DETAILED ACTION
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 .
Claims 1-20 are presented for examination.
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 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claims 1 and 11:
Applying the Alice/Mayo Framework:
Step 1
Claim 1 is directed to a “computer-implemented method” comprising steps performed by “one or more processors,” which falls within the statutory category of a process under 35 U.S.C. 101. Claim 11 is directed to a “non-transitory, computer-readable medium containing instructions for causing one or more processors to perform a method,” which falls within the statutory category of an article of manufacture (manufacture) under 35 U.S.C. 101.
Step 2A, Prong I – whether the claim recites a judicial exception
Under its broadest reasonable interpretation, independent claims 1 and 11 recite operations that can be characterized as financial data analysis and portfolio/product selection, namely:
Receiving, by one or more processors, a product dataset associated with a product comprising one or more subproducts, a first corresponding product dataset associated with a first corresponding product, and a second corresponding product dataset associated with a second corresponding product.
Determining, by the one or more processors, a product model output corresponding to the product, wherein the product model output is a single, value-weighted indicator of the product.
Determining, by the one or more processors, a first variability index corresponding to the first corresponding product based at least on the product model output and the first corresponding product dataset, and a second variability index corresponding to the second corresponding product based at least on the product model output and the second corresponding product dataset.
Displaying, by the one or more processors, a visual indicator on a graphical user interface of the first variability index and the second variability index, and, in certain dependent claims, using a variability threshold applied to the indices to trigger trading or exchange instructions via an exchange system.
These limitations collectively recite:
Mathematical concepts (e.g., determining a single, value-weighted indicator of a product and determining variability indices based on datasets and the product model output).
Certain methods of organizing human activity in the field of financial product and portfolio management (e.g., analyzing relationships between a managed product and corresponding products and making trading/exchange decisions based on that analysis).
As such, claims 1 and 11 recite at least the abstract idea of mathematical calculations and financial product selection/trading, which falls within the judicial exceptions of mathematical concepts and certain methods of organizing human activity (e.g., managing commercial or financial interactions) identified in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Step 2A, Prong II – whether the claim integrates the judicial exception into a practical application
The additional elements beyond the abstract idea in claims 1 and 11 include, at a high level:
“One or more processors.”
A “graphical user interface” and “visual indicator” displayed thereon.
An “exchange system” that receives trade or exchange instructions responsive to variability indices satisfying a threshold (as further specified in dependent claims).
These additional elements amount to using generic computer components (processors, memory, GUI, exchange system) as tools to implement the abstract financial and mathematical processing and to present the results. The claims do not recite any improvement in the functioning of a computer, any new type of data structure or memory architecture, any specific GUI control or display technique that improves computer interaction, or any other meaningful limitation that applies the abstract idea with a particular machine in a non-generic manner.
Although the specification describes potential benefits such as improved efficiency in identifying corresponding financial products and reduced complexity for portfolio managers, these improvements arise from the content of the financial calculations and decision rules themselves, rather than from any improvement in computer technology or other technical field. The claims as drafted merely require a generic computer to receive data, perform mathematical calculations to generate indicators and variability indices, compare those results to thresholds, display results, and generate trading instructions, all of which are conventional data-processing and presentation functions.
Accordingly, the claims do not integrate the judicial exception into a practical application under Step 2A, Prong II.
Step 2B – whether the claim recites significantly more than the judicial exception
Under Step 2B, the claim elements, individually and in ordered combination, are evaluated to determine whether they amount to “significantly more” than the abstract idea itself.
As noted above, the additional elements consist of:
Generic “one or more processors” executing software instructions stored in memory or on a non-transitory computer-readable medium.
Generic user interface components for displaying information, such as a graphical user interface presenting visual indicators of computed indices.
Generic communication with an “exchange system” or “clearing agency” to send trade or exchange instructions.
