DETAILED ACTION
This action is in response to the application filed 01/12/2023. Claims 1-20 are pending and have been examined.
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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 12-14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 12 recites the limitation "managing the scoring flow via the one or more scoring flow artifacts" in lines 1-2. Lines 9-12 of claim 1 recite “the scoring flow is configured to be managed as one or more scoring flow artifacts of the plurality of artifacts”. The language in claim 12 is inconsistent with the language regarding managing the scoring flow artifact in claim 1. It is unclear as to whether the scoring flow according to claim 12 is a scoring flow artifact as recited in claim 1, or if it is to be managed by a scoring flow artifact as recited in claim 12. For purposes of examination, Examiner has interpreted claim 12 to be consistent with claim 1. Examiner notes that if applicant amends claim 12 to be consistent with claim 1, claim 12 would be rejected under 112(d).
Claim 13 recites the limitation "a shape of the one or more data inputs" in lines 1-2. It is unclear as to what “shape” means. For purposes of examination, Examiner interpreted “shape” to mean a geometric form of the data.
Claim 14 recites the limitation "a shape of the one or more data sinks" in lines 1-2. It is unclear as to what “shape” means. For purposes of examination, Examiner interpreted “shape” to mean a geometric form of the data.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-14 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by TIBCO, (“TIBCO ModelOps Documentation”) (hereafter referred to as TIBCO).
Regarding claim 1, TIBCO teaches
A computer-implemented method to implement a model operation application, the method comprising: defining a plurality of artifacts of a model operation application (TIBCO, page 4, Overview section, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the artifacts.),
wherein each artifact has an abstract interface (TIBCO, page 5, Authoring a Scoring Flow section, “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section.” Examiner notes that the template is the abstract interface.),
and wherein each artifact is invoked by a corresponding reference (TIBCO, page 4, Overview section, “Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the artifacts and the reference is the data source.);
organizing references of one or more data inputs and references of one or more data sinks of the model operation application into a data channel, wherein the data channel comprises one or more data channel artifacts of the plurality of artifacts (TIBCO, pages 15-16 Authoring a Scoring Pipeline section, “3. If you are using Data Source and Data Sink as input and output, select the Connect to deployed Data Channels for input and output. 1. Select the scoring flow from the drop-down list under Scoring Flows section. 2. Add Data Source and Data Sink from the drop-down list under the Data Channels section. A data source is used to supply data to a flow to process it. A data sink is a place where the data processed by the flow is sent.” Examiner notes that the data source is the one or more data inputs and the data sink is the one or more data references of one or more data sinks. Examiner further notes that the data channel is the one or more data channel artifacts of the plurality of artifacts or scoring flows.);
combining a plurality of processing steps by reference into a scoring flow, wherein the scoring flow is configured to be managed as one or more scoring flow artifacts of the plurality of artifacts (TIBCO, page 4, Overview section, “Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the artifacts and the reference is the data source. Examiner further notes that the scoring flows are the scoring flow artifacts of the plurality of artifacts.); and
attaching the data channel to the scoring flow to form a scoring pipeline, wherein the scoring pipeline comprises one or more scoring pipeline artifacts of the plurality of artifacts (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “1. In the Project Explorer pane, under Overview section, click Pipelines. 2. Select the scoring pipeline. 3. If you are using Data Source and Data Sink as input and output, select the Connect to deployed Data Channels for input and output. 1. Select the scoring flow from the drop-down list under Scoring Flows section. 2. Add Data Source and Data Sink from the drop-down list under the Data Channels section. A data source is used to supply data to a flow to process it. A data sink is a place where the data processed by the flow is sent.” Examiner notes that the data channel is added to the scoring flow and a scoring pipeline is created from adding the data channel.).
