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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on November 4, 2025 has been entered.
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 1-20 are rejection under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1,
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 1 is directed to a non-transitory computer readable storage medium comprising stored instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“identify a plurality of candidate changes to one or more of the plurality of steps of the target workflow”
“filter the plurality of candidate changes into a subset of candidate changes by identifying a first segment of the plurality of candidate changes having the context attribute”
“identifying, from the first segment, a set of matching candidate changes”
“determining whether an amount of matching candidate changes within the set exceeds a threshold number of matching candidate changes”
“responsive to determining that the amount of matching candidate changes within the set does not exceed the threshold: relaxing the context attribute by referencing a knowledge graph and identifying at least one additional context attribute having a node that is connected to a node for the context attribute by an edge within the knowledge graph, the context attribute relaxed from including only the node for the context attribute to including the node for the at least one additional context attribute, the node for the at least one additional context attribute one hop away from the node for the context attribute”
“identifying a second segment of the plurality of candidate changes having the at least one additional context attribute”
“identifying, from the second segment, additional matches to add to the set of matching candidate changes, wherein the context attribute is iteratively relaxed to further next-hop context attributes by further edges and further new additional matches are added to the set until the amount of matching candidate changes within the set exceeds the threshold, at which time the set becomes used as the subset of candidate changes”
“for each candidate change of the subset of candidate changes: generate a feature vector comprising a set of features for the candidate change”
“select, for a step of the plurality of steps, a candidate change associated with a highest expected impact”
“apply the selected candidate change to the target workflow by replacing the step with the candidate change”
As drafted, under their broadest reasonable interpretations, cover mental processes, i.e., concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The above limitations in the context of this claim correspond to mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)).
The limitations:
“A non-transitory computer readable storage medium comprising stored instructions, the instructions when executed by one or more processors cause the one or more processors”
“input the feature vector into a machine learning model that outputs an expected impact for the candidate change based on its respective feature vector, the machine learning model trained using training data including changes made to historical workflows and corresponding changes in performance of the historical workflows”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
The limitations:
“receive a target workflow comprising a structure having a plurality of steps in a predefined order, the target workflow having a context attribute”
As drafted, are additional elements that amount to no more than insignificant extra-solution activity. See MPEP 2106.05(g).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply” and “insignificant extra-solution activity”. Additionally, the receiving limitation recites the well-understood, routine, and conventional activity of receiving or transmitting data over a network. MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Mere instructions to apply an exception and insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 2,
Claim 2 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 2 is directed to a non-transitory computer readable storage medium comprising stored instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“identify a plurality of candidate workflows similar to the target workflow”
“identify a plurality of historical changes previously made to the plurality of candidate workflows as the plurality of candidate changes”
As drafted, under their broadest reasonable interpretations, cover mental processes, i.e., concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The above limitations in the context of this claim correspond to mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: See corresponding analysis of claim 1.
Step 2B Analysis: See corresponding analysis of claim 1.
Regarding Claim 3,
Claim 3 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 3 is directed to a non-transitory computer readable storage medium comprising stored instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 2.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the target workflow is associated with a first context and a candidate workflow of the plurality of candidate workflows is associated with a second context that has a strength of similarity to the first context greater than a threshold strength”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. The claim is not patent eligible.
Regarding Claim 4,
Claim 4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 4 is directed to a non-transitory computer readable storage medium comprising stored instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 3.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the first context is connected to the second context by a weighted edge representing the strength of similarity between the first context and the second context in a context association graph”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. The claim is not patent eligible.
Regarding Claim 5,
Claim 5 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 5 is directed to a non-transitory computer readable storage medium comprising stored instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 2.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the target workflow is associated with a first structure having a plurality of steps in a predefined order and each of the plurality of candidate workflows is associated with a structure with a number of structural changes relative to the first structure less than a threshold number of structural changes”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. The claim is not patent eligible.
Regarding Claim 6,
Claim 6 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 6 is directed to a non-transitory computer readable storage medium comprising stored instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“responsive to applying the selected candidate change to the target workflow, determine corresponding changes in performance”
“based on the changes in performance, determine whether the selected candidate change improves performance of the target workflow”
“responsive to determining that the selected candidate change improves the performance of the target workflow, keep the selected candidate change”
“responsive to determining that the selected candidate change does not improve the performance of the target workflow, remove the selected candidate change”
As drafted, under their broadest reasonable interpretations, cover mental processes, i.e., concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The above limitations in the context of this claim correspond to mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: See corresponding analysis of claim 1.
Step 2B Analysis: See corresponding analysis of claim 1.
Regarding Claim 7,
Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 7 is directed to a non-transitory computer readable storage medium comprising stored instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)).
The limitations:
“wherein the feature vector associated with a candidate change previously made to a candidate workflow includes one or more of: a type of action associated with the candidate change, a timing associated with the candidate change, an order of a step to which the candidate change was applied within a corresponding candidate workflow, historical impact associated with the candidate change, and a number of times the candidate change was tested”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception. See MPEP 2106.05(f).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply”. The claim is not patent eligible.