The specification describes implementation using conventional client devices, servers, databases, and networks, and treats the processors and memories as standard computing hardware. The steps of receiving datasets, computing a single, value-weighted indicator, determining variability indices, comparing them to thresholds, and sending trading instructions represent mathematical and financial logic carried out on generic computers, which is the type of activity that has been held not to provide an inventive concept in numerous cases.
There is no indication in the claims of:
Any unconventional computer hardware.
Any non-routine or unconventional use of generic computer components.
Any additional element that adds a meaningful limitation beyond generally linking the use of the judicial exception to the technological environment of generic computers and networks.
When the abstract idea is set aside, the remaining elements in the claims are well-understood, routine, and conventional activities previously known in the art, such as using processors to receive and process data, using GUIs to display results, and using networked systems to send trading instructions. Thus, the claims, considered as a whole, do not amount to significantly more than the judicial exception itself.
For these reasons, claims 1–20 are directed to an abstract idea (mathematical concepts and financial product management) and do not recite additional elements that amount to significantly more than the abstract idea. Therefore, claims 1–20 are rejected under 35 U.S.C. 101.
Regarding claim 2, claim 2 adds the abstract idea of further specifying that the first corresponding product comprises a plurality of first corresponding subproducts and the second corresponding product comprises a plurality of second corresponding subproducts. This is merely an additional description of the financial products being analyzed and modeled as groups of subproducts, which is another aspect of financial data organization and analysis and therefore an abstract idea. This additional abstract idea does not add any meaningful limitation to the underlying abstract concept of receiving financial product datasets, computing a product model output and variability indices, and using those indices to inform product selection, and thus does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 3, claim 3 adds the abstract idea of receiving a variability threshold and, responsive to the first variability index satisfying the variability threshold and indicating less variability than the second variability index, transmitting an instruction to trade the first corresponding product to an exchange system. This limitation merely recites an additional mental/financial decision rule—using a threshold on a computed score to decide whether to trade—implemented on a generic computer and exchange system, which remains within the realm of abstract methods of organizing financial activity. This additional abstract idea does not meaningfully limit the claimed abstract concept and therefore does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 4, claim 4 adds the abstract idea of, when the first variability index does not satisfy the variability threshold, generating an adjusted first corresponding product by adjusting one or more corresponding subproducts of a currently owned corresponding product, determining a corresponding product model output, determining an adjusted first variability index, and, if the adjusted first variability index satisfies the variability threshold, transmitting an instruction to exchange the first corresponding product with the adjusted first corresponding product. These steps are additional financial decision and portfolio-rebalancing rules—how to adjust and exchange products based on updated variability measures—which are methods of organizing financial activity and remain abstract ideas. The added abstract idea does not add any technical improvement to computer functioning or other technology, and therefore does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 5, claim 5 adds the abstract idea of specifying that the instruction to exchange includes exchanging one or more individual first corresponding subproducts of the first corresponding product with one or more individual subproducts of the product. This further refines the financial transaction and portfolio rebalancing logic at the level of individual subproducts, which is still an abstract method of managing financial instruments. This additional abstract idea does not provide a meaningful limitation beyond the recited abstract financial calculations and trading decisions and therefore does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 6, claim 6 adds the abstract idea of specifying that the product model output is the single, value-weighted indicator of the one or more subproducts of the product. This is an additional mathematical characterization of the model output as a particular kind of aggregated financial metric, which falls squarely within the “mathematical concepts” category of abstract ideas. This added abstract mathematical specification does not add significantly more than the underlying abstract idea of financial data analysis and thus does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 7, claim 7 adds the abstract idea of specifying that the product model output is a historical trend of single, value-weighted indicators of the one or more subproducts of the product over a statistically significant period of time. This recites generating a time series of mathematical indicators and analyzing their historical trend, which is a further mathematical refinement of the financial analysis and thus an abstract idea. This additional abstract idea does not improve the functioning of a computer or any other technology and therefore does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 8, claim 8 adds the abstract idea of specifying that the exchange system is a clearing agency. This merely labels the type of financial intermediary that receives the trading instruction and remains within the abstract field of financial trading and