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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 08/20/2026 has been entered.
Status of the Claims
Claims 1-2, 5-12, and 15-27 are currently pending and have been considered by the Examiner.
Claim Objections
Claims 1, 23, 25, and 27 are objected to because of the following informalities: In claim 1, line 19, Examiner suggests deleting “and” before the comma.
In claim 23, line 4, the spelling for “volume” should be corrected. Claims 25 and 27 contain the same minor informality. Appropriate correction is required.
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 1-2, 5-12, and 15-27 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.
The term “similar” in claim 1, line 27 is a relative term which renders the claim indefinite. The term “similar” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The term “similar” is a subjective term under MPEP 2173.05(b), subsection IV because the claim and written disclosure do not provide a standard for ascertaining whether a given condition is similar to a plurality of conditions. The Examiner treats similar conditions as conditions that share any characteristics. Claim 5 is rendered indefinite for reciting the same relative term in line 3.
In claim 1 on page 3, line 5, the term “most” is a relative term which renders the claim indefinite. The term “most” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The term “most” is a subjective term under MPEP 2173.05 subsection IV because the specification fails to supply an objective standard for measuring the scope of the term. Examiner treats the limitation “most of features” to mean a predetermined amount of features.
Claims 2, 5-10, and 22-23 are rejected for failing to cure the deficiencies of claim 1.
Claim 8 is rendered indefinite for the following reasons. Claim 1 recites “a number of data points of the subset of the data points being limited based on the proximity value” in lines 25-26. It is unclear if claim 8 is redundant with claim 1. It is unclear if “a number of the subset of the data points” in claim 8 is the same as “a number of data points of the subset” from claim 1. It is unclear if “a proximity value” in claim 8 is the same as the proximity value from claim 1. Examiner treats claim 8 as being redundant with claim 1.
Claim 10 is rendered indefinite for the following reasons. It is unclear whether “the number of the subset of the data points” has proper antecedent basis. Specifically, claim 1 recites “identifying a subset of the data points closest to the location of the new data point based on a proximity value, … a number of data points of the subset of the data points being limited based on the proximity value” in lines 24-26. It is unclear if “a number of data points” from claim 1 provides proper antecedent basis for “the number of the subset of the data points” in claim 10. Additionally, claim 10 is not grammatically correct, and it is unclear whether “information” is the subject of the verb “is analyzed” in line 3. Examiner treats claim 10 to mean “information associated with the new data point and the subset of data points is analyzed using statistical measures to determine correlations.”
Claim 11 recites the same indefinite limitation as claim 1 and is therefore rejected for at least the same reasons.
Claims 12, 15-20, and 24-25 are rejected for failing to cure the deficiencies of claim 11.
Claims 18 and 20 recite the same indefinite limitation as claims 8 and 10, respectively, and are therefore rejected for at least the same reasons.
Claim 21 recites the same indefinite limitation as claim 1 and is therefore rejected for at least the same reasons.
Claims 26-27 are rejected for failing to cure the deficiencies of claim 21.
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 1-2, 5-12, and 15-27 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1-2, 5-10, and 22-23 each recites a product. Claims 11-12, 15-20, and 24-25 each recites a method. Claims 21 and 26-27 each recites a system comprising a processor. A product, a method, and a system each fall within one of the four statutory categories of patent eligible subject matter.
Claim 1
Step 2A Prong 1: The entire limitation “generating a topological representation using the features of the received data set and topological data analysis, the topological representation being generated using at least one metric-lens combination of a subset of metric-lens combinations, the topological representation including a plurality of nodes, each of the nodes having one or more data points from the data set as members, at least two nodes of the plurality of nodes being connected by an edge if the at least two nodes share at least one data point from the data set as members, each of the one or more data points from the data set being identified by a date, each of the one or more data points including the features indicating a plurality of conditions associated with that date” amounts to a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. In the specification, paragraph [0142] discloses generating a topological representation, and a human could draw a graph of nodes and edges such as the one depicted in Fig. 9 on a piece of paper. A human could perform topological data analysis based on data having features.
Determining distances between the new data point and at least some of the one or more data points from the data set based on features of the new data point and, the features of the at least some of the one or more data points, and the at least one metric-lens combination is a mathematical calculation. Specification paragraph [0050] discloses calculating a distance using the n-dimensional Euclidean distance function.