Regarding claim 2, TIBCO teaches
The computer-implemented method of claim 1, further comprising labeling an artifact of the plurality of artifacts with a metadata (TIBCO, page 11-12, Authoring a Scoring Flow section, “6. Configure the Output block. 1. Click the Output processing step to open its configuration form. 2. Under Output Record, click the plus sign (+) next to 0 of 0 Fields are set and add these 5 fields: Name: Predicted _CreditStanding_Bad; Name: Probability_0; Name: Probability_1; Name: Final_Credit_Approval_Decision; Name: Policy_Followed; 3. To populate the values for these fields, click Populate unset values with entries and select ‘SCORE’ of step ‘Score’. 4. Next, click Populate unset values with entries again and select ‘POST_SCORING_DECISION_OUT’ of step ‘Decisions’. 5. Click SAVE”. Examiner notes that populating the fields with values is labeling with metadata. Examiner further notes that the output is an artifact of the plurality of artifacts.).
Regarding claim 3, TIBCO teaches,
The computer-implemented method of claim 1, further comprising organizing references of a second set of one or more data inputs and references of a second set of one or more data sinks of the model operation application into a second data channel, wherein the second data channel comprises a second set of one or more data channel artifacts of the plurality of artifacts (TIBCO, page 15 Creating a Scoring Pipeline section, “1. In the Project Explorer pane, under Overview section, click Pipelines (glossary.html#scoring-pipeline). 2. Click ADD A SCORING PIPELINE to create a new scoring pipeline. You can also click Add one to add a new scoring pipeline if there are none present” where “3. If you are using Data Source and Data Sink as input and output, select the Connect to deployed Data Channels for input and output. 1. Select the scoring flow from the drop-down list under Scoring Flows section. 2. Add Data Source and Data Sink from the drop-down list under the Data Channels section. A data source is used to supply data to a flow to process it. A data sink is a place where the data processed by the flow is sent” (TIBCO, pages 15-16, Authoring a Scoring Pipeline section) Examiner notes that the data source is the second set of one or more data inputs and the data sink is the second set of one or more data references of a second set of one or more data sinks. Examiner further notes that the data channel is the second set of one or more data channel artifacts of the plurality of artifacts or scoring flows.).
Regarding claim 4, TIBCO teaches,
The computer-implemented method of claim 3, further comprising: combining a second plurality of processing steps by reference into a second scoring flow, wherein the second scoring flow is configured to be managed as a second set of one or more scoring flow artifacts of the plurality of artifacts; and attaching the second data channel to the second scoring flow to form a second scoring pipeline, wherein the second scoring pipeline comprises a second set of one or more scoring pipeline artifacts of the plurality of artifacts (TIBCO, page 4, Overview section, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the second set of one or more scoring flow artifacts and the reference is the data source. Examiner further notes that the scoring flows are the second set of scoring flow artifacts of the plurality of artifacts.).
Regarding claim 5, TIBCO teaches
The computer-implemented method of claim 4, wherein the data channel, and the scoring flow form a first scoring pipeline, and wherein the second data channel and the second scoring flow form a second scoring pipeline that is interconnected with the first scoring pipeline (TIBCO, page 4, Overview section, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps” where “1. You can also deploy multiple instances with the same pipelines. 2. You can either follow the same steps as mentioned earlier to deploy a new instance with the same pipeline. 3. Or, you can duplicate the instance by clicking the duplicate icon. 4. Note that even though we are using the same pipeline for deployment, the Deployment name is unique every time” (TIBCO, page 20, Deploying Multiple Scoring Pipeline Instances section). Examiner notes that the first scoring pipeline is the original pipeline and the second scoring pipeline is the duplicated pipeline. Examiner further notes that the definition of interconnected according to Merriam-Webster is “mutually joined or related”. Based on this definition, the duplicated pipeline is related and thus interconnected to the original pipeline.).
Regarding claim 6, TIBCO teaches
The computer-implemented method of claim 1, further comprising forming a knowledge network graph from the data channel, the scoring flow, and the scoring pipeline, wherein one or more nodes and connectors of the knowledge network graph represent the data channel, the data processing steps, the scoring flow, or the scoring pipeline (TIBCO, Overview section, page 4, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps” where “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.