Regarding Claim 8,
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 8 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“identifying a plurality of candidate changes to one or more of the plurality of steps of the target workflow”
“filtering the plurality of candidate changes into a subset of candidate changes by identifying a first segment of the plurality of candidate changes having the context attribute”
“identifying, from the first segment, a set of matching candidate changes”
“determining whether an amount of matching candidate changes within the set exceeds a threshold number of matching candidate changes”
“responsive to determining that the amount of matching candidate changes within the set does not exceed the threshold: relaxing the context attribute by referencing a knowledge graph and identifying at least one additional context attribute having a node that is connected to a node for the context attribute by an edge within the knowledge graph, the context attribute relaxed from including only the node for the context attribute to including the node for the at least one additional context attribute, the node for the at least one additional context attribute one hop away from the node for the context attribute”
“identifying a second segment of the plurality of candidate changes having the at least one additional context attribute”
“identifying, from the second segment, additional matches to add to the set of matching candidate changes, wherein the context attribute is iteratively relaxed to further next-hop context attributes by further edges and further new additional matches are added to the set until the amount of matching candidate changes within the set exceeds the threshold, at which time the set becomes used as the subset of candidate changes”
“for each candidate change of the subset of candidate changes generating a feature vector comprising a set of features for the candidate change”
“selecting, for a step of the plurality of steps, a candidate change associated with a highest expected impact”
“applying the selected candidate change to the target workflow by replacing the step with the candidate change”
As drafted, under their broadest reasonable interpretations, cover mental processes, i.e., concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The above limitations in the context of this claim correspond to mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)).
The limitations:
“inputting the feature vector into a machine learning model that outputs an expected impact for the candidate change based on its respective feature vector, the machine learning model trained using training data including changes made to historical workflows and corresponding changes in performance of the historical workflows”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
The limitations:
“receiving a target workflow comprising a structure having a plurality of steps in a predefined order, the target workflow having a context attribute”
As drafted, are additional elements that amount to no more than insignificant extra-solution activity. See MPEP 2106.05(g).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply” and “insignificant extra-solution activity”. Additionally, the receiving limitation recites the well-understood, routine, and conventional activity of receiving or transmitting data over a network. MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Mere instructions to apply an exception and insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 9,
Claim 9 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 9 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“identifying a plurality of candidate workflows similar to the target workflow”
“identifying a plurality of historical changes previously made to the plurality of candidate workflows as the plurality of candidate changes”
As drafted, under their broadest reasonable interpretations, cover mental processes, i.e., concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The above limitations in the context of this claim correspond to mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: See corresponding analysis of claim 8.
Step 2B Analysis: See corresponding analysis of claim 8.
Regarding Claim 10,
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 10 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 9.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the target workflow is associated with a first context and a candidate workflow of the plurality of candidate workflows is associated with a second context that has a strength of similarity to the first context greater than a threshold strength”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. The claim is not patent eligible.
Regarding Claim 11,
Claim 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 11 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 10.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the first context is connected to the second context by a weighted edge representing the strength of similarity between the first context and the second context in a context association graph”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. The claim is not patent eligible.
Regarding Claim 12,
Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 12 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 9.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the target workflow is associated with a first structure having a plurality of steps in a predefined order and each of the plurality of candidate workflows is associated with a structure with a number of structural changes relative to the first structure less than a threshold number of structural changes”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. The claim is not patent eligible.
Regarding Claim 13,
Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 13 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“responsive to applying the selected candidate change to the target workflow, determining corresponding changes in performance”
“based on the changes in performance, determining whether the selected candidate change improves performance of the target workflow”
“responsive to determining that the selected candidate change improves the performance of the target workflow, keeping the selected candidate change”
“responsive to determining that the selected candidate change does not improve the performance of the target workflow, removing the selected candidate change”
As drafted, under their broadest reasonable interpretations, cover mental processes, i.e., concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The above limitations in the context of this claim correspond to mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: See corresponding analysis of claim 8.
Step 2B Analysis: See corresponding analysis of claim 8.
Regarding Claim 14,
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 14 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 8.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)).
The limitations:
“wherein the feature vector associated with a candidate change previously made to a candidate workflow includes one or more of: a type of action associated with the candidate change, a timing associated with the candidate change, an order of a step to which the candidate change was applied within a corresponding candidate workflow, historical impact associated with the candidate change, and a number of times the candidate change was tested”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception. See MPEP 2106.05(f).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply”. The claim is not patent eligible.
Regarding Claim 15,
Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 15 is directed to a system comprising: one or more processors; and a non-transitory computer-readable medium comprising computer program instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“identifying a plurality of candidate changes to one or more of the plurality of steps of the target workflow”
“filtering the plurality of candidate changes into a subset of candidate changes by identifying a first segment of the plurality of candidate changes having the context attribute”
“identifying, from the first segment, a set of matching candidate changes”
“determining whether an amount of matching candidate changes within the set exceeds a threshold number of matching candidate changes”
“responsive to determining that the amount of matching candidate changes within the set does not exceed the threshold: relaxing the context attribute by referencing a knowledge graph and identifying at least one additional context attribute having a node that is connected to a node for the context attribute by an edge within the knowledge graph, the context attribute relaxed from including only the node for the context attribute to including the node for the at least one additional context attribute, the node for the at least one additional context attribute one hop away from the node for the context attribute”
“identifying a second segment of the plurality of candidate changes having the at least one additional context attribute”
“identifying, from the second segment, additional matches to add to the set of matching candidate changes, wherein the context attribute is iteratively relaxed to further next-hop context attributes by further edges and further new additional matches are added to the set until the amount of matching candidate changes within the set exceeds the threshold, at which time the set becomes used as the subset of candidate changes”
“for each candidate change of the subset of candidate changes: generating a feature vector comprising a set of features for the candidate change”
“selecting, for a step of the plurality of steps, a candidate change associated with a highest expected impact”
“applying the selected candidate change to the target workflow by replacing the step with the candidate change”
As drafted, under their broadest reasonable interpretations, cover mental processes, i.e., concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The above limitations in the context of this claim correspond to mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)).