settlement, i.e., methods of organizing human financial activity. This additional abstract idea does not meaningfully limit the abstract financial and mathematical processing recited in the independent claim and therefore does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 9, claim 9 adds the abstract idea of defining the first variability index as a measure of variability between the product and the first corresponding product and the second variability index as a measure of variability between the product and the second corresponding product. This is a further mathematical description of the computed indices as particular measures of variability between financial products and therefore a mathematical concept and abstract idea. This refinement does not add any non-abstract technical feature or inventive concept and thus does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 10, claim 10 adds the abstract idea of specifying that the first variability index and the second variability index are determined at regular time intervals. Determining financial or mathematical indices on a periodic basis is itself an abstract data-analysis scheduling concept and a method of organizing financial analysis activity. This additional abstract idea does not provide significantly more than the underlying abstract financial calculations and thus does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 12, claim 12 adds the abstract idea of further specifying that the first corresponding product comprises a plurality of first corresponding subproducts and the second corresponding product comprises a plurality of second corresponding subproducts, in the context of instructions stored on a non-transitory computer-readable medium. As in claim 2, this is merely additional financial data modeling and organization and therefore an abstract idea. This additional abstract idea does not add a meaningful limitation to the underlying abstract concept and thus does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 13, claim 13 adds the abstract idea of instructions to receive a variability threshold and, responsive to the first variability index satisfying the variability threshold and indicating less variability than the second variability index, to transmit an instruction to trade the first corresponding product to an exchange system. This is the same abstract financial decision rule as in claim 3, implemented as software instructions on a non-transitory medium, and remains an abstract method of organizing financial trading activity. This additional abstract idea does not provide significantly more than the abstract financial and mathematical concepts and therefore does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 14, claim 14 adds the abstract idea of instructions that, when the first variability index does not satisfy the variability threshold, cause a processor to generate an adjusted first corresponding product by adjusting one or more corresponding subproducts of a currently owned corresponding product, determine a corresponding product model output and adjusted first variability index, and, if the adjusted first variability index satisfies the variability threshold, transmit an instruction to exchange the first corresponding product with the adjusted first corresponding product. These steps mirror the abstract portfolio-rebalancing and exchange decision rules of claim 4 and remain methods of organizing financial activity. This additional abstract idea does not introduce any technical improvement to computer technology and therefore does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 15, claim 15 adds the abstract idea of instructions specifying that the exchange instruction includes exchanging individual first corresponding subproducts of the first corresponding product with individual subproducts of the adjusted first corresponding product. This is a further refinement of the abstract financial transaction and rebalancing logic and thus still constitutes an abstract method of managing financial instruments. This additional abstract idea does not meaningfully limit the underlying abstract concept and does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 16, claim 16 adds the abstract idea of specifying, in the stored instructions, that the product model output is a single, value-weighted indicator of the one or more subproducts of the product. As with claim 6, this is a mathematical characterization of the model output and falls within the category of mathematical concepts, which are abstract ideas. This additional abstract idea does not add significantly more than the abstract financial calculations already recited and thus does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 17, claim 17 adds the abstract idea of specifying that the product model output is a historical trend of single, value-weighted indicators over a statistically significant period of time. This is a further mathematical data-analysis refinement, similar to claim 7, involving computation of historical trends over time, which is an abstract mathematical concept. This additional abstract idea does not improve any computer technology and therefore does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 18, claim 18 adds the abstract idea of specifying, in the stored instructions, that the exchange system is a clearing agency. This merely identifies the type of financial intermediary and thus recites an additional abstract financial trading concept. This added abstract idea does not meaningfully limit the underlying abstract financial and mathematical operations and therefore does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 19, claim 19 adds the abstract idea of defining the first and second variability indices as measures of variability between the product and each corresponding product. As with claim 9, this is a mathematical definition of the computed indices and therefore an abstract mathematical concept. This additional abstract idea does not provide significantly more than the abstract idea itself and thus does not overcome the prior rejection under 35 U.S.C. 101.