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” (TIBCO, page 15-16, Authoring a Scoring Pipeline section). Examiner notes that the knowledge network is the scoring flow diagram in the figure above. Examiner further notes that the input box is the data channel, the score box is the scoring flow and the flow diagram is the scoring pipeline. Thus, the knowledge network graph is formed from the data channel, the scoring flow, and the scoring pipeline.).
Regarding claim 7, TIBCO teaches
The computer-implemented method of claim 6, further comprising: receiving an instruction to modify the data channel, the scoring flow, or the scoring pipeline, in response to receiving the instruction to modify the data channel, the scoring flow, or the scoring pipeline: identifying a corresponding artifact associated with the data channel, the scoring flow, or the scoring pipeline: and modifying the corresponding artifact (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.” Examiner notes that the user configuring the input block is the step of receiving an instruction to modify the scoring flow. Examiner further notes that by configuring the input block, the scoring flow associated with the input block is identified and modified. Examiner additionally notes that the artifact is the scoring flow.).
Regarding claim 8, TIBCO teaches
The computer-implemented method of claim 7, wherein modifying the corresponding artifact comprises modifying the corresponding artifact without modifying another artifact of the plurality of artifacts (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.” Examiner notes that the user selects a singular scoring flow to modify thus, other scoring flows or artifacts are not modified.).
Regarding claim 9, TIBCO teaches
The computer-implemented method of claim 7, further comprising dynamically propagating a modification throughout the data channel, the scoring flow, and the scoring pipeline (TIBCO, page 1, Records section, “Data flowing through a scoring pipeline is represented as a record, which is a set of named data values” where “when a record is received by a scoring flow it is passed to each processing step in order. Each processing step has access to all fields in the record and can add new fields, or modify existing field values” (TIBCO, page 1, Execution Model section). Examiner notes that the modification was to the data source or data channel and the data from the data source is then propagated through the processing steps which is included in the scoring flow and the scoring pipeline. Examiner notes that since the processing steps can further modify the data, the data is dynamically propagated. ).
Regarding claim 10, TIBCO teaches
The computer-implemented method of claim 6, further comprising providing the knowledge network graph for display (TIBCO, page 4, Overview section, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps” where “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.
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” (TIBCO, pages 15-16, Authoring a Scoring Pipeline section). Examiner notes that the knowledge network is the scoring flow diagram in the figure above which is displayed to a user.).
Regarding claim 11, TIBCO teaches
The computer-implemented method of claim 1, further comprising managing the data channel via the one or more data channel artifacts (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “3. If you are using Data Source and Data Sink as input and output, select the Connect to deployed Data Channels for input and output. 1. Select the scoring flow from the drop-down list under Scoring Flows section. 2. Add Data Source and Data Sink from the drop-down list under the Data Channels section. A data source is used to supply data to a flow to process it. A data sink is a place where the data processed by the flow is sent.” Examiner notes that the data source is the one or more data inputs and the data sink is the one or more data references of one or more data sinks. Examiner further notes that the data channel is the one or more data channel artifacts of the plurality of artifacts or scoring flows.).
Regarding claim 12, TIBCO teaches
The computer-implemented method of claim 1, further comprising managing the scoring flow via the one or more scoring flow artifacts (TIBCO, page 4, Overview section, “Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the scoring flow artifacts.).
Regarding claim 13, TIBCO teaches
The computer-implemented method of claim 12, wherein the scoring flow defines a shape of the one or more data inputs used by a processing step that is associated with the scoring flow (TIBCO, page 2, see figure below,
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Examiner notes that the shape of the data inputs is the matrix created in the scoring flow.).
Regarding claim 14, TIBCO teaches
The computer-implemented method of claim 13, wherein the scoring flow defines a shape of the one or more data sinks that are emitted from a processing step that is associated with the scoring flow (TIBCO, page 2, see figure below,
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Examiner notes that the shape of the data sink is the matrix created in the scoring flow.).
