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 § 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.
Claim(s) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over US 20230308930 A1 to Xin et al. (“Xin”) in view of US 20210019652 A1 to Gadelrab et al. (“Gadelrab”).
Regarding claim 1, Xin taught a data processing method, comprising:
sending, by a first network element (“PCF” via the “NWDAF”), a federated inference request message (“request” “to subscribe to” “a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model”; consider at least paragraph 0171) to at least one second network element (“terminals of the service A” with “domains”) when performing a federated inference process corresponding to a first inference task, wherein the federated inference request message comprises at least information related to the first inference task, and the second network element is a network element participating in the federated inference process; (consider paragraphs 0168-0171, specifically “The PCF sends a request #1 to the NWDAF, to subscribe to, from the NWDAF, a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model” wherein “The Nnwdaf_AnalyticsSubscription_Subscribe service operation includes, for example, the following information: Analytics ID=Service Experience, indicating the PCF to subscribe to a data analysis result of a service experience type from the NWDAF, where Analytics ID is further used to determine a service experience model used to generate the service experience data analysis result; Analytics Filter, indicating filtering information of a to-be-requested service experience data analysis result, for example, an Application ID indicating a service identifier of a service; and Target of Analytics Reporting, indicating an object of a to-be-requested model inference result, for example, an SUPI indicating a terminal identifier of the terminal” and also “the request is a service model inference result request for one or some terminals of the service A, or is a service model inference result request for all terminals of the service A”) (consider further paragraphs 0180 and 0185-0189 regarding the “NWDAF sends a request to each domain, to request a model inference result” “for the service A” wherein the request “includes the following content: a first identifier of the terminal and at least one of the following information: an analysis identifier and identification information of a first model, where the analysis identifier and/or the identification information of the first model is for determining a model used by the terminal for service experience model inference on the core network device” wherein “Specifically, in at least one embodiment, the NWDAF triggers an Nnf_AnalyticsSubscription_Subscribe service operation to the 5GC NF to subscribe to the model inference result of service experience of the terminal for the service A in the core network domain from the CN. The service operation includes a terminal identifier, for example, an SUPI or a GPSI, and model identification information of the service A, for example, one or more of a Model ID, an IP address, a URL, and an FQDN”)
receiving, by the first network element, first information sent by the at least one second network element, wherein the first information comprises at least one first inference result; (consider at least paragraphs 0201 and 0206-2017, specifically “Each domain receives the subscription request of the NWDAF, generates a local model inference result of the terminal in each domain for the service A, and sends a response to the NWDAF, where the response includes the local model inference result in each domain.”) (consider further paragraphs 0218-0221, specifically “The NWDAF receives the response information, and determines a model inference result of service experience data of the terminal for the service A in each domain” wherein “the RAN, the CN, and the AF all report a model inference result and association information of each terminal in each domain to the NWDAF. Based on the association information reported from each domain, the NWDAF aggregates model inference results of each terminal in the RAN domain, the CN domain, and the AF domain”) (consider further paragraphs 0236-0237 wherein “The NWDAF sends a response #4 to the PCF. The response #4 is used by the NWDAF to send a service experience data analysis result of the terminal, namely, the foregoing model inference result, to the PCF”) and
determining, by the first network element based on the at least one first inference result, a second inference result corresponding to the first inference task. (consider paragraphs 0240-0241 wherein “The PCF receives the response #4 and determines the QoS parameter. In at least one embodiment, the PCF calculates a new QoS parameter of the service A based on response information d. As described above, the PCF calculates the QoS parameter based on a service model inference result of the terminal and a service experience requirement through a multi-criteria decision-making algorithm.”)
Xiu may be interpreted as not expressly teaching wherein the federated inference request message comprises: information related to a first filter, used for limiting inference sample information corresponding to the first inference task, wherein the inference sample information comprises at least one of inference object information, inference time information, and inference area information.
