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 .
DETAILED ACTION
The instant application having Application No. 17837010 has a total of 10 claims pending in the application.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: use-case configure module, service builder module, service manage module, service consumption module, specification information processing module, an automated probabilistic forecasting module, an automated forecasted factor and objective factor relationship module, a reward or penalty estimation module, a forecast adjustment recommendation generating module, a probabilistic optimization module, action tracking module, and a machine learning model training module, in claims 1 and 10.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claim 1 is a process type claim. Claim 10 is a machine type claim. Therefore, claims 1-10 are directed to either a process, machine, manufacture or composition of matter.
As per claim 1,
2A Prong 1:
“manage probabilistic forecast management resources to provide a probabilistic forecast management service to one or more client…” A risk analysis agent mentally or with pencil and paper manages their time and effort to provide analysis to a client.
“select factors of interest and modeling the probabilistic forecast management service” The risk analysis agent mentally or with pencil and paper selects factors of interest for their analysis.
“Assembling, validating and publishing the probabilistic forecast management service” The risk analysis agent mentally or with pencil and paper assembles, validates, and provides their work publicly to their clients.
“generate a recommendation for adjusting an existing forecast of at least one forecasted factor of a factor group” The risk analysis agent mentally or with pencil and paper recommends a change to a forecasting model in order to get a more accurate outcome.
“identifying quantified probabilistic values… to identify an emerging signal indicative of an impact with respect to a factor” The risk analysis agent mentally or with pencil and paper identifies relevant probabilistic values and monitor them for data impacting the risk analysis system
“Using historical data of a forecasted factor and historical data of at least one factor group associated with the use case” The risk agent mentally or with pencil and paper considers historical data of the forecasted factor and factor group in relation to their predictions for the forecasting.
“Using external data, the historical data of a forecasted factor, historical data of an objective factor, and historical data of at least one factor group associated with the use case” The risk agent mentally or with pencil and paper considers historical data of the forecasted factor, objective factor, and factor group in relation to their predictions for the forecasting.
“Making one or more adjustments to the existing forecast” The risk analysis agent mentally or with pencil and paper makes adjustments to the forecast based on modeling.
“Determining an optimization model using a simulation based optimization, wherein the simulation is run on at least one adjustment of the existing forecast of the forecasted factor based on the probabilistic forecasting model and the relationship model… wherein the at least one adjustment includes an amount of return gained on the adjustment and an amount of risk undertaken in the adjustment, wherein one or more simulation actions induces a state” The risk agent mentally or with pencil and paper performs the analysis by adjusting return and risk related to the target of the analysis, and determines the current state of the analysis.
“Tracking the one or more adjustments made in the use-case based on a recommendation to enable feedback-based learning…” The risk analysis agent mentally or with pencil and paper considers feedback based on their previous results of their analysis and uses it to improve their analysis.
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
Probabilistic forecast management platform, client devices, a network, a repository (mere instructions to apply the exception using a generic computer component);
Automated system of machine learning models, “updating real-time recommendations machine learning (ML) models”, “utilizing deep learning and machine learning”, A first automated system of machine learning models, a second automated system of machine learning models, using a third automated system of machine learning models, at least one machine learning model of the at least one of the first automated system and the second automated system, “Trains one or more machine learning models using data available in the repository” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: Claims denote numerous generic machine learning models and generic machine learning methods, but includes no limitations, relationships, or details beyond generic, off the shelf machine learning models and generic training of said generic models.
“capturing a specification information of a use-case for which a probabilistic forecast management service is created, the specification information including internal data of the use-case and a meta-data model applicable for the use-case with which the one or more client devices is associated”, “:capturing one or more possible actions from the one or more client devices and operations constraints of the use case”, “receiving the specification information of the use case from the use-case configure module”, “receiving the published probabilistic forecast management service from the service builder module”, receiving specification information and internal data of a probabilistic forecast management service from a repository of the probabilistic forecast management platform”, “providing one or more inputs to a probabilistic optimization module” (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)).
“which is recorded by an agent” (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
Probabilistic forecast management platform, client devices, a network, a repository (mere instructions to apply the exception using a generic computer component)
Automated system of machine learning models, “updating real-time recommendations machine learning (ML) models”, “utilizing deep learning and machine learning”, A first automated system of machine learning models, a second automated system of machine learning models, using a third automated system of machine learning models, at least one machine learning model of the at least one of the first automated system and the second automated system, “Trains one or more machine learning models using data available in the repository” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: Claims denote numerous generic machine learning models and generic machine learning methods, but includes no limitations, relationships, or details beyond generic, off the shelf machine learning models and generic training of said generic models.