Claim Rejections - 35 USC § 103
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.
Claim(s) 15-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over TIBCO in view of Mannheimer et al. (US 2025/0362889 A1) (hereafter referred to as Mannheimer).
Regarding claim 15, TIBCO teaches
define a plurality of artifacts of a model operation application (TIBCO, page 4, Overview section, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the artifacts.),
wherein each artifact has an abstract interface (TIBCO, page 5, Authoring a Scoring Flow section, “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section.” Examiner notes that the template is the abstract interface.),
and wherein each artifact is invoked by a corresponding reference (TIBCO, page 4, Overview section, “Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the artifacts and the reference is the data source.);
organize references of one or more data inputs and references of one or more data sinks of the model operation application into a data channel, wherein the data channel comprises one or more data channel artifacts of the plurality of artifacts (TIBCO, pages 15-16 Authoring a Scoring Pipeline section, “3. If you are using Data Source and Data Sink as input and output, select the Connect to deployed Data Channels for input and output. 1. Select the scoring flow from the drop-down list under Scoring Flows section. 2. Add Data Source and Data Sink from the drop-down list under the Data Channels section. A data source is used to supply data to a flow to process it. A data sink is a place where the data processed by the flow is sent.” Examiner notes that the data source is the one or more data inputs and the data sink is the one or more data references of one or more data sinks. Examiner further notes that the data channel is the one or more data channel artifacts of the plurality of artifacts or scoring flows.);
combine a plurality of processing steps by reference into a scoring flow, wherein the scoring flow is configured to be managed as one or more scoring flow artifacts of the plurality of artifacts (TIBCO, page 4, Overview section, “Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the artifacts and the reference is the data source. Examiner further notes that the scoring flows are the scoring flow artifacts of the plurality of artifacts.); and
attach the data channel to the scoring flow to form a scoring pipeline, wherein the scoring pipeline comprises one or more scoring pipeline artifacts of the plurality of artifacts (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “1. In the Project Explorer pane, under Overview section, click Pipelines. 2. Select the scoring pipeline. 3. If you are using Data Source and Data Sink as input and output, select the Connect to deployed Data Channels for input and output. 1. Select the scoring flow from the drop-down list under Scoring Flows section. 2. Add Data Source and Data Sink from the drop-down list under the Data Channels section. A data source is used to supply data to a flow to process it. A data sink is a place where the data processed by the flow is sent.” Examiner notes that the data channel is added to the scoring flow and a scoring pipeline is created from adding the data channel.)
label an artifact of the plurality of artifacts with a metadata (TIBCO, page 11-12, Authoring a Scoring Flow section, “6. Configure the Output block. 1. Click the Output processing step to open its configuration form. 2. Under Output Record, click the plus sign (+) next to 0 of 0 Fields are set and add these 5 fields: Name: Predicted _CreditStanding_Bad; Name: Probability_0; Name: Probability_1; Name: Final_Credit_Approval_Decision; Name: Policy_Followed; 3. To populate the values for these fields, click Populate unset values with entries and select ‘SCORE’ of step ‘Score’. 4. Next, click Populate unset values with entries again and select ‘POST_SCORING_DECISION_OUT’ of step ‘Decisions’. 5. Click SAVE”. Examiner notes that populating the fields with values is labeling with metadata. Examiner further notes that the output is an artifact of the plurality of artifacts.).
TIBCO does not explicitly disclose but Mannheimer does disclose
A model operation implementation system, comprising: a storage medium; and one or more processors configured to: (Mannheimer, page 40, paragraph 0024, “In some implementations, a non-transitory computer readable storage medium stores one or more programs configured for execution by a computing device having one or more processors and memory. The one or more programs include instructions for performing any of the methods described herein.”)