However, in an analogous art relating to inference requests and processing such requests, Gadelrab taught wherein a federated inference request message may comprise information related to a first filter, used for limiting inference sample information corresponding to a first inference task, wherein the inference sample information comprises at least one of inference object information, inference time information, and inference area information. (consider paragraphs 0055-0056, “[0055] As illustrated, operations 300 begin at block 302, where the computing device receives a request to perform inferences on a data set using the machine learning model and performance metric targets for performance of the inferences. [0056] The performance metric targets may define, for example, an accuracy of inferences performed using the machine learning model, an execution time for performance of an inference, an amount of power consumed to perform an inference, an amount of memory consumed to perform an inference, an amount of data transferred during performance of an inference, and other metrics.”) (consider further paragraph 0085, specifically “By performing an inference using predefined operational parameters, inference process 502 can generate an initial inference within a latency value specifying a maximum amount of time that may elapse between receipt of inference request 512 and the performance of the first inference. Meanwhile, using information about the properties of the machine learning model used by inference process 502 and information about the current operational state of the computing device on which inference process 502 is executing (e.g., current processor speed, thermal limits, current draw, memory latency, cache occupancy, etc.), optimizer process 504 can generate an optimized set of parameters for the machine learning model that results in performance approaching a target set of performance metrics defined for inference operations. The target set of performance metrics may be defined as part of inference request 512 and may define, for example, that an inference should be performed within a specified amount of time, that an inference should be performed using a maximum amount of power, that an inference should result in a given amount of accuracy, and other metrics.”)
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to combine the teachings of these references such that their combination includes every element as claimed. One skilled in the art could have combined the teachings by known methods such as integration of software routines with no changes to the operation of either reference such that, in combination, each element merely performs the same function as it does separately. Additionally, Examiner finds that, based on the references' analogous disclosure regarding inference requests and processing such requests, further demonstrates that a combination of their features would have been known and obvious. Therefore, such a combination of the teachings of the references would have yielded nothing more than predictable results to one of ordinary skill in the art.
Regarding claim 2, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 1.
Xin further taught wherein before the sending a federated inference request message to at least one second network element, the method further comprises:
determining, by the first network element, a first condition is met, wherein the first condition comprises at least one of the following:
the first network element does not store or cannot obtain all or a part of inference data corresponding to the inference process; the at least one second network element can provide all or a part of the inference data corresponding to the inference process; or samples of inference data between second network elements required by the inference task are the same, but sample features are different. (again, consider paragraphs 0168-0171, specifically “The PCF sends a request #1 to the NWDAF, to subscribe to, from the NWDAF, a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model” wherein “the request is a service model inference result request for one or some terminals of the service A, or is a service model inference result request for all terminals of the service A”) (consider further paragraphs 0180 and 0185-0189 regarding the “NWDAF sends a request to each domain, to request a model inference result” “for the service A”)
Regarding claim 3, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 1.
Xin further taught wherein the federated inference request message further comprises at least one of the following:
model instance identification information, used for identifying a target model required by the federated inference process; identification information of the first inference task; first indication information, used for indicating that the federated inference process is a vertical federated inference process; or reporting information corresponding to the first inference result. (consider paragraphs 0168-0171, specifically “The PCF sends a request #1 to the NWDAF, to subscribe to, from the NWDAF, a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model” wherein “The Nnwdaf_AnalyticsSubscription_Subscribe service operation includes, for example, the following information: Analytics ID=Service Experience, indicating the PCF to subscribe to a data analysis result of a service experience type from the NWDAF, where Analytics ID is further used to determine a service experience model used to generate the service experience data analysis result; Analytics Filter, indicating filtering information of a to-be-requested service experience data analysis result, for example, an Application ID indicating a service identifier of a service; and Target of Analytics Reporting, indicating an object of a to-be-requested model inference result, for example, an SUPI indicating a terminal identifier of the terminal” and also “the request is a service model inference result request for one or some terminals of the service A, or is a service model inference result request for all terminals of the service A”) (consider further paragraphs 0180 and 0185-0189 regarding the “NWDAF sends a request to each domain, to request a model inference result” “for the service A” wherein the request “includes the following content: a first identifier of the terminal and at least one of the following information: an analysis identifier and identification information of a first model, where the analysis identifier and/or the identification information of the first model is for determining a model used by the terminal for service experience model inference on the core network device” wherein “Specifically, in at least one embodiment, the NWDAF triggers an Nnf_AnalyticsSubscription_Subscribe service operation to the 5GC NF to subscribe to the model inference result of service experience of the terminal for the service A in the core network domain from the CN. The service operation includes a terminal identifier, for example, an SUPI or a GPSI, and model identification information of the service A, for example, one or more of a Model ID, an IP address, a URL, and an FQDN”)
Regarding claim 4, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 3.