The limitations:
“A system comprising: one or more processors”
“a non-transitory computer-readable medium comprising computer program instructions that, when executed by the one or more processors, cause the one or more processors to perform operations”
“inputting the feature vector into a machine learning model that outputs an expected impact for the candidate change based on its respective feature vector, the machine learning model trained using training data including changes made to historical workflows and corresponding changes in performance of the historical workflows”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
The limitations:
“receiving a target workflow comprising a structure having a plurality of steps in a predefined order, the target workflow having a context attribute”
As drafted, are additional elements that amount to no more than insignificant extra-solution activity. See MPEP 2106.05(g).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply” and “insignificant extra-solution activity”. Additionally, the receiving limitation recites the well-understood, routine, and conventional activity of receiving or transmitting data over a network. MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Mere instructions to apply an exception and insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 16,
Claim 16 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 16 is directed to a system comprising: one or more processors; and a non-transitory computer-readable medium comprising computer program instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“identifying a plurality of candidate workflows similar to the target workflow”
“identifying a plurality of historical changes previously made to the plurality of candidate workflows as the plurality of candidate changes”
As drafted, under their broadest reasonable interpretations, cover mental processes, i.e., concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The above limitations in the context of this claim correspond to mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: See corresponding analysis of claim 15.
Step 2B Analysis: See corresponding analysis of claim 15.
Regarding Claim 17,
Claim 17 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 17 is directed to a system comprising: one or more processors; and a non-transitory computer-readable medium comprising computer program instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 16.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the target workflow is associated with a first context and a candidate workflow of the plurality of candidate workflows is associated with a second context that has a strength of similarity to the first context greater than a threshold strength”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. The claim is not patent eligible.
Regarding Claim 18,
Claim 18 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 18 is directed to a system comprising: one or more processors; and a non-transitory computer-readable medium comprising computer program instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 17.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the first context is connected to the second context by a weighted edge representing the strength of similarity between the first context and the second context in a context association graph”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. The claim is not patent eligible.
Regarding Claim 19,
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 19 is directed to a system comprising: one or more processors; and a non-transitory computer-readable medium comprising computer program instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 16.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the target workflow is associated with a first structure having a plurality of steps in a predefined order and each of the plurality of candidate workflows is associated with a structure with a number of structural changes relative to the first structure less than a threshold number of structural changes”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. The claim is not patent eligible.
Regarding Claim 20,
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 20 is directed to a system comprising: one or more processors; and a non-transitory computer-readable medium comprising computer program instructions, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“responsive to applying the selected candidate change to the target workflow, determining corresponding changes in performance”
“based on the changes in performance, determining whether the selected candidate change improves performance of the target workflow”
“responsive to determining that the selected candidate change improves the performance of the target workflow, keeping the selected candidate change”
“and responsive to determining that the selected candidate change does not improve the performance of the target workflow, removing the selected candidate change”
As drafted, under their broadest reasonable interpretations, cover mental processes, i.e., concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The above limitations in the context of this claim correspond to mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: See corresponding analysis of claim 15.
Step 2B Analysis: See corresponding analysis of claim 15.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3, 5-10, 12-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kalluri et al. (U.S. Patent Publication No. 2021/0264202) (“Kalluri”) in view of Scheideler et al. (U.S. Patent Publication No. 2019/0294733) (“Scheideler”).
