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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/13/2024 is in compliance with the provisions of 37 CFR 1.97 and have been entered into the record. Accordingly, the information disclosure statements are being considered by the examiner.
Allowable Subject Matter
Claims 6-7 and 16-17 are allowable over the prior art, however these claims remain rejected under 35 USC 101. Furthermore, if these claims overcome the 101 rejection, they would be allowable only if rewritten in independent form to include all the limitations of the base claim and any intervening claims.
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 non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below.
Claims 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. These claims are directed towards a system but they do not recite structural features but rather recite features such as “detecrtinc module…processing module” the system/component fail to satisfy Step 1 of the eligibility inquiry because there are no physical/hardware elements in the claims to render the systems as a machine or manufacture, but instead these modules may be reasonably interpreted as being directed to software per se, which is not eligible subject matter.
A module is interpreted as software according to the plain/ordinary meaning in the art. In addition, there is no special definition provided in the Spec for re-defining this term. While the Spec discusses exemplary embodiments of memory modules and processing modules, the description is open-ended and does not preclude a software per se embodiment. Applicant specification states ““Although not required, the embodiments described with reference to the Figures can be implemented as an application programming interface (API) or as a series of libraries for use by a developer or can be included within another software application, such as a terminal or personal computer operating system or a portable computing device operating system. Generally, as program modules include routines, programs, objects, components and data files assisting in the performance of particular functions, the skilled person will understand that the functionality of the software application may be distributed across a number of routines, objects or components to achieve the same functionality desired herein.”
Products that do not have a physical or tangible form, such as information (often referred to as "data per se") or a computer program per se (often referred to as "software per se") when claimed as a product without any structural recitations;, see MPEP 2106.03 I. Therefore, since the Spec is open-ended, and since one skilled in the art could reasonably interpret a virtual machine or other software-only embodiment as performing the function of the memory modules and processing modules, the system does not necessarily constitute a machine; and thus the claims appear to be directed towards software per se and software is not a statutory category of patentable subject matter. Appropriate correction and/or clarification is required. The Office recommends amending the claims so that more structural features are recited in the bodies of these claims.
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is first noted that the method (claims 11-20) are directed to potentially eligible categories of subject matter (i.e., process, machine, and article of manufacture respectively). Thus, Step 1 is satisfied. However, system claims (claims 1-10) is not eligible and Step 1 is not satisfied.
With respect to Step 2, and in particular Step 2A Prong One, it is next noted that the claims recite an abstract idea by reciting concepts performed in the human mind (including an observation, evaluation, judgment, opinion), which falls into the “Mental Process” group; and by reciting mathematical relationships, mathematical formulas or equations, mathematical calculations which falls into the “Mathematical concepts” group within the enumerated groupings of abstract ideas. The mere nominal recitation of a generic computer does not take the claim limitation out of mathematical concepts or the mental processes grouping. Thus, the claim recites a mental process for performing mathematics.
The limitations reciting the abstract idea(s) (Mental process and mathematical concepts), as set forth in exemplary claim 1, are: detecting an event associated with generation and/or transaction of an exchangeable asset; and processing the detected event to obtain an evaluation score of the market indicating a likelihood of a change of market value of the exchangeable assets; wherein the evaluation score is obtained with reference to a database of a plurality of history events categorized by a plurality of predefined categories and a plurality of seasoned factors according to a plurality of signal classification rules, and wherein the plurality of history events are assigned with the evaluation score. Independent claim 1 recites the system for performing the method of independent claim 11 without adding significantly more. Thus, the same rationale/analysis is applied.
With respect to Step 2A Prong Two, the judicial exception is not integrated into a practical application. The claims do not recite additional elements, and thus fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Even if the acquiring steps are considered as additional elements, these steps at most amount to insignificant extra-solution activity accomplished via receiving/transmitting data, which is not enough to amount to a practical application. See MPEP 2106.05(g).
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Any additional elements merely serve to tie the invention to a particular operating environment (i.e., computer-based implementation), though at a very high level of generality and without imposing meaningful limitation on the scope of the claim.
In addition, Applicant’s Specification describes generic off-the-shelf computer-based elements for implementing the claimed invention, and which does not amount to significantly more than the abstract idea, which is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo. See, e.g., Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide conventional computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself. Further, the courts have found the presentation of data to be a well-understood, routine, conventional activity, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93 (see MPEP 2106.05(d)).