Xin further taught wherein the reporting information corresponding to the first inference result comprises at least one of the following:
a reporting format of the first inference result; or a reporting condition of the first inference result. (consider paragraphs 0168-0171, specifically “The PCF sends a request #1 to the NWDAF, to subscribe to, from the NWDAF, a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model” wherein “The Nnwdaf_AnalyticsSubscription_Subscribe service operation includes, for example, the following information: Analytics ID=Service Experience, indicating the PCF to subscribe to a data analysis result of a service experience type from the NWDAF, where Analytics ID is further used to determine a service experience model used to generate the service experience data analysis result; Analytics Filter, indicating filtering information of a to-be-requested service experience data analysis result, for example, an Application ID indicating a service identifier of a service; and Target of Analytics Reporting, indicating an object of a to-be-requested model inference result, for example, an SUPI indicating a terminal identifier of the terminal” and also “the request is a service model inference result request for one or some terminals of the service A, or is a service model inference result request for all terminals of the service A”)
Regarding claim 5, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 1.
Xin further taught wherein the first inference result is obtained by the second network element through inference based on a local inference model, and the local inference model is determined by the second network element based on model instance identification information comprised in the federated inference request message. (consider further paragraphs 0180 and 0185-0189 regarding the “NWDAF sends a request to each domain, to request a model inference result” “for the service A” wherein the request “includes the following content: a first identifier of the terminal and at least one of the following information: an analysis identifier and identification information of a first model, where the analysis identifier and/or the identification information of the first model is for determining a model used by the terminal for service experience model inference on the core network device” wherein “Specifically, in at least one embodiment, the NWDAF triggers an Nnf_AnalyticsSubscription_Subscribe service operation to the 5GC NF to subscribe to the model inference result of service experience of the terminal for the service A in the core network domain from the CN. The service operation includes a terminal identifier, for example, an SUPI or a GPSI, and model identification information of the service A, for example, one or more of a Model ID, an IP address, a URL, and an FQDN”) (consider also paragraphs 0201 and 0206-2017, specifically “Each domain receives the subscription request of the NWDAF, generates a local model inference result of the terminal in each domain for the service A, and sends a response to the NWDAF, where the response includes the local model inference result in each domain.”)
Regarding claim 6, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 1.
Xin further taught wherein the first information further comprises at least one of the following:
model instance identification information, used for identifying a target model required by the federated inference process; identification information of the first inference task; or the inference sample information. (consider paragraphs 0168-0171, specifically “The PCF sends a request #1 to the NWDAF, to subscribe to, from the NWDAF, a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model” wherein “The Nnwdaf_AnalyticsSubscription_Subscribe service operation includes, for example, the following information: Analytics ID=Service Experience, indicating the PCF to subscribe to a data analysis result of a service experience type from the NWDAF, where Analytics ID is further used to determine a service experience model used to generate the service experience data analysis result; Analytics Filter, indicating filtering information of a to-be-requested service experience data analysis result, for example, an Application ID indicating a service identifier of a service; and Target of Analytics Reporting, indicating an object of a to-be-requested model inference result, for example, an SUPI indicating a terminal identifier of the terminal” and also “the request is a service model inference result request for one or some terminals of the service A, or is a service model inference result request for all terminals of the service A”) (consider further paragraphs 0180 and 0185-0189 regarding the “NWDAF sends a request to each domain, to request a model inference result” “for the service A” wherein the request “includes the following content: a first identifier of the terminal and at least one of the following information: an analysis identifier and identification information of a first model, where the analysis identifier and/or the identification information of the first model is for determining a model used by the terminal for service experience model inference on the core network device” wherein “Specifically, in at least one embodiment, the NWDAF triggers an Nnf_AnalyticsSubscription_Subscribe service operation to the 5GC NF to subscribe to the model inference result of service experience of the terminal for the service A in the core network domain from the CN. The service operation includes a terminal identifier, for example, an SUPI or a GPSI, and model identification information of the service A, for example, one or more of a Model ID, an IP address, a URL, and an FQDN”)
Regarding claim 7, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 1.
Xin further taught wherein the step of determining, by the first network element based on the at least one first inference result, a second inference result corresponding to the first inference task comprises:
calculating, by the first network element, the second inference result based on a target model and the at least one first inference result. (consider paragraphs 0240-0241 wherein “The PCF receives the response #4 and determines the QoS parameter. In at least one embodiment, the PCF calculates a new QoS parameter of the service A based on response information d. As described above, the PCF calculates the QoS parameter based on a service model inference result of the terminal and a service experience requirement through a multi-criteria decision-making algorithm.”)