“capturing a specification information of a use-case for which a probabilistic forecast management service is created, the specification information including internal data of the use-case and a meta-data model applicable for the use-case with which the one or more client devices is associated”, “:capturing one or more possible actions from the one or more client devices and operations constraints of the use case”, “receiving the specification information of the use case from the use-case configure module”, “receiving the published probabilistic forecast management service from the service builder module”, receiving specification information and internal data of a probabilistic forecast management service from a repository of the probabilistic forecast management platform”, “providing one or more inputs to a probabilistic optimization module” (MPEP 2106.05(d)(II) indicate that merely “receiving or transmitting data” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed receiving and capturing steps are well-understood, routine, conventional activity is supported under Berkheimer).
“which is recorded by an agent” (MPEP 2106.05(d)(II) indicate that merely “storing and retrieving data” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed recording step is well-understood, routine, conventional activity is supported under Berkheimer).
As per claim 2, this claim contains additional mental steps and generic hardware to claim 1, and is rejected for similar reasons.
As per claim 3, this claim contains additional mental steps and generic machine learning model aspects similar to claim 1, and is rejected for similar reasons.
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
“a server”, (mere instructions to apply the exception using a generic computer component);
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
“a server”, (mere instructions to apply the exception using a generic computer component)
As per claim 5-6, this claim contains similar mental steps to claim 1 and is rejected for similar reasons to claim 1.
As per claim 7-8, this claim contains similar generic machine learning models to claim 1, and is rejected for similar reasons.
As per claim 9, this claim contains similar mental steps and generic machine learning aspects to claim 1, and is rejected for similar reasons.
As per claim 10,
2A Prong 1:
“manage probabilistic forecast management resources to provide a probabilistic forecast management service to one or more client…” A risk analysis agent mentally or with pencil and paper manages their time and effort to provide analysis to a client.
“Specify meta-data model of the use-case” The risk analysis agent mentally or with pencil and paper denotes which meta data model to use for their situation.
“select factors of interest and models the probabilistic forecast management service” The risk analysis agent mentally or with pencil and paper selects factors of interest for their analysis.
“Assembles, validates and publishes the probabilistic forecast management service” The risk analysis agent mentally or with pencil and paper assembles, validates, and provides their work publicly to their clients.
“generate a recommendation for adjusting an existing forecast of at least one forecasted factor of a factor group” The risk analysis agent mentally or with pencil and paper recommends a change to a forecasting model in order to get a more accurate outcome.
“identifies quantified probabilistic values… to identify an emerging signal indicative of an impact with respect to a factor” The risk analysis agent mentally or with pencil and paper identifies relevant probabilistic values and monitor them for data impacting the risk analysis system
“Using historical data of a forecasted factor and historical data of at least one factor group associated with the use case” The risk agent mentally or with pencil and paper considers historical data of the forecasted factor and factor group in relation to their predictions for the forecasting.
“Using external data, the historical data of a forecasted factor, historical data of an objective factor, and historical data of at least one factor group associated with the use case” The risk agent mentally or with pencil and paper considers historical data of the forecasted factor, objective factor, and factor group in relation to their predictions for the forecasting.
“Making one or more adjustments to the existing forecast” The risk analysis agent mentally or with pencil and paper makes adjustments to the forecast based on modeling.
“Determines an optimization model using a simulation based optimization, wherein the simulation is run on at least one adjustment of the existing forecast of the forecasted factor based on the probabilistic forecasting model and the relationship model… wherein the at least one adjustment includes an amount of return gained on said adjustment and an amount of risk undertaken in said adjustment” The risk agent mentally or with pencil and paper performs the analysis by adjusting return and risk related to the target of the analysis, and determines the current state of the analysis.
“makes one or more adjustments to the existing forecast” The risk agent mentally or with pencil and paper performs the analysis by adjusting return and risk related to the target of the analysis, and determines the current state of the analysis.
“one or more actions induces a state” The risk agent mentally or with pencil and paper performs the analysis by adjusting return and risk related to the target of the analysis, and determines the current state of the analysis.
“Tracking the one or more adjustments made in the use-case based on a recommendation to enable feedback-based learning…” The risk analysis agent mentally or with pencil and paper considers feedback based on their previous results of their analysis and uses it to improve their analysis.
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
One or more external data sources, Probabilistic forecast management server, Probabilistic forecast management platform, client devices, a network, a repository (mere instructions to apply the exception using a generic computer component);
Automated system of machine learning models, “updates real-time recommendations machine learning (ML) models”, “utilizing deep learning and machine learning”, A first automated system of machine learning models, a second automated system of machine learning models, using a third automated system of machine learning models, at least one machine learning model of the at least one of the first automated system and the second automated system, “Trains one or more machine learning models using data available in the repository” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: Claims denote numerous generic machine learning models and generic machine learning methods, but includes no limitations, relationships, or details beyond generic, off the shelf machine learning models and generic training of said generic models.