Locating the new data point in a location relative to one or more of the nodes in the topological representation using the distances between the new data point and the at least some of the one or more data points from the data set is a judgement mental process based on a mathematical calculation which can reasonably be performed in the human mind with the aid of pencil and paper. Specification paragraphs [0197], [0241] disclose placing a new data point on the graph by using a distance metric, which a human can perform.
Identifying a subset of the data points closest to the location of the new data point based on a proximity value, the proximity value being based the determined distances, a number of data points of the subset of the data points being limited based on the proximity value, the subset of the data points closest to the location of the new data point including at least one similar condition of the plurality of conditions is an observation and judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. Specification paragraphs [0198], [0241] disclose how a human could observe distances between original data points and the new data point, and group the new data point.
The limitation “comparing the features of the subset of the data points to at least some of the features of the new data point to identify a market regime associated with the new data point, the market regime including multiple conditions that match the new data point features, the conditions encapsulating financial market behavior, the market regime indicating a set of financial market and economic factors of at least most of the features of the subset of the data points as influencing factors of data point factors of the new data point, one or more asset prices of the data points being at least one of the influencing factors based on the market regime, one or more asset returns of the data points being at least another of the influencing factors based on the market regime, the market regime being one of a plurality of different market regimes that indicate different sets of financial market and economic factors, each market regime indicating different sets of financial market and economic factors from other market regimes of the plurality of market regimes” is an observation and judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human could compare features of the new data point to features of data points in the grouping, and identify a market regime associated with the new data point.
The limitation “determining directional signals of the influencing factors based on the market regime to determine a degree of impact on the data point factors of the new data point, the directional signals including at least one of an increase or decrease of the one or more asset prices and an increase or decrease of the one or more asset returns over one or more predetermined periods of time” is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. Specification paragraph [0267] discloses predicting directional signals of +1 (up) or -1 (down), and a human could predict whether an asset price will increase or decrease.
The limitation “generating a forecast for the new date associated with the new data point, the forecast associating influencing factors associated with the subset of the data points and the directional signals with the new data point for predicting future asset returns of one or more assets associated with the new data point” is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human could generate a forecast based on the identified market regime associated with the new data point and the predicted direction of an asset price.
Step 2A Prong 2: A non-transitory computer readable medium including executable instructions, the instructions being executable by a processor to perform a method amounts to generic computer components for applying the abstract ideas on a generic computer under MPEP 2106.05(f).
Receiving a data set, the data set including financial market information and economic information as features of data points in the data set, the financial market information including asset returns, liquidity, and asset prices within some data points, the economic information including Gross Domestic Product (GDP) growth rates, interest rates, and inflation data within some data points amounts to mere data gathering, an insignificant extra-solution activity under MPEP 2106.05(g).
Receiving a new data point, the new data point being associated with a new date amounts to mere data gathering, an insignificant extra-solution activity under MPEP 2106.05(g).
The additional elements as disclosed above, alone or in combination, do not integrate the abstract ideas into a practical application as they are mere insignificant extra-solution activities as disclosed in combination with generic computer functions that are implemented to perform the abstract ideas disclosed above. The claim is directed to an abstract idea.
Step 2B: A non-transitory computer readable medium including executable instructions, the instructions being executable by a processor to perform a method amounts to generic computer components for applying the abstract ideas on a generic computer under MPEP 2106.05(f).
Receiving a data set, the data set including financial market information and economic information as features of data points in the data set, the financial market information including asset returns, liquidity, and asset prices within some data points, the economic information including Gross Domestic Product (GDP) growth rates, interest rates, and inflation data within some data points is analogous to receiving data over a network, which the courts have recognized as a well-understood, routine, conventional activity under MPEP 2106.05(d)(II).
Receiving a new data point, the new data point being associated with a new date is analogous to receiving data over a network, which the courts have recognized as a well-understood, routine, conventional activity under MPEP 2106.05(d)(II).
The additional elements as disclosed above, in combination with the abstract ideas, are not sufficient to amount to significantly more than the abstract ideas as they are well-understood, routine and conventional activities as disclosed in combination with generic computer functions that are implemented to perform the abstract ideas disclosed above. The claim is not patent eligible.