Regarding claim 1, Kalluri teaches a non-transitory computer readable storage medium comprising stored instructions (Kalluri [0011] “Other embodiments of this aspect include corresponding computer systems, apparatus, and executable code stored on non-transitory computer-readable storage medium, each configured to perform the actions of the methods.” Kalluri provides a non-transitory computer readable storage medium comprising stored instructions.), the instructions when executed by one or more processors cause the one or more processors to: receive a target workflow comprising a structure having a plurality of steps in a predefined order (Kalluri [0034] “In some implementations, client system 130 may define one or more workflows for communicating with user devices. A communication workflow may be an orchestrated sequence of one or more tasks, such as an MCO.” Kalluri provides defining a first workflow structure having a plurality of steps in a predefined order corresponding to receive a target workflow comprising a structure having a plurality of steps in a predefined order.), the target workflow having a context attribute (Kalluri [0039] “As an illustrative example, for an email task, feature vector generator 220 may generate representations of various parameters of an email communication. Parameters may include numerical and categorical variables of the metadata associated with the email (e.g., product-category, type-of-task, and so on).”; [0064] “The interface may receive user input corresponding to the partial communication workflow. The partial communication workflow may be associated with one or more parameters that characterize each task of the one or more tasks of the partial communication workflow. For example, the parameters may include vocabularies for topic-modeling, content images of digital messages, and other suitable characteristics of the tasks.” Kalluri provides parameters for characterizing workflows corresponding to context attributes.); identify a plurality of candidate changes to one or more of the plurality of steps of the target workflow (Kalluri [0030] “As a practical application, certain aspects and features of the present disclosure generate vector representations of communication workflows to enhance the computational efficiency of comparing various new and previously-executed communication workflows to predict the performance of the new communication workflows and to recommend tasks for completing partial communication workflows.” Kalluri provides new communication workflows/tasks to be compared to previously executed ones corresponds to identifying a plurality of candidate changes to one or more of the plurality of steps of a target workflow.); filter the plurality of candidate changes into a subset of candidate changes by identifying a first segment of the plurality of candidate changes having the context attribute (Kalluri [0064] “The partial communication workflow may be associated with one or more parameters that characterize each task of the one or more tasks of the partial communication workflow. For example, the parameters may include vocabularies for topic-modeling, content images of digital messages, and other suitable characteristics of the tasks.”; [0067] “At block 660, partial workflow predictor 250 may select a subset of the set of previously-executed partial workflows. The subset of previously-executed partial workflows that is selected may share a same structure with the partial workflow. Partial workflow predictor 250 may determine, from the subset of previously-executed partial workflows, one or more previously-executed partial workflows that are similar to the partial workflow. The similarity may be determined based on a comparison between the composite feature vector of each previously-executed partial workflow of the subset and the composite feature vector of the partial workflow or any other similarity determination technique described above with respect to FIG. 2” Kalluri provides selecting subsets from one or more previously executed workflows which include parameters corresponding to context attributes based on workflow similarity determinations and comparisons, corresponding to filter the plurality of candidate changes into a subset of candidate changes by identifying a first segment of the plurality of candidate changes having the context attribute.); identifying, from the first segment, a set of matching candidate changes (Kalluri [0048] “The workflow performance predictor 240 may then evaluate the composite feature vectors of the set of partial portions of previously-executed communication workflows to determine which partial portions are similar to the communication workflow, using the techniques described above (e.g., identifying composite feature vectors within a threshold distance from the composite feature vector of the communication workflow). Similar to the above techniques, the known task outcomes of the set of partial portions of previously-executed workflows may be combined (e.g., an average may be determined) to determine the prediction of the task outcome for the communication workflow.” Kalluri provides combining portions of previously executed workflows based on distance/similarity thresholds and a calculated average, which corresponds to identifying, from the first segment, a set of matching candidate changes.); determining whether an amount of matching candidate changes within the set exceeds a threshold number of matching candidate changes (Kalluri [0048] “The workflow performance predictor 240 may then evaluate the composite feature vectors of the set of partial portions of previously-executed communication workflows to determine which partial portions are similar to the communication workflow, using the techniques described above (e.g., identifying composite feature vectors within a threshold distance from the composite feature vector of the communication workflow). Similar to the above techniques, the known task outcomes of the set of partial portions of previously-executed workflows may be combined (e.g., an average may be determined) to determine the prediction of the task outcome for the communication workflow.” Kalluri provides combining portions of previously executed workflows based on distance/similarity thresholds and a calculated average, which also corresponds to determining whether an amount of matching candidate changes within the set exceeds a threshold number of matching candidate changes.) …identifying a second segment of the plurality of candidate changes having the at least one additional context attribute (Kalluri [0064] “The partial communication workflow may be associated with one or more parameters that characterize each task of the one or more tasks of the partial communication workflow.”; [0067] “At block 660, partial workflow predictor 250 may select a subset of the set of previously-executed partial workflows. The subset of previously-executed partial workflows that is selected may share a same structure with the partial workflow. Partial workflow predictor 250 may determine, from the subset of previously-executed partial workflows, one or more previously-executed partial workflows that are similar to the partial workflow.” Kalluri provides identifying subsets of workflow changes which include parameters corresponding to context attributes corresponding to identifying a second segment of the plurality of candidate changes having the at least one additional context attribute.); and identifying, from the second segment, additional matches to add to the set of matching candidate changes (Kalluri [0048] “The workflow performance predictor 240 may then evaluate the composite feature vectors of the set of partial portions of previously-executed communication workflows to determine which partial portions are similar to the communication workflow, using the techniques described above (e.g., identifying composite feature vectors within a threshold distance from the composite feature vector of the communication workflow). Similar to the above techniques, the known task outcomes of the set of partial portions of previously-executed workflows may be combined (e.g., an average may be determined) to determine the prediction of the task outcome for the communication workflow.” Kalluri provides a threshold distance from previous workflows for workflow comparison for implementing and determining subsets of workflow changes corresponding to identifying, from the second segment, additional matches to add to the set of matching candidate changes.) …for each candidate change of the subset of candidate changes: generate a feature vector comprising a set of features for the candidate change (Kalluri [0031] “A feature vector may be generated for each task included in a communication workflow. The feature vectors of the various tasks of the communication workflow may be concatenated to generate a composite feature vector.” Kalluri provides generating feature vectors of various tasks of the workflow corresponding to features for the candidate change.); and input the feature vector into a machine learning model that outputs an expected impact for the candidate change based on its respective feature vector (Kalluri [0031] “The composite feature vector can then be inputted into a machine-learning model to generate a prediction of a task outcome of the communication workflow. The composite feature vector may also be inputted into a machine-learning model to generate a recommendation of one or more tasks to include in the communication workflow to complete the workflow.” Kalluri provides inputting the feature vector into a machine learning model that outputs a prediction of a task outcome corresponding to an expected impact of the candidate change.), the machine learning model trained using training data including changes made to historical workflows and corresponding changes in performance of the historical workflows (Kalluri [0042] “Workflow performance predictor 240 may input the vector representation of the communication workflow into a machine-learning model (e.g., a supervised learning model trained with labeled data, such as known overall performance values of previously-executed workflows).” Kalluri provides machine learning models trained using previously executed workflows corresponding to historical workflows.); select, for a step of the plurality of steps, a candidate change associated with a highest expected impact (Kalluri [0068] “At block 670, partial workflow predictor 250 may generate a recommendation of one or more recommended tasks for completing the partial workflow. The one or more recommended tasks may be selected from one or more remaining tasks of a previously-executed partial workflow of the one or more previously-executed partial workflows that share the same structure with the partial workflow, that are determined to be similar to the partial workflow, and that has the highest performance value.” Kalluri provides selecting the modified workflow with the highest performance value corresponding to select, for a step of the plurality of steps, a candidate change associated with a highest expected impact.); and apply the selected candidate change to the target workflow by replacing the step with the candidate change (Kalluri [0068] “At block 670, partial workflow predictor 250 may generate a recommendation of one or more recommended tasks for completing the partial workflow. The one or more recommended tasks may be selected from one or more remaining tasks of a previously-executed partial workflow of the one or more previously-executed partial workflows that share the same structure with the partial workflow, that are determined to be similar to the partial workflow, and that has the highest performance value.” Kalluri provides applying selected candidate change to the target workflow.).