“captures a specification information of the use-case for which the probabilistic forecast management service is created, the specification information including internal data of the use-case and the meta-data model applicable for the use-case”, “captures one or more possible actions from the one or more client devices and operations constraints of the use case”, “receives the specification information of the use case from the use-case configure module”, “receives the published probabilistic forecast management service from the service builder module”, “receives specification information and internal data of a probabilistic forecast management service from a repository of the probabilistic forecast management platform”, “provides one or more inputs to a probabilistic optimization module” (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)).
“which is recorded by an agent” (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)).
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
Probabilistic forecast management platform, client devices, a network, a repository (mere instructions to apply the exception using a generic computer component)
Automated system of machine learning models, “updating real-time recommendations machine learning (ML) models”, “utilizing deep learning and machine learning”, A first automated system of machine learning models, a second automated system of machine learning models, using a third automated system of machine learning models, at least one machine learning model of the at least one of the first automated system and the second automated system, “Trains one or more machine learning models using data available in the repository” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: Claims denote numerous generic machine learning models and generic machine learning methods, but includes no limitations, relationships, or details beyond generic, off the shelf machine learning models and generic training of said generic models.
“capturing a specification information of a use-case for which a probabilistic forecast management service is created, the specification information including internal data of the use-case and a meta-data model applicable for the use-case with which the one or more client devices is associated”, “:capturing one or more possible actions from the one or more client devices and operations constraints of the use case”, “receiving the specification information of the use case from the use-case configure module”, “receiving the published probabilistic forecast management service from the service builder module”, receiving specification information and internal data of a probabilistic forecast management service from a repository of the probabilistic forecast management platform”, “providing one or more inputs to a probabilistic optimization module” (MPEP 2106.05(d)(II) indicate that merely “receiving or transmitting data” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed receiving and capturing steps are well-understood, routine, conventional activity is supported under Berkheimer).
“which is recorded by an agent” (MPEP 2106.05(d)(II) indicate that merely “storing and retrieving data” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed recording step is well-understood, routine, conventional activity is supported under Berkheimer).
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-10 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
As per claim 1, this claim calls for “using the probabilistic optimization module within the forecast adjustment recommendation generating module of the probabilistic forecast management environment, determining an optimization model using a simulation based optimization, wherein the simulation is run on at least one adjustment of the existing forecast of the forecasted factor based on the probabilistic forecasting model and the relationship model using a third automated system of machine learning models, wherein the at least one adjustment includes an amount of return gained on the adjustment and an amount of risk undertaken in the adjustment, wherein the one or more simulation actions induces a state which is recorded by an agent in the reward or penalty estimation module” However, the specification does not support this limitation. The claim calls for the probabilistic optimization module to perform the tasks above, but this not supported by the specification. The probabilistic optimization module is described in paragraphs 0071-0072 and briefly mentioned in paragraph 0044, however none of these paragraphs discuss these actions.
These actions are discussed in paragraph 0073, but have no relationship to the probabilistic optimization model. This causes the limitation to be new matter, and therefore rejected under U.S.C. 112(a).
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(a).
As per claim 10, this claim calls for “a forecast adjustment recommendation generating module comprising (1) a probabilistic optimization module that determines an optimization model using a simulation based optimization, wherein the simulation is run on at least one adjustment of the existing forecast of the forecasted factor based on the probabilistic forecasting model, and the relationship model using a third automated system of machine learning models, wherein the at leas tone adjustment includes an amount of return based on said adjustment and an amount of risk undertaken in said adjustment.” However, the specification does not support this limitation. The claim calls for the probabilistic optimization module to perform the tasks above, but this not supported by the specification. The probabilistic optimization module is described in paragraphs 0071-0072 and briefly mentioned in paragraph 0044, however none of these paragraphs discuss these actions.
These actions are discussed in paragraph 0073, but have no relationship to the probabilistic optimization model. This causes the limitation to be new matter, and therefore rejected under U.S.C. 112(a).
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 1-10 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.
As per claim 1, this claim calls for “modeling the probabilistic forecast management service” Publishing the probabilistic forecast management service” (Pg.1, L21, Pg.2. L1).
Claim 1 also contains “provide a probabilistic forecast management service to one or more client devices…” (Pg.1, Line 15-16), and “capturing a specification information of a use-case for which a probabilistic forecast management service is created” (Pg.1, L17-18), and it is unclear which “a probabilistic forecast management service” this limitation is referring to. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
As per claim 1, this claim calls for “publishing the probabilistic forecast management service” ” (Pg.2, L5-6).
Claim 1 also contains “provide a probabilistic forecast management service to one or more client devices…” (Pg.1, Line 15-16), and “capturing a specification information of a use-case for which a probabilistic forecast management service is created” (Pg.1, L17-18), and it is unclear which “a probabilistic forecast management service” this limitation is referring to. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
As per claim 1, this claim calls for “facilitate usage of the probabilistic forecast management service to the one or more client devices ” (Pg.2, L12-13).