Claim 2 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. The topological representation being a visualization depicting the plurality of nodes and the edge is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. In the specification, paragraph [0142] discloses generating a topological representation, and a human could draw a graph of nodes and edges such as the one depicted in Fig. 9 on a piece of paper.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional elements which, alone or in combination, would integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 5 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. The forecast predicts an outcome associated with information regarding the new data point when the at least one similar condition of the plurality of conditions recurs is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional elements which, alone or in combination, would integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 6 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. The distances between the new data point and the at least some of the one or more data points from the data set is based on a metric from the at least one metric-lens combination is a mathematical calculation. Specification paragraph [0050] discloses calculating a distance using the n-dimensional Euclidean distance function.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional elements which, alone or in combination, would integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 7 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. The distances between the new data point and the at least some of the one or more data points from the data set is based on a graphical distance of the topological representation is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human could count a number of graph edges between the new data point and the original data points to determine a graphical distance.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional elements which, alone or in combination, would integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 8 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated.
Step 2A Prong 2 and Step 2B: A number of the subset of the data points closest to the new data point is based on a proximity value amounts to a field of use and technological environment under MPEP 2106.05(h). The claim is not patent eligible.
Claim 9 incorporates the rejection of claim 8.
Step 2A Prong 1: The abstract ideas of claim 8 are incorporated.
Step 2A Prong 2: The proximity value is received from a digital device amounts to mere data-gathering, an insignificant extra-solution activity under MPEP 2106.05(g).
Step 2B: The proximity value is received from a digital device is analogous to receiving data over a network, which the courts have recognized as a well-understood, routine, conventional activity under MPEP 2106.05(d)(II). The claim is not patent eligible.
Claim 10 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. The limitation “information associated with the new data point and the number of the subset of the data points closest to the new data point is based on a proximity value is analyzed using statistical measures to determine correlations” is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human could reasonably analyze information associated with the new data point and the subset of data points using statistical measures to determine correlations.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional elements which, alone or in combination, would integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 11
Step 2A Prong 1: The entire limitation “generating a topological representation using the features of the received data set and topological data analysis, the topological representation being generated using at least one metric-lens combination of a subset of metric-lens combinations, the topological representation including a plurality of nodes, each of the nodes having one or more data points from the data set as members, at least two nodes of the plurality of nodes being connected by an edge if the at least two nodes share at least one data point from the data set as members, each of the one or more data points from the data set being identified by a date, each of the one or more data points including the features indicating a plurality of conditions associated with that date” amounts to a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. In the specification, paragraph [0142] discloses generating a topological representation, and a human could draw a graph of nodes and edges such as the one depicted in Fig. 9 on a piece of paper. A human could perform topological data analysis based on data having features.
Determining distances between the new data point and at least some of the one or more data points from the data set based on features of the new data point and the features of the at least some of the one or more data points is a mathematical calculation. Specification paragraph [0050] discloses calculating a distance using the n-dimensional Euclidean distance function.
Locating the new data point in a location relative to one or more of the nodes in the topological representation using the distances between the new data point and the at least some of the one or more data points from the data set is a judgement mental process based on a mathematical calculation which can reasonably be performed in the human mind with the aid of pencil and paper. Specification paragraphs [0197], [0241] disclose placing a new data point on the graph by using a distance metric, which a human can perform.
Identifying a subset of the data points closest to the location of the new data point based on a proximity value, the proximity value being based the determined distances, a number of data points of the subset of the data points being limited based on the proximity value, the subset of the data points closest to the location of the new data point including at least one similar condition of the plurality of conditions is an observation and judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. Specification paragraphs [0198], [0241] disclose how a human could observe distances between original data points and the new data point, and group the new data point.
The limitation “comparing the features of the subset of the data points to at least some of the features of the new data point to identify a market regime associated with the new data point, the market regime including multiple conditions that match the new data point features, the conditions encapsulating financial market behavior, the market regime indicating a set of financial market and economic factors of at least most of the features of the subset of the data points as influencing factors of data point factors of the new data point, one or more asset prices of the data points being at least one of the influencing factors based on the market regime, one or more asset returns of the data points being at least another of the influencing factors based on the market regime, the market regime being one of a plurality of different market regimes that indicate different sets of financial market and economic factors, each market regime indicating different sets of financial market and economic factors from other market regimes of the plurality of market regimes” is an observation and judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human could compare features of the new data point to features of data points in the grouping, and identify a market regime associated with the new data point.
The limitation “determining directional signals of the influencing factors based on the market regime to determine a degree of impact on the data point factors of the new data point, the directional signals including at least one of an increase or decrease of the one or more asset prices and an increase or decrease of the one or more asset returns over one or more predetermined periods of time” is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. Specification paragraph [0267] discloses predicting directional signals of +1 (up) or -1 (down), and a human could predict whether an asset price will increase or decrease.