Regarding claim 8, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 7.
Xin further taught wherein the step of calculating, by the first network element, the second inference result based on the target model and the at least one first inference result comprises:
associating and aligning, by the first network element based on the inference sample information corresponding to the first inference result, the first inference result that is sent by the at least one second network element and corresponds to an inference sample; and inputting, by the first network element, the first inference result corresponding to the inference sample into the target model to obtain the second inference result corresponding to the inference sample. (consider paragraphs 0149-0153 wherein “at least one embodiment provides a communication method, to enable a service provider to update a local parameter based on a model inference result of service experience of the network side or a service requirement” including wherein “service experience or service flow experience model parameters is first obtained based on the foregoing vertical federated training model. An NWDAF or a PCF (namely, an example of a first network device) obtains a model inference result (namely, an example of an analysis result) of a terminal for private data (namely, an example of first data) of the service or the service flow in each domain. For example, the first network device obtains a model inference result of service experience (namely, an example of a first analysis result) of the terminal for the service or the service flow in a CN domain (namely, an example of a second network device), a model inference result of service experience (namely, an example of a second analysis result) in a RAN domain (namely, an example of a third network device), or a model inference result of service experience (namely, an example of a third analysis result) in an AF domain (namely, an example of a fourth network device). The PCF network element then determines a value relationship between the model inference result of service experience and a service experience requirement or a service flow experience requirement (namely, an example of second service experience information) (consider further paragraphs 0227-0228 wherein “in response to each domain sending public data, the NWDAF performs inference on the public data. For example, in at least one embodiment, in response to each domain sending public data, in at least one embodiment, the NWDAF associates the public data of the terminal in the core network domain and the public data of the terminal in the access network domain based on the association information between the RAN and the AMF, for example, x.sub.i.sup.D. The NWDAF then determines an inference result θ.sub.Dx.sub.i.sup.D of the public data based on a local model parameter θ.sub.D.” or, alternatively, “he NWDAF associates the public data of the terminal in the core network domain and the public data of the terminal in the access network domain based on the association information between the RAN and the AMF, and further associates the public data of the terminal in the core network domain and the public data of the terminal in the AF domain based on the association information between the UPF and the AF, to finally obtain the public data of the terminal in each domain, for example, x.sub.i.sup.D. The NWDAF then determines the inference result θ.sub.Dx.sub.i.sup.D of the public data based on the local model parameter θ.sub.D.”) (consider also further paragraphs 0323-0324 regarding the “calculation” of a “new QoS parameter” “based on the model inference result of service experience of the terminal and a service experience requirement through the multi-criteria decision-making algorithm”)
Regarding claim 9, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 1.
Xin further taught wherein the method is further comprising:
sending, by the first network element, a model request message to a third network element, wherein the model request message is used for requesting the third network element to train or feedback the target model; and receiving, by the first network element, information related to the target model sent by the third network element, wherein the information related to the target model comprises at least information of the target model. (again, consider paragraphs 0168-0171, specifically “The PCF sends a request #1 to the NWDAF, to subscribe to, from the NWDAF, a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model” wherein “the request is a service model inference result request for one or some terminals of the service A, or is a service model inference result request for all terminals of the service A”) (consider further paragraphs 0180 and 0185-0189 regarding the “NWDAF sends a request to each domain, to request a model inference result” “for the service A”)
Regarding claim 10, Xin taught a data processing method, comprising:
receiving, by a second network element, a federated inference request message sent by a first network element, wherein the federated inference request message comprises at least information related to a first inference task; (consider paragraphs 0168-0171, specifically “The PCF sends a request #1 to the NWDAF, to subscribe to, from the NWDAF, a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model” wherein “The Nnwdaf_AnalyticsSubscription_Subscribe service operation includes, for example, the following information: Analytics ID=Service Experience, indicating the PCF to subscribe to a data analysis result of a service experience type from the NWDAF, where Analytics ID is further used to determine a service experience model used to generate the service experience data analysis result; Analytics Filter, indicating filtering information of a to-be-requested service experience data analysis result, for example, an Application ID indicating a service identifier of a service; and Target of Analytics Reporting, indicating an object of a to-be-requested model inference result, for example, an SUPI indicating a terminal identifier of the terminal” and also “the request is a service model inference result request for one