The dependent claims (2-10 and 12-20) are directed to the same abstract idea as recited in the independent claims, and merely incorporate additional details that narrow the abstract idea via additional details of the abstract idea. For example claims 12-20“wherein the step of processing the detected event includes processing the detected event using an AI-based processing engine, and wherein the database is a database of a training dataset comprising the plurality of history events; wherein the evaluation score is arranged to represent a bullish or a bearish signal of the market of exchangeable assets; wherein the exchangeable asset includes crypto assets; wherein the plurality of predefined categories includes a miner selling event associated with an outflow of crypto assets generated by miners; wherein the plurality of predefined categories includes a whale accumulation/dumping event associated with an accumulation/dumping of crypto assets by institutional investors; wherein the whale accumulation event is represented a detection of huge over-the-counter deal of the crypto assets on the crypto assets network; wherein the plurality of predefined categories includes a determination of indicators associated with transaction histories of crypto assets in a predetermined period of time, wherein the indicators represent one or more of buying pressure, selling pressure, market trend related to a supply of crypto assets on exchanges and market sentiment; using Bollinger Band to detect an outlier; - using a tsmoothie function to detect the outlier; or - using predefined logics associated with the plurality of seasoned factors each associated with generation and/or transaction of the exchangeable asset; wherein the outlier represents a signal trigger; further comprising the step of providing a summary of analysis including the evaluation score of the market, a score calculated for each of the plurality of predefined categories, a score calculated for each of the plurality of seasoned factors, a score indicating past accuracy, a score indicating confidence level and/or a change of real value of each seasoned factor”, without additional elements that integrate the abstract idea into a practical application and without additional elements that amount to significantly more to the claims. The remaining dependent claims (2-10) recite the CRM and system for performing the method of claims 12-20. Thus, the same rationale/analysis is applied. Thus, all dependent claims have been fully considered, however, these claims are similarly directed to the abstract idea itself, without integrating it into a practical application and with, at most, a general-purpose computer that serves to tie the idea to a particular technological environment, which does not add significantly more to the claims.
The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to significantly more than the abstract idea itself.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2, 4, 8, 11-12, 14, and 18 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent 10706472 (hereinafter “Myers”) et al.
As per claim 1, Myers teaches a system for analyzing a market of exchangeable assets, comprising:
a detecting module arranged to detect an event associated with generation and/or transaction of an exchangeable asset; and a processing module arranged to process the detected event to obtain an evaluation score of the market indicating a likelihood of a change of market value of the exchangeable assets;
Myers 013-014: “a computer-implemented method for determining the fundamental health of a crypto-asset comprises receiving, from one or more interfaces associated with one or more development servers associated with a crypto-asset, developer activity data associated with the crypto-asset; calculating a developer activity factor based on the developer activity data; establishing a connection to a blockchain server that maintains a blockchain that tracks transactions associated with the crypto-asset; receiving, from the blockchain server, transaction data for a plurality of the transactions; calculating a project utility factor based on a plurality of behavioral use cases derived from the transaction data, wherein the behavioral use cases are respectively associated with different uses of the crypto-asset; and determining a fundamental health score for the crypto-asset based on the developer activity factor and the project utility factor. Other aspects of the foregoing include corresponding systems and computer-executable instructions stored on non-transitory storage media… Calculating the project utility factor can comprise differentiating among behaviors exhibited in the transaction data using probabilistic modeling, heuristics, and/or manual inspection. Calculating the project utility factor can comprise: forming clusters of similar transaction participants based on the transaction data; classifying the clusters into the behavioral use cases; and calculating a time-series of proportions of the behavioral use cases. Determining the fundamental health score can comprise calculating a covariance-weighted average using the developer activity factor and the project utility factor. A market maturity factor can be calculated for the crypto-asset based on trading volume, current price, total project value, and/or volatility, and wherein the fundamental health score is further based on the market maturity factor…023-036: to build archetypes for exchange heuristics, coins and tokens can be purchased from certain exchanges and products/services, and the flow of the coins/tokens can be tracked to isolate and define the unique behaviors of the addresses associated with the coins/tokens transactions. Probabilistic modeling: Machine learning models, e.g., Random Forest, are used to identify groups of addresses and transactions that fall into particular categories to identify different types of address and transaction types…This Market Maturity score provides a single aggregate indicator of the likelihood that the market for a particular coin will change dramatically or drop to zero in the medium-term (many days, weeks, or months, rather than hours or seconds). Projects with higher Market Maturity scores tend to be more mature, and are less likely to see dramatic volatility, loss of liquidity, or significant price declines than projects with lower scores”