The limitation “generating a forecast for the new date associated with the new data point, the forecast associating influencing factors associated with the subset of the data points and the directional signals with the new data point for predicting future asset returns of one or more assets associated with the new data point” is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human could generate a forecast based on the identified market regime associated with the new data point and the predicted direction of an asset price.
Step 2A Prong 2: Receiving a data set, the data set including financial market information and economic information as features of data points in the data set, the financial market information including asset returns, liquidity, and asset prices within some data points, the economic information including Gross Domestic Product (GDP) growth rates, interest rates, and inflation data within some data points amounts to mere data gathering, an insignificant extra-solution activity under MPEP 2106.05(g).
Receiving a new data point, the new data point being associated with a new date amounts to mere data gathering, an insignificant extra-solution activity under MPEP 2106.05(g).
The additional elements as disclosed above, alone or in combination, do not integrate the abstract ideas into a practical application as they are mere insignificant extra-solution activities as disclosed that are implemented to perform the abstract ideas disclosed above. The claim is directed to an abstract idea.
Step 2B: Receiving a data set, the data set including financial market information and economic information as features of data points in the data set, the financial market information including asset returns, liquidity, and asset prices within some data points, the economic information including Gross Domestic Product (GDP) growth rates, interest rates, and inflation data within some data points is analogous to receiving data over a network, which the courts have recognized as a well-understood, routine, conventional activity under MPEP 2106.05(d)(II).
Receiving a new data point, the new data point being associated with a new date is analogous to receiving data over a network, which the courts have recognized as a well-understood, routine, conventional activity under MPEP 2106.05(d)(II).
The additional elements as disclosed above, in combination with the abstract ideas, are not sufficient to amount to significantly more than the abstract ideas as they are well-understood, routine and conventional activities as disclosed that are implemented to perform the abstract ideas disclosed above. The claim is not patent eligible.
Claims 12, 15-20 each recites a method which implements the same features as the product of claims 2, 5-10, respectively, and are therefore rejected for at least the same reasons.
Claim 21 recites a system which implements the same features as the method of claim 11 and is therefore rejected for at least the same reasons.
In Step 2A Prong 2 and Step 2B, a processor a memory including instructions to configure the processor amount to generic components for applying the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 22 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. Generating a liquidity forecasting model for the new date associated with the new data point based on the dates associated with each data point of the subset of the data points closest to the location of the new data point is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human could reasonably generate a liquidity forecasting model for the new date associated with the new data point.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional elements which, alone or in combination, would integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 23 incorporates the rejection of claim 22.
Step 2A Prong 1: The abstract ideas of claim 22 are incorporated. The liquidity forecasting model forecasts cost savings according to
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where X is a total order size, K ranges from 0 to N intraday periods, Vk is a volume percentage at a time interval, and Pk is a price at each time interval is a mathematical calculation.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional elements which, alone or in combination, would integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 24 incorporates the rejection of claim 11.
Step 2A Prong 1: The abstract ideas of claim 11 are incorporated. Generating a liquidity forecasting model for the new date associated with the new data point based on the one or more features associated with each data point of the subset of the data points closest to the location of the new data point is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human could reasonably generate a liquidity forecasting model for the new date associated with the new data point.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional elements which, alone or in combination, would integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 25 recites a method which implements the same features as the product of claim 23 and is therefore rejected for at least the same reasons.
Claim 26 recites a system which implements the same features as the method of claim 24 and is therefore rejected for at least the same reasons.
Claim 27 recites a system which implements the same features as the product of claim 23 and is therefore rejected for at least the same reasons.