Regarding claim 20, claim 20 adds the abstract idea of specifying that the first variability index and the second variability index are determined at regular time intervals. This is a scheduling refinement of the abstract data analysis and financial decision process, and therefore remains a method of organizing financial activity and a mathematical/organizational concept. This additional abstract idea does not add any inventive concept or technical improvement and does not overcome the prior rejection under 35 U.S.C. 101.
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Ma et al, US 2023/0169565 and further in view of Stenneth et al, US 2022/0063673.
Regarding claim 1, Ma discloses a computer-implemented method comprising:
receiving, by one or more processors, a product dataset associated with a product (Paragraph 0013: obtaining historical data over a threshold period for a set of product types) comprising one or more subproducts, a first corresponding product dataset associated with a first corresponding product (0013: product type of the set of product types), and a second corresponding product dataset associated with a second corresponding product (0013: selecting a subset of product types);
determining, by the one or more processors, a product model output corresponding to the product (0013: applying a theme-aware model to the product types), wherein the product model output is a single, value-weighted indicator of the product (0013, based on the seasonality index score);
determining, by the one or more processors, a first variability index corresponding to the first corresponding product based at least on the product model output and the first corresponding product dataset, and a second variability index corresponding to the second corresponding product based at least on the product model output and the second corresponding product dataset (0058: The seasonality index determination module 428 identifies the top (for example, five) items or rather those items with the highest seasonality index scores. Those top items are then stored in the season database 128 corresponding to the season indicated in the set generation request.).
Ma lacks or does not expressly disclose a visual indicator on a graphical user interface the first variability index and the second variability index .
However, Stenneth discloses displaying, by the one or more processors, a visual indicator on a graphical user interface the first variability index and the second variability index (0020: via a map display of the vehicle based on the comparison between the first transition variability index for the first spatial reference point and the second transition variability index for the second spatial reference point).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Ma with Stenneth to include a display of the two variability indexes in order to view a comparison between the two reference points, as taught by Stenneth, paragraph 0020.
Regarding claim 2, Ma, as modified above, further discloses the computer-implemented method of claim 1, wherein the first corresponding product comprises a plurality of first corresponding subproducts, and the second corresponding product comprises a plurality of second corresponding subproducts (0005: first threshold number of product types to select the subset of product types; and identify the set of items as a second threshold number of items).
Regarding claim 3, Ma, as modified above, further discloses the computer-implemented method of claim 1, further comprising: receiving, by the one or more processors, a variability threshold; and responsive to the first variability index satisfying the variability threshold and indicating less variability than the second variability index, transmitting, by the one or more processors to an exchange system, an instruction to trade the first corresponding product (0004: obtain historical data over a threshold period for a set of product types. The computing device is further configured to, for each product type of the set of product types, compute a seasonality index score based on the historical data over a target period and the threshold period, the target period being a portion of the threshold period.).
Regarding claim 4, Ma, as modified above, further discloses the computer-implemented method of claim 2, further comprising: receiving, by the one or more processors, a variability threshold; responsive to the first variability index not satisfying the variability threshold, generating, by the one or more processors, an adjusted first corresponding product by adjusting one or more of the plurality of first corresponding subproducts, wherein the first corresponding product is a currently owned corresponding product; determining, by the one or more processors, a first corresponding product model output corresponding to the adjusted first corresponding product; determining, by the one or more processors, an adjusted first variability index corresponding to the adjusted first corresponding product based at least on the product model output and the first corresponding product model output; and responsive to the adjusted first variability index satisfying the variability threshold, transmitting, by the one or more processors to an exchange system, an instruction to exchange the first corresponding product with the adjusted first corresponding product (0005: the computing device is configured to select a first threshold number of product types based on the seasonality index score and apply the theme-aware model to the selected first threshold number of product types to select the subset of product types. In another aspect, the computing device is configured to compute an item seasonality index score for each item of the subset of product types and identify the set of items as a second threshold number of items corresponding to a highest item seasonality index score. 0013: for each product type of the set of product types, computing a seasonality index score based on the historical data over a target period and the threshold period, the target period being a portion of the threshold period. The method also includes selecting a subset of product types based on the seasonality index score and by applying a theme-aware model to the product types and identifying and storing a set of items corresponding to at least one product type of the subset of product types. The method includes, in response to a user navigating to a webpage using a user device, selecting and displaying at least one item of the set of items on a user interface of the user device.).