TIBCO and Mannheimer are analogous to the claimed invention because they both integrate a machine learning platform with a visual analytics platform. It would have been obvious to a person having ordinary skill in the art prior to the effective filing date to have implemented the methods of TIBCO on the system of Mannheimer. Thus, this would be applying a known technique (the methods of TIBCO) to a known device (a storage medium and processor of Mannheimer) ready for improvement to yield predictable results (integration of machine learning platform with a visual analytics platform) (MPEP 2143 I. (C) Use of known technique to improve similar devices (methods, or products) in the same way).
Regarding claim 16, TIBCO in view of Mannheimer teaches the model operation implementation system of claim 15. TIBCO in view of Mannheimer further teaches
organize references of a second set of one or more data inputs and references of a second set of one or more data sinks of the model operation application into a second data channel, wherein the second data channel comprises a second set of one or more data channel artifacts of the plurality of artifacts (TIBCO, page 15 Creating a Scoring Pipeline section, “1. In the Project Explorer pane, under Overview section, click Pipelines (glossary.html#scoring-pipeline). 2. Click ADD A SCORING PIPELINE to create a new scoring pipeline. You can also click Add one to add a new scoring pipeline if there are none present” where “3. If you are using Data Source and Data Sink as input and output, select the Connect to deployed Data Channels for input and output. 1. Select the scoring flow from the drop-down list under Scoring Flows section. 2. Add Data Source and Data Sink from the drop-down list under the Data Channels section. A data source is used to supply data to a flow to process it. A data sink is a place where the data processed by the flow is sent” (TIBCO, pages 15-16, Authoring a Scoring Pipeline section) Examiner notes that the data source is the second set of one or more data inputs and the data sink is the second set of one or more data references of a second set of one or more data sinks. Examiner further notes that the data channel is the second set of one or more data channel artifacts of the plurality of artifacts or scoring flows.).
combine a second plurality of processing steps by reference into a second scoring flow, wherein the second scoring flow is configured to be managed as a second set of one or more scoring flow artifacts of the plurality of artifacts; and attach the second data channel to the second scoring flow to form a second scoring pipeline, wherein the second scoring pipeline comprises a second set of one or more scoring pipeline artifacts of the plurality of artifacts (TIBCO, page 4, Overview section, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the second set of one or more scoring flow artifacts and the reference is the data source. Examiner further notes that the scoring flows are the second set of scoring flow artifacts of the plurality of artifacts.).
wherein the data channel, and the scoring flow form a first scoring pipeline, and wherein the second data channel and the second scoring flow form a second scoring pipeline that is interconnected with the first scoring pipeline (TIBCO, page 4, Overview section, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps” where “1. You can also deploy multiple instances with the same pipelines. 2. You can either follow the same steps as mentioned earlier to deploy a new instance with the same pipeline. 3. Or, you can duplicate the instance by clicking the duplicate icon. 4. Note that even though we are using the same pipeline for deployment, the Deployment name is unique every time” (TIBCO, page 20, Deploying Multiple Scoring Pipeline Instances section). Examiner notes that the first scoring pipeline is the original pipeline and the second scoring pipeline is the duplicated pipeline. Examiner further notes that the definition of interconnected according to Merriam-Webster is “mutually joined or related”. Based on this definition, the duplicated pipeline is related and thus interconnected to the original pipeline.).
Regarding claim 17, TIBCO in view of Mannheimer teaches the model operation implementation system of claim 16. TIBCO in view of Mannheimer further teaches
form a knowledge network graph from the data channel, the scoring flow, and the scoring pipeline, wherein one or more nodes and connectors of the knowledge network graph represent the data channel, the data processing steps, the scoring flow, or the scoring pipeline (TIBCO, Overview section, page 4, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps” where “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.
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” (TIBCO, page 15-16, Authoring a Scoring Pipeline section). Examiner notes that the knowledge network is the scoring flow diagram in the figure above. Examiner further notes that the input box is the data channel, the score box is the scoring flow and the flow diagram is the scoring pipeline. Thus, the knowledge network graph is formed from the data channel, the scoring flow, and the scoring pipeline.).