Examiner’s Note
No prior art rejection was made for claims 1, 11, and 21. The features of a non-transitory computer readable medium including executable instructions, the instructions being executable by a processor to perform a method, the method comprising: receiving a data set, the data set including financial market information and economic information as features of data points in the data set, the financial market information including asset returns, liquidity, and asset prices within some data points, the economic information including Gross Domestic Product (GDP) growth rates, interest rates, and inflation data within some data points; generating a topological representation using the features of the received data set and topological data analysis, the topological representation being generated using at least one metric-lens combination of a subset of metric-lens combinations, the topological representation including a plurality of nodes, each of the nodes having one or more data points from the data set as members, at least two nodes of the plurality of nodes being connected by an edge if the at least two nodes share at least one data point from the data set as members, each of the one or more data points from the data set being identified by a date, each of the one or more data points including the features indicating a plurality of conditions associated with that date; receiving a new data point, the new data point being associated with a new date; determining distances between the new data point and at least some of the one or more data points from the data set based on features of the new data point and, the features of the at least some of the one or more data points, and the at least one metric-lens combination; locating the new data point in a location relative to one or more of the nodes in the topological representation using the distances between the new data point and the at least some of the one or more data points from the data set; identifying a subset of the data points closest to the location of the new data point based on a proximity value, the proximity value being based the determined distances, a number of data points of the subset of the data points being limited based on the proximity value, the subset of the data points closest to the location of the new data point including at least one similar condition of the plurality of conditions; comparing the features of the subset of the data points to at least some of the features of the new data point to identify a market regime associated with the new data point, the market regime including multiple conditions that match the new data point features, the conditions encapsulating financial market behavior, the market regime indicating a set of financial market and economic factors of at least most of the features of the subset of the data points as influencing factors of data point factors of the new data point, one or more asset prices of the data points being at least one of the influencing factors based on the market regime, one or more asset returns of the data points being at least another of the influencing factors based on the market regime, the market regime being one of a plurality of different market regimes that indicate different sets of financial market and economic factors, each market regime indicating different sets of financial market and economic factors from other market regimes of the plurality of market regimes; determining directional signals of the influencing factors based on the market regime to determine a degree of impact on the data point factors of the new data point, the directional signals including at least one of an increase or decrease of the one or more asset prices and an increase or decrease of the one or more asset returns over one or more predetermined periods of time; and generating a forecast for the new date associated with the new data point, the forecast associating influencing factors associated with the subset of the data points and the directional signals with the new data point for predicting future asset returns of one or more assets associated with the new data point, when taken in the context of the claim as a whole, were not uncovered in the prior art teachings.
Response to Arguments
Below is the Examiner’s response to the Applicant’s arguments filed 08/20/2026.
Applicant’s Arguments Under 35 U.S.C. 101 – Part A: On page 10 of the remarks, the Applicant argues that the mental-process exception applies only when a claim can practically be performed in the human mind under its broadest reasonable interpretation. The Applicant argues a claim requiring a processor to construct a multi-dimensional metric-lens-based node-graph, compute high-dimensional feature-space distances to locate a new data point within that graph, select a quantitatively proximity-bounded historical analog subset, identify a market regime, compute directional signals, and generate a topology-anchored forecast, all as an ordered, interdependent computational sequence, cannot practically be performed mentally. The Applicant argues the Examiner's contrary conclusion atomizes each step, addresses it in isolation, and does not engage with the claim as an ordered combination, and that approach is legally insufficient under Step 2A.
Examiner’s Response: Applicant's arguments have been fully considered but they are not persuasive. The Examiner respectfully disagrees with the Applicant’s argument that each step of claim 1 was improperly addressed in isolation rather than as an ordered combination. In the 101 analysis of claim 1, construct a multi-dimensional metric-lens-based node-graph (lines 9-16) is a judgement mental process. In the specification, paragraph [0142] discloses generating a topological representation, and a human could draw a graph of nodes and edges such as the one depicted in Fig. 9 or Fig. 17 on a piece of paper. A human could perform topological data analysis based on data having features.
Compute high-dimensional feature-space distances to locate a new data point within that graph (lines 18-20) is a mathematical calculation. Specification paragraph [0050] discloses calculating a distance using the n-dimensional Euclidean distance function.
Select a quantitatively proximity-bounded historical analog subset (lines 24-28) is an observation and judgement mental process. Specification paragraphs [0198], [0241] disclose how a human could observe distances between original data points and the new data point, and group the new data point.
Identify a market regime (page 3, lines 1-12) is an observation and judgement mental process. A human could compare features of the new data point to features of data points in the grouping, and identify a market regime associated with the new data point.
Compute directional signals (page 3, lines 13-17) is a judgement mental process. Specification paragraph [0267] discloses predicting directional signals of +1 (up) or -1 (down), and a human could predict whether an asset price will increase or decrease.
Generate a topology-anchored forecast (page 3, lines 18-21) is a judgement mental process. A human could generate a forecast based on the identified market regime associated with the new data point and the predicted direction of an asset price. The claim has been considered as an ordered combination.
It is noted that a processor is not a judicial exception.
Applicant’s Arguments Under 35 U.S.C. 101 – Parts B and C: On page 11 of the remarks, the Applicant argues that no human being could practically perform this ordered combination. The Applicant argues that the specific technical functionality of the claim requires a machine, not a human mind. On page 12, the Applicant argues the claims reflect an improvement in computer-implemented financial data analysis.