or some terminals of the service A, or is a service model inference result request for all terminals of the service A”) (consider further paragraphs 0180 and 0185-0189 regarding the “NWDAF sends a request to each domain, to request a model inference result” “for the service A” wherein the request “includes the following content: a first identifier of the terminal and at least one of the following information: an analysis identifier and identification information of a first model, where the analysis identifier and/or the identification information of the first model is for determining a model used by the terminal for service experience model inference on the core network device” wherein “Specifically, in at least one embodiment, the NWDAF triggers an Nnf_AnalyticsSubscription_Subscribe service operation to the 5GC NF to subscribe to the model inference result of service experience of the terminal for the service A in the core network domain from the CN. The service operation includes a terminal identifier, for example, an SUPI or a GPSI, and model identification information of the service A, for example, one or more of a Model ID, an IP address, a URL, and an FQDN”)
performing, by the second network element, inference based on the federated inference request message to obtain a first inference result; and sending, by the second network element, first information to the first network element, wherein the first information comprises at least the first inference result. (consider at least paragraphs 0201 and 0206-2017, specifically “Each domain receives the subscription request of the NWDAF, generates a local model inference result of the terminal in each domain for the service A, and sends a response to the NWDAF, where the response includes the local model inference result in each domain.”) (consider further paragraphs 0218-0221, specifically “The NWDAF receives the response information, and determines a model inference result of service experience data of the terminal for the service A in each domain” wherein “the RAN, the CN, and the AF all report a model inference result and association information of each terminal in each domain to the NWDAF. Based on the association information reported from each domain, the NWDAF aggregates model inference results of each terminal in the RAN domain, the CN domain, and the AF domain”) (consider further paragraphs 0236-0237 wherein “The NWDAF sends a response #4 to the PCF. The response #4 is used by the NWDAF to send a service experience data analysis result of the terminal, namely, the foregoing model inference result, to the PCF”)
Xiu may be interpreted as not expressly teaching wherein the federated inference request message comprises: information related to a first filter, used for limiting inference sample information corresponding to the first inference task, wherein the inference sample information comprises at least one of inference object information, inference time information, and inference area information.
However, in an analogous art relating to inference requests and processing such requests, Gadelrab taught wherein a federated inference request message may comprise information related to a first filter, used for limiting inference sample information corresponding to a first inference task, wherein the inference sample information comprises at least one of inference object information, inference time information, and inference area information. (consider paragraphs 0055-0056, “[0055] As illustrated, operations 300 begin at block 302, where the computing device receives a request to perform inferences on a data set using the machine learning model and performance metric targets for performance of the inferences. [0056] The performance metric targets may define, for example, an accuracy of inferences performed using the machine learning model, an execution time for performance of an inference, an amount of power consumed to perform an inference, an amount of memory consumed to perform an inference, an amount of data transferred during performance of an inference, and other metrics.”) (consider further paragraph 0085, specifically “By performing an inference using predefined operational parameters, inference process 502 can generate an initial inference within a latency value specifying a maximum amount of time that may elapse between receipt of inference request 512 and the performance of the first inference. Meanwhile, using information about the properties of the machine learning model used by inference process 502 and information about the current operational state of the computing device on which inference process 502 is executing (e.g., current processor speed, thermal limits, current draw, memory latency, cache occupancy, etc.), optimizer process 504 can generate an optimized set of parameters for the machine learning model that results in performance approaching a target set of performance metrics defined for inference operations. The target set of performance metrics may be defined as part of inference request 512 and may define, for example, that an inference should be performed within a specified amount of time, that an inference should be performed using a maximum amount of power, that an inference should result in a given amount of accuracy, and other metrics.”)
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to combine the teachings of these references such that their combination includes every element as claimed. One skilled in the art could have combined the teachings by known methods such as integration of software routines with no changes to the operation of either reference such that, in combination, each element merely performs the same function as it does separately. Additionally, Examiner finds that, based on the references' analogous disclosure regarding inference requests and processing such requests, further demonstrates that a combination of their features would have been known and obvious. Therefore, such a combination of the teachings of the references would have yielded nothing more than predictable results to one of ordinary skill in the art.
Regarding claim 11, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 10.