Regarding claim 18, TIBCO in view of Mannheimer teaches the model operation implementation system of claim 17. TIBCO in view of Mannheimer further teaches
receive an instruction to modify the data channel, the scoring flow, or the scoring pipeline; in response to receiving the instruction to modify the data channel, the scoring flow, or the scoring pipeline: identify a corresponding artifact associated with the data channel, the scoring flow, or the scoring pipeline: and modify the corresponding artifact (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.” Examiner notes that the user configuring the input block is the step of receiving an instruction to modify the scoring flow. Examiner further notes that by configuring the input block, the scoring flow associated with the input block is identified and modified. Examiner additionally notes that the artifact is the scoring flow.)
wherein modifying the corresponding artifact comprises modifying the corresponding artifact without modifying another artifact of the plurality of artifacts (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.” Examiner notes that the user selects a singular scoring flow to modify thus, other scoring flows or artifacts are not modified.).
Regarding claim 19, TIBCO teaches
defining a plurality of artifacts of a model operation application (TIBCO, page 4, Overview section, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the artifacts.),
wherein each artifact has an abstract interface (TIBCO, page 5, Authoring a Scoring Flow section, “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section.” Examiner notes that the template is the abstract interface.),
and wherein each artifact is invoked by a corresponding reference (TIBCO, page 4, Overview section, “Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the artifacts and the reference is the data source.);
organizing references of one or more data inputs and references of one or more data sinks of the model operation application into a data channel, wherein the data channel comprises one or more data channel artifacts of the plurality of artifacts (TIBCO, pages 15-16 Authoring a Scoring Pipeline section, “3. If you are using Data Source and Data Sink as input and output, select the Connect to deployed Data Channels for input and output. 1. Select the scoring flow from the drop-down list under Scoring Flows section. 2. Add Data Source and Data Sink from the drop-down list under the Data Channels section. A data source is used to supply data to a flow to process it. A data sink is a place where the data processed by the flow is sent.” Examiner notes that the data source is the one or more data inputs and the data sink is the one or more data references of one or more data sinks. Examiner further notes that the data channel is the one or more data channel artifacts of the plurality of artifacts or scoring flows.);
combining a plurality of processing steps by reference into a scoring flow, wherein the scoring flow is configured to be managed as one or more scoring flow artifacts of the plurality of artifacts (TIBCO, page 4, Overview section, “Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps.” Examiner notes that the scoring flows are the artifacts and the reference is the data source. Examiner further notes that the scoring flows are the scoring flow artifacts of the plurality of artifacts.); and
attaching the data channel to the scoring flow to form a scoring pipeline, wherein the scoring pipeline comprises one or more scoring pipeline artifacts of the plurality of artifacts (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “1. In the Project Explorer pane, under Overview section, click Pipelines. 2. Select the scoring pipeline. 3. If you are using Data Source and Data Sink as input and output, select the Connect to deployed Data Channels for input and output. 1. Select the scoring flow from the drop-down list under Scoring Flows section. 2. Add Data Source and Data Sink from the drop-down list under the Data Channels section. A data source is used to supply data to a flow to process it. A data sink is a place where the data processed by the flow is sent.” Examiner notes that the data channel is added to the scoring flow and a scoring pipeline is created from adding the data channel.)
labeling an artifact of the plurality of artifacts with a metadata (TIBCO, page 11-12, Authoring a Scoring Flow section, “6. Configure the Output block. 1. Click the Output processing step to open its configuration form. 2. Under Output Record, click the plus sign (+) next to 0 of 0 Fields are set and add these 5 fields: Name: Predicted _CreditStanding_Bad; Name: Probability_0; Name: Probability_1; Name: Final_Credit_Approval_Decision; Name: Policy_Followed; 3. To populate the values for these fields, click Populate unset values with entries and select ‘SCORE’ of step ‘Score’. 4. Next, click Populate unset values with entries again and select ‘POST_SCORING_DECISION_OUT’ of step ‘Decisions’. 5. Click SAVE”. Examiner notes that populating the fields with values is labeling with metadata. Examiner further notes that the output is an artifact of the plurality of artifacts.).
