latent feature that had at least a threshold impact on the label; a reconfiguration suggestion based on the root cause; and an amount that a feature affected the label’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g))..
Regarding claim 19, the limitation ‘performing the action comprises adjusting a type of input data used by the ML model’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Regarding claim 20, with the exception of the recitation of the limitations ‘A non-transitory computer readable medium having instructions stored therein that are executable by a system’, the claim recites concepts performed in the human mind.
The limitations ‘determining an issue in a communications network associated with a label of a machine learning (ML) model based on input data associated with performance of the communications network; determining a plurality of categories associated with a plurality of features of the ML model; determining a causality relationship between each category of the plurality of categories’ are mental processes performed by observation, evaluation, judgement, and/or opinion. The limitation ‘determining a root cause of the issue based on the causality relationship between each category of the plurality of categorizes, wherein determining the root cause of the issue comprises using an asymmetric Shapley Additive Explanation (SHAP) procedure as the model explainer with ordering constraints based on the causality relationship between each category of the plurality of categories rather than between individual features of the plurality of features of the ML model, thereby reducing computational complexity and improving scalability for RCA in a communications network’ is using math, as disclosed throughout the specification, to determine the root cause.
Step 2A: Prong two
This judicial exception is not integrated into a practical application because the additional element ‘A non-transitory computer readable medium having instructions stored therein that are executable by a system; via a network interface’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instruction to apply the exception using generic computer components (MPEP 2106.05(f)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional element ‘performing an action based on the root cause of the issue; measuring, after the change, at least one performance management (PM) metric associated with the issue; transmitting, via the network interface, instructions to further modify the CM parameter based on the at least one PM metric and the root cause’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements ‘wherein performing the action comprises transmitting instructions to a network node to identified based on the root cause to change a configuration management (CM) parameter associated with antenna configuration, spectrum allocation, or cell dimensioning’ are simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, MPEP 2106.05(d). TW201351910A - Conventional approaches are time consuming and not suitable for dynamically changing antenna configuration parameters in order to react, for example, to channel environment changes, flow load changes, or other changes.; JPH1135531A - However, in the conventional wireless communication network system, when the base station is defective (failure or the like), the cell configuration is changed, or the communication service time is changed, the entire system is stopped. There is a problem that the priority table needs to be changed.
Regarding claim 21, the limitations ‘wherein determining the root cause of the issue using the asymmetric SHAP procedure as the model explainer with ordering constraints comprises: defining a causality graph that specifies causal relationships between the categories; training a plurality of predictive models, wherein each model is trained using a different subset of the categories, the subsets being determined based on the causal relationships in the causality graph; and determining a root cause contribution for each category by aggregating outputs from the plurality of predictive models’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instruction to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 22, the limitations ‘wherein determining the root cause of the issue using the asymmetric SHAP procedure as the model explainer with ordering constraints comprises: defining a causality graph that specifies causal relationships between the categories; training a plurality of predictive models, wherein each model is trained using a different subset of the categories, the subsets being determined based on the causal relationships in the causality graph; and determining a root cause contribution for each category by aggregating outputs from the plurality of predictive models’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instruction to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 23, the limitations ‘wherein determining the root cause of the issue using the asymmetric SHAP procedure as the model explainer with ordering constraints comprises: defining a causality graph that specifies causal relationships between the categories; training a plurality of predictive models, wherein each model is trained using a different subset of the categories, the subsets being determined based on the causal relationships in the causality graph; and determining a root cause contribution for each category by aggregating outputs from the plurality of predictive models’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instruction to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 24, the limitations ‘wherein performing the action further comprises: measuring, after the change, at least one performance management (PM) metric associated with the issue’; and transmitting, via the network interface, instructions to further modify the CM parameter based on the at least one PM metric and the root cause’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Regarding claim 25, the limitations ‘wherein performing the action further comprises: measuring, after the change, at least one performance management (PM) metric associated with the issue’; and transmitting, via the network interface, instructions to further modify the CM parameter based on the at least one PM metric and the root cause’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Regarding claim 26, the limitations ‘wherein performing the action further comprises: measuring, after the change, at least one performance management (PM) metric associated with the issue’; and transmitting, via the network interface, instructions to further modify the CM parameter based on the at least one PM metric and the root cause’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Response to Arguments
Applicant's arguments and amendment filed 03/20/2026 have been fully considered. The 101 rejection still stands. Concerning Applicant’s argument of the 101 rejection, as disclosed above the limitation "determining a causality relationship between each category of the plurality of categories" is capable of being a mental process performed by observation, evaluation, judgement, and/or opinion. There is only an indication of being performed by generic computer components. This is a clear sign of automating a mental process. The limitation "determining the root cause of the issue using a model explainer with ordering constraints based on the causality relationship between each category of the plurality of categories" involves an asymmetric Shapley Additive Explanation (SHAP) procedure which is mathematical as disclosed in paragraphs 0033-0037, 0076-0077, which cite calculus being used. As indicated in example 47 – claim 2 the claim was found to be ineligible because the algorithms for the artificial neural network, the backpropagation algorithm and gradient optimization algorithm, are mathematical calculations. The limitation "determining data associated with each feature of the plurality of features" is merely choosing the data associated with each feature which is a mental process performed by observation, evaluation, judgement, and/or opinion There is only an indication of being performed by generic computer components. This is a clear sign of automating a mental process.
The claim as a whole has no additional limitations that would result in the claim being eligible. Please see the above rejection as to how the limitations are rejected. Although the argument “Additionally, independent claim 1 identifies one of the improvements, reciting, "thereby reducing computational complexity and improving scalability for RCA in a communications network" is citing an improvement. However, it does not overcome the fact that the type of algorithm used for the machine learning model to determine a root cause is mathematical.
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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/Yolanda L Wilson/Primary Examiner, Art Unit 2113
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