wherein the evaluation score is obtained with reference to a database of a plurality of history events categorized by a plurality of predefined categories and a plurality of seasoned factors according to a plurality of signal classification rules, and wherein the plurality of history events are assigned with the evaluation score;Myers 015-021: “As a result, the current and historical price of a given crypto-asset is a major factor in any valuation metric, even though different exchanges offer different prices at different times for different crypto-assets. The current approach therefore aggregates data across all of the various exchanges and projects that influence crypto-asset prices. More specifically, a volume-weighted aggregation of all available exchange data is used to provide consistent real-time and historical price data for crypto-assets. FIG. 2 illustrates the many-to-many mapping of exchanges to crypto-assets… One factor used to determine an asset value (e.g., FCAS) is “Developer Activity,” which can be based on information relating to developer and community contributions and codebases. Such information used in determining Developer Activity may be collected from public code repositories, such as GitHub and BitBucket, or private or proprietary repositories and source control systems. The information can be automatically collected through various interfaces, such as application programming interfaces (APIs) or web scraping browser-based interfaces. The repositories and source control systems provide access to a historical record of all contributions made… Another factor used to determine an asset value (e.g., FCAS) is “Project Utility.” For the various crypto-assets, a blockchain maintains a record of all transactions that have ever occurred for a given token or coin, and each blockchain can be accessed by establishing a server that communicates with the blockchain. Once this connection has been established, a copy of every transaction for every crypto-asset can be downloaded and stored in a local database. Generally, each crypto-asset transaction comprises distinct types of users: active traders, passive traders/holders/speculators, and actual users—those who actually use a coin or token to engage with a project's intended purpose (e.g., providing storage, computing resources, access to intellectual property, etc.).”
As per claim 2, Myers teaches all the limitations of claim 1.
In addition, Myers teaches:
wherein the evaluation score is arranged to represent a bullish or a bearish signal of the market of exchangeable assets; Myers 023: “Several mechanisms can be used to differentiate among the types of behaviors (e.g., investing, holding, selling, ordinary use, etc.) associated with crypto-assets, as follows: Manual inspection: Block explorers are used to study transaction and account behaviors, transactions are followed through the ecosystem to flag particular addresses and transaction types known to belong to a particular category with high or absolute (100%) certainty. Heuristics: Heuristics are used to understand the life-cycle of suspicious or irrelevant addresses and flag them as such. Heuristics can also be developed from the above manual activities. For example, to build archetypes for exchange heuristics, coins and tokens can be purchased from certain exchanges and products/services, and the flow of the coins/tokens can be tracked to isolate and define the unique behaviors of the addresses associated with the coins/tokens transactions. Probabilistic modeling: Machine learning models, e.g., Random Forest, are used to identify groups of addresses and transactions that fall into particular categories to identify different types of address and transaction types.”
As per claim 4, Myers teaches all the limitations of claim 1.
In addition, Myers teaches:
wherein the exchangeable asset includes crypto assets; Myers 013: “a computer-implemented method for determining the fundamental health of a crypto-asset comprises receiving, from one or more interfaces associated with one or more development servers associated with a crypto-asset, developer activity data associated with the crypto-asset; calculating a developer activity factor based on the developer activity data; establishing a connection to a blockchain server that maintains a blockchain that tracks transactions associated with the crypto-asset; receiving, from the blockchain server, transaction data for a plurality of the transactions; calculating a project utility factor based on a plurality of behavioral use cases derived from the transaction data, wherein the behavioral use cases are respectively associated with different uses of the crypto-asset; and determining a fundamental health score for the crypto-asset based on the developer activity factor and the project utility factor. Other aspects of the foregoing include corresponding systems and computer-executable instructions stored on non-transitory storage media.”
As per claim 8, Myers teaches all the limitations of claim 4.