TIBCO does not explicitly disclose but Mannheimer does disclose
A non-transitory machine-readable medium comprising instructions, which, when executed by a processor, causes the processor to perform operations comprising: (Mannheimer, page 40, paragraph 0024, “In some implementations, a non-transitory computer readable storage medium stores one or more programs configured for execution by a computing device having one or more processors and memory. The one or more programs include instructions for performing any of the methods described herein.”)
TIBCO and Mannheimer are analogous to the claimed invention because they both integrate a machine learning platform with a visual analytics platform. It would have been obvious to a person having ordinary skill in the art prior to the effective filing date to have implemented the methods of TIBCO on the non-transitory machine-readable medium of Mannheimer. Thus, this would be applying a known technique (the methods of TIBCO) to a known device (the non-transitory machine-readable medium of Mannheimer) ready for improvement to yield predictable results (integration of machine learning platform with a visual analytics platform) (MPEP 2143 I. (C) Use of known technique to improve similar devices (methods, or products) in the same way).
Regarding claim 20, TIBCO in view of Mannheimer teaches the non-transitory machine-readable medium of claim 19. TIBCO in view of Mannheimer further teaches
forming a knowledge network graph from the data channel, the scoring flow, and the scoring pipeline, wherein one or more nodes and connectors of the knowledge network graph represent the data channel, the data processing steps, the scoring flow, or the scoring pipeline (TIBCO, Overview section, page 4, “Scoring Pipeline: A scoring pipeline is a design-time artifact that defines a scoring pipeline. A scoring pipeline defines a data source, a data sink, one or more scoring flows, and zero or more models used in the scoring flow. Scoring Flow: A scoring flow is an ordered sequence of processing steps that operate on data received from a data source and sent to a data sink. The data flowing through a scoring flow can be transformed and augmented by processing steps” where “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.
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” (TIBCO, page 15-16, Authoring a Scoring Pipeline section). Examiner notes that the knowledge network is the scoring flow diagram in the figure above. Examiner further notes that the input box is the data channel, the score box is the scoring flow and the flow diagram is the scoring pipeline. Thus, the knowledge network graph is formed from the data channel, the scoring flow, and the scoring pipeline.)
receiving an instruction to modify the data channel, the scoring flow, or the scoring pipeline; in response to receiving the instruction to modify the data channel, the scoring flow, or the scoring pipeline: identify a corresponding artifact associated with the data channel, the scoring flow, or the scoring pipeline: and modifying the corresponding artifact (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.” Examiner notes that the user configuring the input block is the step of receiving an instruction to modify the scoring flow. Examiner further notes that by configuring the input block, the scoring flow associated with the input block is identified and modified. Examiner additionally notes that the artifact is the scoring flow.)
wherein modifying the corresponding artifact comprises modifying the corresponding artifact without modifying another artifact of the plurality of artifacts (TIBCO, pages 15-16, Authoring a Scoring Pipeline section, “In the Project Explorer pane, under Overview section, click Scoring Flows. Select the scoring flow. Select a scoring flow template by clicking the Load template flows option under Edit section. The Score template can be configured by following these steps: 1. Configure the input block. 1. Click input block to open the Input processing step’s configuration form. 2. Click the drop-down menu on the Load Schema From option. 3. Next, click Data Source and select the appropriate data source.” Examiner notes that the user selects a singular scoring flow to modify thus, other scoring flows or artifacts are not modified.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Suryanarayana et al. (WO 2023/143746 A1) also discloses managing artifacts and forming a knowledge graph from the artifacts.
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/K.R.H./Examiner, Art Unit 2148 /MICHELLE T BECHTOLD/Supervisory Patent Examiner, Art Unit 2148