Claim 1 also contains “provide a probabilistic forecast management service to one or more client devices…” (Pg.1, Line 15-16), and “capturing a specification information of a use-case for which a probabilistic forecast management service is created” (Pg.1, L17-18), and it is unclear which “a probabilistic forecast management service” this limitation is referring to. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
Examiners note: Claim 1 also contains a third “a probabilistic forecast management service” in Pg.2 L16-17, but there is no corresponding “the probabilistic forecast management service” to cause a 112(b) for that limitation. Any amendments that lead to another “the probabilistic forecast management service” after this limitation would lead to another rejection under U.S.C. 112(b).
As per claim 1, this claim calls for “at least one adjustment of the existing forecast of the forecasted factor…” (pg.3, L14-15).
Claim 1 also contains “at least one forecasted factor of a factor group” (Pg.2, Line 9-10), “historical data of a forecasted factor” (Pg.2 L22-Pg.3 L1) and “the historical data of a forecasted factor” (Pg.3, L5), and it is unclear which “forecasted factor” this limitation is referring to. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
As per claim 1, this claim contains “the probabilistic forecast management environment” (pg.3, L12-13).
Claim 1 also contains “a probabilistic forecast management environment” (pg.2, L15-16), and “a forecast adjustment recommendation generating module of a probabilistic forecast management environment” (Pg.3, L8). It is unclear which “a probabilistic forecast management environment is being referred to. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
As per claim 1, This claim contains the phrase “the probabilistic forecasting model” in Pg.3, L15. There is insufficient antecedent basis for this limitation. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
As per claim 1, This claim contains the phrase “the relationship model” in Pg.3, L15. There is insufficient antecedent basis for this limitation. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
As per claim 1, this claim contains “the at least one adjustment” and “the adjustment” in Pg.3 line 16-17.
Claim 1 also contains “making one or more adjustments” (pg.3, L9), and “at least one adjustment” (Pg.3, L14). It is unclear which “adjustment” is being referred to. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
As per claim 2, this claim contains “an existing forecast of the forecasted factor” and “wherein the existing forecast of the forecasted factor” in line 3-4.
Claim 1 also contains “at least one forecasted factor of a factor group” (Pg.2, Line 9-10), “historical data of a forecasted factor” (Pg.2 L22-Pg.3 L1) and “the historical data of a forecasted factor” (Pg.3, L5), and it is unclear which “forecasted factor” this limitation is referring to. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claim 6, this claim calls for “the objective factor” in line 1 of the claim. Independent claim 1 has “An objective factor” (Pg.1, Line 2), and “historical data of an objective factor” (Pg.3, L5-6). It is unclear what “objective factor” “the objective factor” in claim 6 is referring to. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
As per claim 10, this claim contains “at least one adjustment of the existing forecast of the forecasted factor.”
Claim 10 also contains: “at least one forecasted factor of a factor group” (Pg.2, L7), “using historical data of a forecasted factor” (pg.2, L21-22), and “The historical data of a forecasted factor” (Pg.3, L2). It is unclear what “forecasted factor” this limitation is referring to. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
As per claim 10, This claim contains the phrase “the probabilistic forecasting model” in Pg.3, L7-8. There is insufficient antecedent basis for this limitation. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claim 10, This claim contains the phrase “the relationship model” in Pg.3, L8. There is insufficient antecedent basis for this limitation. This causes the claim to be unclear, and therefore rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention
As per claims 1 and 10, Claim limitations: use-case configure module, service builder module, service manage module, service consumption module, specification information processing module, an automated probabilistic forecasting module, an automated forecasted factor and objective factor relationship module, a reward or penalty estimation module, a forecast adjustment recommendation generating module, a probabilistic optimization module, action tracking module, and a machine learning model training module, invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The Examiner was not able to find any described structure for these various modules. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
As per claims 2-9, these claims are rejected as being dependent on a claim rejected under U.S.C. 112(b) for failing to particularly point out and claim the intended invention.
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Allowable Subject Matter
As per claims 1 and 10 and their respective dependent claims (2-3, 5-9), these claims would be found allowable over the prior art if the rejections under 112(b) can be corrected and the limitations rejected under 112(a) can be shown to be supported by the specification. While no particular limitation has been found to be novel, the combination of limitations found within the independent claims and the particular connections among the various modules would be non-obvious to one of ordinary skill in the art at the time of filing.
Response to Arguments
Applicant's arguments with respect to claims 1-10 have been considered but are moot in view of the new ground(s) of rejection.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BEN M RIFKIN whose telephone number is (571)272-9768. The examiner can normally be reached Monday-Friday 9 am - 5 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alexey Shmatov can be reached at (571) 270-3428. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BEN M RIFKIN/Primary Examiner, Art Unit 2123