Examiner’s Response: Applicant's arguments have been fully considered but they are not persuasive. The Examiner respectfully disagrees with the Applicant’s argument that no human being could practically perform the ordered combination (excluding the receiving limitations). Specification paragraphs [0142], [0246] and Figures 9 and 19 disclose how a topological representation is generated as a graph of data values, which are arranged into nodes and connected by edges. The claims do not recite any feature which would make it unreasonable for a human to construct these topological representations by hand on a piece of paper based on features of data points in the data set. Nor do the claims recite any features which would make it unreasonable for a human to place the new data point into the topological representation, use its position to identify a market regime associated with the new data point, predict directional signals, and generate a forecast.
Examiner respectfully disagrees with the Applicant’s argument that the claims reflect an improvement in computer-implemented financial data analysis. Analyzing financial data is a judgement mental process which can reasonably be performed in the human mind. Any improvement recited by claim 1 is an improvement to the abstract ideas. It is noted that the judicial exception alone cannot provide the improvement, and that an improvement in the abstract idea itself is not an improvement in technology. See MPEP 2106.05(a) and (a)(II).
Applicant’s Arguments Under 35 U.S.C. 101 – Part D: On pages 12-14 of the remarks, the Applicant argues the following: Regarding claim 2, the visualization is clearly not a mental act, and claim 5 is not a mental act. Regarding claim 6, the metric in the claims is not generic, but derived from the metric-lens combination used to generate the topological representation. Regarding claim 7, no human could practically traverse and measure graphical distances within a computationally-generated topological graph of a large financial dataset. Regarding claim 8, the claims require the number of selected data points to be quantitatively limited based on a topology-derived proximity value, and this is not a qualitative mental clustering exercise.
Examiner’s Response: Applicant has relied on arguments that computing a topological structure and applying a topology-based workflow cannot be mental acts. Examiner respectfully disagrees. Topology is a field of mathematics which is performed by humans. As stated above, nothing in the claim would prevent a human from generating a topological representation of financial data comprising a number of features, and then analyzing the topological representation to generate predictions, according to the steps of claim 1, as explained in the rejection of claim 1 and in the Examiner’s responses above.
Claims 2 recites a mental process because a human could generate a topological representation on paper. Claim 5 recites a mental process because forecasting based on the recurrence determination is a mental process. Claim 6 recites a mathematical calculation. Specification paragraph [0050] discloses calculating a distance using the n-dimensional Euclidean distance function. Regarding claim 7, Examiner respectfully disagrees with the argument that no human could practically traverse and measure graphical distances. A graphical distance is simply a number of graph edges between two data points. A person could reasonably count the number of graph edges between two data points in the topological representation of Fig. 19.
The limitation of claim 8 recites a field of use and technological environment, rather than a judicial exception.
Regarding claim 9, Examiner respectfully disagrees with the argument that a proximity value is central to the claim. In claim 8, the limitation “a number… is based on a proximity value” is passively recited. Nothing in claims 1, 8, and 9 positively recites any details explaining how the proximity value would lead to generating the number.
Regarding claim 10, the language “information associated with the new data point and the number… is analyzed using statistical measures to determine correlations” is broad and passively recited. The claim does not positively recite any details explaining how the statistical measures are used to analyze the information, how the analysis leads to determining correlations, or which claim features are determined to be correlated.
Applicant’s Arguments Under 35 U.S.C. 101 – Part E: On page 14 of the remarks, the Applicant submits that the liquidity forecasting model of claim 22 is generated using inputs specifically constrained by the topological proximity-based selection of the independent claim, the dates of the historically analogous data points identified through the TDA workflow.
On page 15 of the remarks, the Applicant argues that regarding claim 23, the cost-savings formula is applied within the liquidity model, and argues the formula is not applied in the abstract; it is integrated in the TDA-grounded liquidity forecasting workflow.
Examiner’s response: The entire limitation of claim 22 is a judgement mental process of generating a liquidity forecasting model. The entire TDA workflow as recited (excluding receiving data) are abstract ideas. Integrating either the mental process of claim 22 or the mathematical formula of claim 23 into an abstract idea is still an abstract idea.
Conclusion
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/A.H.J./Examiner, Art Unit 2127
/ABDULLAH AL KAWSAR/Supervisory Patent Examiner, Art Unit 2127
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