Regarding claim 5, Ma, as modified above, further discloses the computer-implemented method of claim 4, wherein the instruction to exchange of the currently owned corresponding product with the adjusted first corresponding product includes instructions to exchange one or more individual first corresponding subproducts of the first corresponding product with one or more individual subproducts of the product (0033: system 100 also includes a query-click database 124, a season database 128, a historical database 132, and a model database 136. The item database 112 stores items for sale on the ecommerce marketplace, and the items are categorized by product type. That is, each item may have a corresponding product type to which the item belongs).
Regarding claim 6, Ma, as modified above, further discloses the computer-implemented method of claim 1, wherein the product model output is the single, value-weighted indicator of the one or more subproducts of the product (0059: FIG. 5, a block diagram illustrating an example theme model generation module of the seasonal recommendation system is shown. The theme model generation module 120 includes a query and product type selection module 504 that receives a model generation request. In various implementations, the model generation request occurs at threshold intervals, for example, in anticipation of a particular season occurring.).
Regarding claim 7, Ma, as modified above, further discloses the computer-implemented method of claim 1, wherein the product model output is a historical trend of single, value-weighted indicators of the one or more subproducts of the product over a statistically significant period of time (0034: The historical database 132 may store historical transactions over a plurality of past years for each of the items in the item database 112. For example, for the last three years, the historical database 132 includes a number of purchases for each item on each day of the previous number of years. In this way, the seasonal recommendation module 116 may access the historical transaction data stored in the historical database 132 to identify, for a particular season).
Regarding claim 8, Ma, as modified above, further discloses the computer-implemented method of claim 3, wherein the exchange system is a clearing agency (0032: The seasonal recommendation system 100 may include a seasonal recommendation device 102 and user devices 104-1 and 104-2, collectively user device 104, such as a phone, tablet, laptop, mobile computing device, desktop, etc., capable of communicating with a plurality of databases and modules via a distributed communications system 108. The user device 104 may display an ecommerce marketplace via a web browser or an application for customers to view items for sale by the ecommerce marketplace that are stored in an item database 112.).
Regarding claim 9, Ma, as modified above, further discloses the computer-implemented method of claim 1, wherein the first variability index is a measure of variability between the product and the first corresponding product, and the second variability index is a measure of variability between the product and the second corresponding product (0058: the identified items are forwarded to a seasonality index determination module 428 (by item) determines the seasonality index scores for each item of the filtered product types. The seasonality index determination module 428 identifies the top (for example, five) items or rather those items with the highest seasonality index scores. Those top items are then stored in the season database 128 corresponding to the season indicated in the set generation request).
Regarding claim 10, Ma, as modified above, further discloses the computer-implemented method of claim 1, wherein the first variability index and the second variability index are determined at regular time intervals (FIGS. 6A and 6B, flowcharts of example methods of generation of seasonal item recommendations are shown. Control begins in response to receiving a request for seasonal recommendations. For example, at predetermined intervals, the seasonal recommendation system may automatically prompt the system to generate seasonal recommendations to be stored in a database for the system to access and display to customers. The predetermined intervals).
As per claims 11-20, this is a computer readable medium version of the claimed method discussed above in claims 1-10 wherein all claimed limitations have also been addressed and/or cited as set forth above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AUBREY H WYSZYNSKI whose telephone number is (571)272-8155. The examiner can normally be reached M-F 9-5.
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/AUBREY H WYSZYNSKI/Primary Examiner, Art Unit 2434