Xin further taught wherein the federated inference request message further comprises at least one of the following:
model instance identification information, used for identifying a target model required by a federated inference process; identification information of the first inference task; first indication information, used for indicating that the federated inference process is a vertical federated inference process; or reporting information corresponding to the first inference result. (consider paragraphs 0168-0171, specifically “The PCF sends a request #1 to the NWDAF, to subscribe to, from the NWDAF, a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model” wherein “The Nnwdaf_AnalyticsSubscription_Subscribe service operation includes, for example, the following information: Analytics ID=Service Experience, indicating the PCF to subscribe to a data analysis result of a service experience type from the NWDAF, where Analytics ID is further used to determine a service experience model used to generate the service experience data analysis result; Analytics Filter, indicating filtering information of a to-be-requested service experience data analysis result, for example, an Application ID indicating a service identifier of a service; and Target of Analytics Reporting, indicating an object of a to-be-requested model inference result, for example, an SUPI indicating a terminal identifier of the terminal” and also “the request is a service model inference result request for one or some terminals of the service A, or is a service model inference result request for all terminals of the service A”) (consider further paragraphs 0180 and 0185-0189 regarding the “NWDAF sends a request to each domain, to request a model inference result” “for the service A” wherein the request “includes the following content: a first identifier of the terminal and at least one of the following information: an analysis identifier and identification information of a first model, where the analysis identifier and/or the identification information of the first model is for determining a model used by the terminal for service experience model inference on the core network device” wherein “Specifically, in at least one embodiment, the NWDAF triggers an Nnf_AnalyticsSubscription_Subscribe service operation to the 5GC NF to subscribe to the model inference result of service experience of the terminal for the service A in the core network domain from the CN. The service operation includes a terminal identifier, for example, an SUPI or a GPSI, and model identification information of the service A, for example, one or more of a Model ID, an IP address, a URL, and an FQDN”)
Regarding claim 12, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 11.
Xin further taught wherein the reporting information of the first inference result comprises at least one of the following: a reporting format of the first inference result; or a reporting condition of the first inference result. (consider paragraphs 0168-0171, specifically “The PCF sends a request #1 to the NWDAF, to subscribe to, from the NWDAF, a service experience data analysis result of using the service A by the terminal, namely, an inference result corresponding to a service experience model” wherein “The Nnwdaf_AnalyticsSubscription_Subscribe service operation includes, for example, the following information: Analytics ID=Service Experience, indicating the PCF to subscribe to a data analysis result of a service experience type from the NWDAF, where Analytics ID is further used to determine a service experience model used to generate the service experience data analysis result; Analytics Filter, indicating filtering information of a to-be-requested service experience data analysis result, for example, an Application ID indicating a service identifier of a service; and Target of Analytics Reporting, indicating an object of a to-be-requested model inference result, for example, an SUPI indicating a terminal identifier of the terminal” and also “the request is a service model inference result request for one or some terminals of the service A, or is a service model inference result request for all terminals of the service A”)
Regarding claim 13, the combined teachings of Xin and Gadelrab taught the data processing method according to claim 10.
Xin further taught wherein the step of performing, by the second network element, inference based on the federated inference request message to obtain a first inference result comprises:
determining, by the second network element, a local inference model and type information of inference input data based on model instance identification information in the federated inference request message; obtaining, by the second network element, the inference input data based on the type information of the inference input data and information related to the first filter in the federated inference request message; and performing, by the second network element, inference based on the inference input data and the local inference model to obtain the first inference result. (consider paragraphs 0180 and 0185-0189 regarding the “NWDAF sends a request to each domain, to request a model inference result” “for the service A” wherein the request “includes the following content: a first identifier of the terminal and at least one of the following information: an analysis identifier and identification information of a first model, where the analysis identifier and/or the identification information of the first model is for determining a model used by the terminal for service experience model inference on the core network device” and “The service operation includes a data type Event ID of the public data in the core network domain and a terminal identifier SUPI”) (consider further paragraphs 0201-0204 wherein “Each domain receives the subscription request of the NWDAF, generates a local model inference result of the terminal in each domain for the service A, and sends a response to the NWDAF, where the response includes the local model inference result in each domain” wherein “for a plurality of terminals, each domain calculates a model inference result of each terminal locally”)
Claim(s) 14-20 recite an electronic device that contain substantially the same limitations as recited in claim(s) 1-5 and 7-8 respectively and are also rejected under 35 USC § 103 as being unpatentable over the same combined teachings of Xin and Gadelrab and the same rationale supporting the conclusion of obviousness.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to G. C. Neurauter, Jr. whose telephone number is (571)272-3918. The examiner can normally be reached Monday-Friday 9am-5pm Eastern Time.
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/G. C. Neurauter, Jr./Primary Examiner, Art Unit 2459
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