In addition, Myers teaches:
wherein the plurality of predefined categories includes a determination of indicators associated with transaction histories of crypto assets in a predetermined period of time, wherein the indicators represent one or more of buying pressure, selling pressure, market trend related to a supply of crypto assets on exchanges and market sentiment; Myers 013: “The inclusion of other factors, which may include traditional measures used to value assets, is also contemplated. In one implementation, the fundamental health of a crypto-asset is represented by a high-level metric, also referred to herein as a Fundamental Crypto Asset Score (“FCAS”), that takes into account three primary factors: Developer Activity, Project Utility, and Market Maturity, each of which is further described below. FCAS is a weighted combination of these factors, two of which are calculated irrespective of market-based metrics and focus instead on the blockchain and development ecosystem to derive value… Certain conventional measures such as overall trading volume, current price (or prices), total project value (e.g., “market capitalization”), volatility measures, and others may also be included in the valuation calculations…035: calculation of the Market Maturity factor takes into consideration “conventional” metrics, such as overall trading volume, current price (or prices), total project value (e.g., “market capitalization”), volatility measures, and others, but also includes an algorithmic approach to gauge the predictability of price, volatility, and trading volume of the crypto-assets that are evaluated. The system performs traditional modeling of capital asset pricing model (CAPM) characteristics (Beta, Alpha), Markov Chain projections of potential price movements (expected performance, upside, downside potential), and calculations of volatility, skewness, and kurtosis, to combine into factors that together concisely describe the risk of investing in a particular crypto-asset and/or portfolio of crypto-assets. This Market Maturity score provides a single aggregate indicator of the likelihood that the market for a particular coin will change dramatically or drop to zero in the medium-term (many days, weeks, or months, rather than hours or seconds). Projects with higher Market Maturity scores tend to be more mature, and are less likely to see dramatic volatility, loss of liquidity, or significant price declines than projects with lower scores.”
Claims 11-12, 14, and 18 are directed to the method for performing the system of claims 1-2, 4, and 8 above. Since Myers teaches the method, the same art and rationale apply.
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 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 3, 5, 13 , and 15 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent 10706472 (hereinafter “Myers”) et al., in view of U.S. PGPub 20160328797 to (hereinafter “Figy”) et al.,
As per claim 3, Myers teaches all the limitations of claim 1.
Myers may not explicitly teach the following. However, Figy teaches:
wherein the evaluation score is arranged to represent a bullish or a bearish signal of the market of exchangeable assets; Figy 0015: “Traders or other users of trading devices utilize candlestick charts to visualize the status and/or past status of a market. A candlestick chart includes a vertical line (also called a “wick”) with a rectangle (also called a “real body”) superimposed over the vertical line. A top and bottom of the wick represents a highest traded price and a lowest traded price for a tradeable object in a time interval, respectively. The top and bottom of the real body represent an opening and closing price of the tradeable object. The real body is generally colored according to the traversal of the opening and closing price. That is, first color of the real body will represent if the price closed higher than it opened (e.g., a bullish market) and a second color of the real body will represent if the price closed lower than it opened (e.g., a bearish market).”
Myers and Figy are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Myers with the aforementioned teachings from Fugy with a reasonable expectation of success, by adding steps that allow the software to analyze data with the motivation to more efficiently and accurately organize and analyze data [Figy 015].
As per claim 5, Myers teaches all the limitations of claim 4.
Myers may not explicitly teach the following. However, Figy teaches:
wherein the plurality of predefined categories includes a miner selling event associated with an outflow of crypto assets generated by miners; Figy 0081-0094: “The example system 400 also includes an order request miner 410. The order request miner 410 analyzes the market information obtained by the market information request handler 405. The order request miner 410 analyzes the market information to determine information relevant to the graphical representation request of the user, the relevant information is parsed and made available to the renderer 415 for graphical representation. Such information to be graphed may include, a range of prices associated with orders for a time interval. For example, the range of prices associated with orders for the time interval may comprise all prices detected for a volume of order activity for each price in the price range, and a type of order for each of the volume of order activity. The order request miner 410 separates the volume of order activity at each price in the price range into buy order volume and sell order volume… the order request miner 410 determines a value area for buy orders and/or sell orders. A value area refers to a price (or a range of prices) associated with a threshold amount (e.g., a large portion) of buy and/or sell orders. For example, if the value area is set to 70%, then the range of prices associated with 70% of the order volume for buy orders and 70% of the order volume for sell orders is determined by the order request miner 410. In some examples, the threshold amount may be determined by a user of a trading device, an administrator of trading devices, and/or a default value.
Myers and Figy are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Myers with the aforementioned teachings from Fugy with a reasonable expectation of success, by adding steps that allow the software to analyze data with the motivation to more efficiently and accurately organize and analyze data [Figy 015].
Claims 13 and 15 are directed to the method for performing the system of claims 3 and 5 above. Since Myers and Figy teach the method, the same art and rationale apply.
Claims 9-10 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent 10706472 (hereinafter “Myers”) et al., in view of U.S. PGPub 20230316403 to (hereinafter “Sogani”) et al.
As per claim 9, Myers teaches all the limitations of claim 1.