Kalluri fails to teach …responsive to determining that the amount of matching candidate changes within the set does not exceed the threshold: relaxing the context attribute by referencing a knowledge graph and identifying at least one additional context attribute having a node that is connected to a node for the context attribute by an edge within the knowledge graph, the context attribute relaxed from including only the node for the context attribute to including the node for the at least one additional context attribute, the node for the at least one additional context attribute one hop away from the node for the context attribute … wherein the context attribute is iteratively relaxed to further next-hop context attributes by further edges and further new additional matches are added to the set until the amount of matching candidate changes within the set exceeds the threshold, at which time the set becomes used as the subset of candidate changes.
However, Scheideler teaches …responsive to determining that the amount of matching candidate changes within the set does not exceed the threshold (Scheideler [0003] “A local sub-graph is generated as a copy of one of the sub-graphs together with a copy of a surrounding graph to the one of the sub-graphs, wherein the surrounding graph comprises a group of vertices of the knowledge graph that are each linked to the plurality of vertices of the one of the sub-graphs via less than a threshold number of edges.” Scheideler provides a threshold number of edges for graph operations, corresponding to responsive to determining that the amount of matching candidate changes within the set does not exceed the threshold.): relaxing the context attribute by referencing a knowledge graph and identifying at least one additional context attribute having a node that is connected to a node for the context attribute by an edge within the knowledge graph (Scheideler [0024] “Additionally, a parameter used for describing a sub-graph of the main knowledge graph may be subject of a modification. A change or modification may also relate to one or more vertex or vertices of the mesh, e.g., the sub-graph, by changing its content or other parameters.”; [0069] “FIG. 4 shows a block diagram of an embodiment of an example sub-graph 400 with a surrounding structure. The sub-graph comprises vertices 402 (sometimes also denoted as nodes) and edges 404, identified by a cluster algorithm, as well as edges directly connecting the vertices 402 with vertices outside the cluster. It should be noted that only a small number of vertices of the subgraphs 400 are shown with reference numerals 402 for comprehensibility reasons. The same applies to the edges 404.” Scheideler provides referencing a knowledge graph and modifying content and other parameters of sub-graphs and identifying connected nodes through clustering, corresponding to relaxing the context attribute by referencing a knowledge graph and identifying at least one additional context attribute having a node that is connected to a node for the context attribute by an edge within the knowledge graph.) the context attribute relaxed from including only the node for the context attribute to including the node for the at least one additional context attribute, the node for the at least one additional context attribute one hop away from the node for the context attribute (Scheideler [0024] “A change or modification may also relate to one or more vertex or vertices of the mesh, e.g., the sub-graph, by changing its content or other parameters.”; [0039] “In some embodiments, modifying the content of the local sub-graph may comprise one out of the group comprising modifying content of a vertex of the local sub-graph, adding and/or deleting a vertex of the local sub-graph, modifying (including adding or deleting) edges of the local sub-graph, adapting a weight factor of an edge, and a property value of the vertex..”; [0073] “Generally, the content of the vertices and the structure (including edges) of the sub-graph 400 can be changed. Local vertex content changes will be applied to the central knowledge graph when the sub-graph 400 is reinserted or reintegrated or replicated. This can be handled in the following way: the edge e.sub.jk is defined as a connection between two vertices v.sub.j and v.sub.k. In the special case, a so-called loop e.sub.jj, an edge connects only to one vertex v.sub.j. In some embodiments, loops can be handled like edges between two vertices.” Scheideler provides modifying node (vertices) content and other parameters including for adjacent nodes, including two nodes connected by an edge, which have respective content corresponding to their context attributes, corresponding to the context attribute relaxed from including only the node for the context attribute to including the node for the at least one additional context attribute, the node for the at least one additional context attribute one hop away from the node for the context attribute.), …wherein the context attribute is iteratively relaxed to further next-hop context attributes by further edges and further new additional matches are added to the set until the amount of matching candidate changes within the set exceeds the threshold (Scheideler Figure 3; [0003] “A local sub-graph is generated as a copy of one of the sub-graphs together with a copy of a surrounding graph to the one of the sub-graphs, wherein the surrounding graph comprises a group of vertices of the knowledge graph that are each linked to the plurality of vertices of the one of the sub-graphs via less than a threshold number of edges.” [0024] “Additionally, a parameter used for describing a sub-graph of the main knowledge graph may be subject of a modification. A change or modification may also relate to one or more vertex or vertices of the mesh, e.g., the sub-graph, by changing its content or other parameters.”; [0040] “One of the reasons to generate the replication trigger by the knowledge graph or a related system may be the fact the surrounding structure of a sub-graph has been modified significantly, e.g., that changes to a percentage of the vertices and edges building the surrounding structure have been made and the percentage has grown over a predetermined threshold value” Scheideler provides iterations, as shown in Figure 3, and modifying parameters and adding edges to a subgraph until a threshold number of edges is exceeded, corresponding to the context attribute is iteratively relaxed to next-hop context attributes by further edges and further new additional matches are added to the set until the amount of matching candidate changes within the set exceeds the threshold.), at which time the set becomes used as the subset of candidate changes (Scheideler [0073] “Generally, the content of the vertices and the structure (including edges) of the sub-graph 400 can be changed. Local vertex content changes will be applied to the central knowledge graph when the sub-graph 400 is reinserted or reintegrated or replicated.” Scheideler provides the sub-graph as the subset of candidate changes, which may be reinserted or reintegrated or replicated to the central graph, corresponding to at which time the set becomes used as the subset of candidate changes.).
Kalluri and Scheideler are both considered to be analogous to the claimed invention because they are in the same field of artificial intelligence and more specifically graph-based learning. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kalluri with the above teachings of Scheideler. Doing so would allow for a computationally efficient approach to generate or modify sub-graphs (Scheideler [0026] “Additionally, such devices may have limited processing and of memory capacity so that a complete copy of the initial knowledge graph to the mobile device may not be feasible. On the other side, mobile users may have been invited to make modifications to such a sub-graph of the original knowledge graph. Such a situation may represent conflicting objectives given to the limitations in bandwidth, processing power, and memory. An objective of the present disclosure may be in solving such conflict.”).
Regarding claim 2, Kalluri in view of Scheideler teaches the non-transitory computer readable storage medium of claim 1 as discussed above in the rejection of claim 1, wherein instructions to identify the plurality of candidate changes further cause the one or more processors to: identify a plurality of candidate workflows similar to the target workflow (Kalluri [0045] “Within the set of previously-executed communication workflows, the workflow performance predictor 240 may identify one or more previously-executed communication workflows that are similar to the communication workflow.” Kalluri provides identifying similarities between workflows.); and identify a plurality of historical changes previously made to the plurality of candidate workflows as the plurality of candidate changes (Kalluri [0049] “The partial workflow predictor 250 may determine partial portions of previously-executed communication workflows that are similar to the new partial communication workflow based on a comparison of composite feature vectors in a domain space, as described above” Kalluri provides determining workflow similarities based on vector comparisons corresponding to the plurality of historical changes previously made to the plurality of candidate workflows as the plurality of candidate changes.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 3, Kalluri in view of Scheideler teaches the non-transitory computer readable storage medium of claim 2 as discussed above in the rejection of claim 2, wherein the target workflow is associated with a first context and a candidate workflow of the plurality of candidate workflows is associated with a second context that has a strength of similarity to the first context greater than a threshold strength (Kalluri [0045] “For example, the previously-executed communication workflows of a given structure for which the corresponding composite feature vector is within a threshold distance from the composite feature vector of the communication workflow may be determined as similar to the communication workflow. In some examples, the task outcome of the communication workflow may be predicted based on a combination (e.g., an average, a weighted average, and so on) of the known task outcomes of the previously-executed communication workflows that are determined to be similar to the communication workflow.” Kalluri provides comparing feature vectors of each of the previously executed workflows and determining if they are within a threshold distance from the composite feature vector corresponding to a strength of similarity between two contexts greater than a threshold strength.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 2.
Regarding claim 5, Kalluri in view of Scheideler teaches the non-transitory computer readable storage medium of claim 2 as discussed above in the rejection of claim 2, wherein the target workflow is associated with a first structure having a plurality of steps in a predefined order (Kalluri [0034] “In some implementations, client system 130 may define one or more workflows for communicating with user devices. A communication workflow may be an orchestrated sequence of one or more tasks, such as an MCO.” Kalluri provides a first workflow structure having a plurality of steps in an orchestrated sequence corresponding to a predefined order.) and each of the plurality of candidate workflows is associated with a structure with a number of structural changes relative to the first structure less than a threshold number of structural changes (Kalluri [0045] “Similarity may be measured in the multi-dimensional space of the composite feature vectors of the previously-executed communication workflows. For example, the previously-executed communication workflows of a given structure for which the corresponding composite feature vector is within a threshold distance from the composite feature vector of the communication workflow may be determined as similar to the communication workflow.” Kalluri provides a threshold for given structures of previously-executed workflows based on similarity which corresponds to each of the plurality of candidate workflows is associated with a structure with a number of structural changes relative to the first structure less than a threshold number of structural changes.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 2.
Regarding claim 6, Kalluri in view of Scheideler teaches the non-transitory computer readable storage medium of claim 1 as discussed above in the rejection of claim 1, wherein the instructions further cause the one or more processors to: responsive to applying the selected candidate change to the target workflow, determine corresponding changes in performance (Kalluri [0030] “As a practical application, certain aspects and features of the present disclosure generate vector representations of communication workflows to enhance the computational efficiency of comparing various new and previously-executed communication workflows to predict the performance of the new communication workflows and to recommend tasks for completing partial communication workflows.” Kalluri provides predicting performance of new workflows corresponding to determining changes in performance to candidate changes to a workflow); based on the changes in performance, determine whether the selected candidate change improves performance of the target workflow (Kalluri [0042] “The machine-learning model may be a supervised, semi-supervised, or unsupervised (e.g., k-means clustering) models. The output of the machine-learning model may represent a prediction of a performance of the communication workflow. In some examples, the overall performance of a communication workflow may be represented by a task outcome, which represents the rate of target user-performed actions in response to receiving a communication (e.g., a conversion rate, a click rate of selecting a link contained in a digital message, an open rate of opening a webpage from a link included in the communication, etc.).” Kalluri provides predicting rate of target user-performed actions in response to receiving a workflow communication corresponding to determining whether the candidate changes improve performance of a target workflow.); responsive to determine that the selected candidate change improves the performance of the target workflow, keep the selected candidate change (Kalluri [0049] “The partial workflow predictor 250 may determine partial portions of previously-executed communication workflows that are similar to the new partial communication workflow based on a comparison of composite feature vectors in a domain space, as described above. The partial workflow predictor 250 may rank the set of partial portions of previously-executed communication workflows that are similar to the new partial communication workflow in decreasing order based on the known task outcomes of the previously-executed communication workflows. The partial workflow predictor 250 may then recommend the full previously-executed communication workflows of the one or more partial portions of previously-executed communication workflows that are ranked the highest.” Kalluri provides ranking the similarity of previously performed/successful workflows and using the portions which are ranked the highest corresponding to keeping the selecting candidate change based on improvements to performance ([0048] “The workflow performance predictor 240 may identify a set of partial portions of previously-executed communication workflows that have the same structure as the communication workflow.”).); and responsive to determining that the selected candidate change does not improve the performance of the target workflow, remove the selected candidate change (Kalluri [0049] “The partial workflow predictor 250 may determine partial portions of previously-executed communication workflows that are similar to the new partial communication workflow based on a comparison of composite feature vectors in a domain space, as described above. The partial workflow predictor 250 may rank the set of partial portions of previously-executed communication workflows that are similar to the new partial communication workflow in decreasing order based on the known task outcomes of the previously-executed communication workflows. The partial workflow predictor 250 may then recommend the full previously-executed communication workflows of the one or more partial portions of previously-executed communication workflows that are ranked the highest.” Kalluri provides ranking the similarity of previously performed/successful workflows and not using the portions which are ranked the lowest corresponding to removing the selecting candidate change based on deteriorations to performance ([0048] “The workflow performance predictor 240 may identify a set of partial portions of previously-executed communication workflows that have the same structure as the communication workflow.”).).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 7, Kalluri in view of Scheideler teaches the non-transitory computer readable storage medium of claim 1 as discussed above in the rejection of claim 1, wherein the feature vector associated with a candidate change previously made to a candidate workflow includes one or more of: a type of action associated with the candidate change, a timing associated with the candidate change, an order of a step to which the candidate change was applied within a corresponding candidate workflow, historical impact associated with the candidate change, and a number of times the candidate change was tested (Kalluri [0031] “A feature vector may be generated for each task included in a communication workflow. The feature vectors of the various tasks of the communication workflow may be concatenated to generate a composite feature vector. The composite feature vector can then be inputted into a machine-learning model to generate a prediction of a task outcome of the communication workflow.” Kalluri provides the feature vector includes tasks corresponding to the type of action associated with the candidate change.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 8, it is the method embodiment of claim 1 with similar limitations to claim 1 and is rejected using the same reasoning found above in the rejection of claim 1.
Regarding claim 9, the rejection of claim 8 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 2.
Regarding claim 10, the rejection of claim 9 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 3.
Regarding claim 12, the rejection of claim 9 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 5.
Regarding claim 13, the rejection of claim 8 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 6.
Regarding claim 14, the rejection of claim 8 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 7.
Regarding claim 15, it is the system embodiment of claim 1 with similar limitations to claim 1 and is rejected using the same reasoning found above in the rejection of claim 1. Further, Kalluri teaches a system comprising: one or more processors (Kalluri [0112] “One or more processors may be included in processing unit 1004.” Kalluri provides one or more processors.); and a non-transitory computer-readable medium comprising computer program instructions (Kalluri [0011] “Other embodiments of this aspect include corresponding computer systems, apparatus, and executable code stored on non-transitory computer-readable storage medium, each configured to perform the actions of the methods.” Kalluri provides a non-transitory computer readable storage medium comprising stored instructions.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 16, the rejection of claim 15 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 2.
Regarding claim 17, the rejection of claim 16 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 3.
Regarding claim 19, the rejection of claim 16 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 5.
Regarding claim 20, the rejection of claim 15 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler for the same reasons disclosed above in the rejection of claim 6.
Claims 4, 11, and 18 are rejected under 35 U.S.C. 103 as being anticipated by Kalluri et al. (U.S. Patent Publication No. 2021/0264202) (“Kalluri”) in view of Scheideler et al. (U.S. Patent Publication No. 2019/0294733) (“Scheideler”) in further view of Burhanuddin et al. (U.S. Patent Publication No. 2018/0330248) (“Burhanuddin”).
Regarding claim 4, Kalluri in view of Scheideler teaches the non-transitory computer readable storage medium of claim 3 as discussed above in the rejection of claim 3, but fails to teach wherein the first context is connected to the second context by a weighted edge representing the strength of similarity between the first context and the second context in a context association graph.
However, Burhanuddin teaches wherein the first context is connected to the second context by a weighted edge representing the strength of similarity between the first context and the second context in a context association graph (Burhanuddin [0072] “As such, a user navigation graph for a user can be a weighted directed graph where each node signifies an individual report viewed by that user, and each directed edge between the nodes of the graph signify that the user transitioned between nodes with probability being greater than zero. The weight of such edges reflects the frequency of transition between two such nodes. For example, if a user transitions from a product webpage report to the product sales report, this will be reflected by the weight of the edge between the node representing the product webpage report and the node representing the product sales report. Thus, this weight represents the historic frequency of transitions from one node to another node.” Burhanuddin provides a weighted edge graph where nodes corresponding to contexts are connected and where the weighted edge represents frequency of transitions between nodes corresponding to a strength of similarity between two contexts.).
Kalluri, Scheideler and Burhanuddin are all considered to be analogous to the claimed invention because they are in the same field of artificial intelligence and more specifically workflow management/processes and graph operations. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kalluri in view of Scheideler with the above teachings of Burhanuddin. Doing so would allow user intent to be inferred by analyzing user interaction history to then make recommendations to a user (Burhanuddin [0072] “As previously described, user intent can be inferred utilizing user interaction history with an analytics system, such as one or more reports presented to a user via an analytics program. As such, user interactions associated with analytics data (e.g., analytics reports) can be tracked and collected. In one embodiment, the intent engine 412 can compile user history by generating a user navigation graph for a user. A user navigation graph depicts analytics data (e.g., reports) that a user has visited to understand the progression of how the user views reports and types of data during an analysis session. In this way, a user navigation graph can be unique or tailored for each user of, for example, analytics system 402. Creating such a graph allows the recommendation system to incorporate a frequency-based recommendation aspect when making recommendations to a user.”).
Regarding claim 11, the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler in further view of Burhanuddin for the same reasons disclosed above in the rejection of claim 4.
Regarding claim 18, the rejection of claim 17 is incorporated herein. Further, the limitations in this claim are taught by Kalluri in view of Scheideler in further view of Burhanuddin for the same reasons disclosed above in the rejection of claim 4.
Response to Arguments
Regarding the rejection applied under 35 U.S.C. 112, Applicant’s amendments overcome the rejection.
Regarding the rejection applied under 35 U.S.C. 101, Applicant firstly asserts that the claims recite a filtering process to obtain a subset of candidate changes for which an expected impact is determined, which involves specifically iteratively relaxing a context attribute and looking only in segments having the context attributes for matching candidates. Applicant further asserts that the claims are similar to those in Desjardins, and therefore positively recite a technical solution to the technical problem of machine learning inefficiencies in isolating relevant data for machine learning models in scenarios where volumes of candidate data are massive (“Remarks”, Pages 13-14). Applicant further asserts that the solution of iteratively relaxing context attributes until a sufficient amount of relevant data is identified for use with a machine learning model to determine expected impact integrates the claimed subject matter into a practical application (“Remarks”, Page 14). Applicant further asserts that the features achieve an efficient tool for improving workflows (“Remarks”, Page 14).
However, the MPEP states that “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer does not integrate a judicial exception into a practical application or provide an inventive concept.” MPEP 21060.5(f). Further, even if the claims did recite an improvement, it would be an improvement in the abstract idea of selecting a candidate change associated with a highest expected impact, which as discussed above in the 35 U.S.C. 101 rejection of claim 1 above, is an abstract idea. As recited in the MPEP, an improvement in the abstract idea itself is not an improvement in technology. MPEP 2106.05(a). Further, the claims are not similar to those in Desjardins. Therefore, the claims are rejected under 35 U.S.C. 101.
Regarding the rejection applied under 35 U.S.C. 103, Applicant asserts that the context attribute being relaxed as claimed does not involve changes to the knowledge graph, and instead involves adding context attributes from the knowledge graph (“Remarks”, Page 15). However, as discussed in paragraph [0030] of Scheideler, the sub-graph may be separated from the initial, large knowledge graph by moving it to another partition on the same server (or a different virtual or physical server) and allowing a restricted access to only a portion (i.e., the sub-graph) of the knowledge graph, thus providing a separate subset without changing the original knowledge graph. Further, as discussed in [0034], the method may also comprise locking one of the sub-graphs, in particular, the vertices and edges, in the knowledge graph. This may prevent the main knowledge graph from being modified in portions relating to the sub-graph if a local copy may have been generated. Therefore, Scheideler teaches not modifying the knowledge graph and instead referencing the knowledge graph.
Therefore, as written, the claims remain rejected under 35 U.S.C. 101 and 35 U.S.C 103.
Conclusion
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/KURT NICHOLAS PRESSLY/Examiner, Art Unit 2125
/KAMRAN AFSHAR/Supervisory Patent Examiner, Art Unit 2125