Myers may not explicitly teach the following. However, Sogani teaches:
wherein the plurality of signal classification rules includes: - using Bollinger Band to detect an outlier; - using a tsmoothie function to detect the outlier; or - using predefined logics associated with the plurality of seasoned factors each associated with generation and/or transaction of the exchangeable asset; wherein the outlier represents a signal trigger; Sogani 0023-0026: “In a specific embodiment, the token economics related parameters may include at least one of a token code, a type, number of coins issued as per contact, total holders, total supply, total circulation, volume, exchanges, pairs, trapped transactions, flagged wallet associations, a listing price, a current price as on, region of interest, charts, Bot analysis, volume analysis, EMA, RSI, MACD, flow index, parabolic SAR. trend line analysis, VPVR, MA, historic trading volumes. Bollinger, Chainkin, money flow index or a combination thereof. In another embodiment, the general project related parameters may include at least one of a website, social media handles, information links, major PR coverage, phone, contact address, contact person, deep web search or a combination thereof… Furthermore, the processing subsystem 15 includes a digital asset data maintenance module 30 operatively coupled to the data collection module 20. The digital asset data maintenance module 30 stores the information collected by the digital asset data collection module into a blockchain 40. As used herein, the blockchain is a growing list of records, called blocks which is distributed to several nodes who maintain the copy of records, that are linked using cryptography. The blockchain 40 is resistant to modification of the data. The blockchain 40 is an open, distributed ledger that may record transactions between two parties efficiently and in a verifiable and permanent way. In one embodiment, the blockchain 40 may be a public blockchain. The public blockchain allows individuals who do not know each other to trust a shared record of events without the involvement of an intermediary or third party irrespective of the industry type. In another embodiment, the blockchain 40 may be a private blockchain. In the private blockchain participants are known and are granted read and write permissions by an authority that governs the use of the blockchain. For example, the private blockchain participants may belong to the same or different organizations within an industry sector. In various embodiments, these relationships may be governed by informal relationships, formal contracts or confidentiality agreements.”
Myers and Sogani are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Myers with the aforementioned teachings from Sogani with a reasonable expectation of success, by adding steps that allow the software to analyze data with the motivation to more efficiently and accurately organize and analyze data [Sogani 0023].
As per claim 10, Myers teaches all the limitations of claim 1.
Myers may not explicitly teach the following. However, Sogani teaches:
further comprising an output module arranged to generate a summary of analysis including the evaluation score of the market, a score calculated for each of the plurality of predefined categories, a score calculated for each of the plurality of seasoned factors, a score indicating past accuracy, a score indicating confidence level and/or a change of real value of each seasoned factor.; Sogani 0028-0047: “Moreover, the processing subsystem 15 includes a data assessment module 50 operatively coupled to the digital asset data maintenance module 30. The data assessment module 50 assesses the information, updated by the data maintenance module 30, stored in the blockchain 40 to obtain multiple research products and other products. On embodiment 45 of the multiple research products and the other products is shown in FIG. 1(a). In one embodiment, the multiple research products may include but not limited to at least one of a rating report, a research report, an intelligence report, an educational report, market indices report, on demand service report, a blockchain forensics report related to transaction tracing or a combination thereof. In another embodiment, the other products may include research, intelligence, reporting, auditing, forecasting, other products backed by reliable research or the like. The data may also be used to publish newsletters and informative research articles by several researchers. As used herein, rating report includes a rating which is more of a certification where the system take guarantee of the score. This is mainly research but the system uses the scoring process mentioned in the document for assessment of the score for the same. The research report consists of data from the data source points but is usually not very detailed as the data is rolled out in the public domain for viewing. Hence sensitive information pertaining to the project such as passport, contacts, bank account numbers, or the like are hidden. Only information which is available publicly is aggregated and given. The intelligence report uses the data from the above process plus other surveillance techniques depending on the expertise of the professional human resources deployed. The due diligence report includes a feasibility of the of a project, legal, financial, technology and directors background along with artificial intelligence/facial recognition-based models 11 to verify identity of the individual and provide authentication management. The report is usually for investors who want to verify the whereabouts of a project before investing to make sure it’s not a scam or a project with bad intentions… Furthermore, the method 200 includes assessing the information, updated by the crypto and digital asset data maintenance module, stored in the blockchain to obtain multiple research products in step 240. In one embodiment, assessing the information stored in the blockchain to obtain multiple research products may include assessing the information stored in the blockchain to obtain multiple research products by a data assessment module. In a specific embodiment, assessing the information stored in the blockchain to obtain multiple research products may include assessing the information stored in the blockchain to obtain at least one of a rating report, a research report, an intelligence report, an educational report, market indices report, on demand service report, a blockchain forensics report, a transaction tracing report or a combination thereof.”
Myers and Sogani are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Myers with the aforementioned teachings from Sogani with a reasonable expectation of success, by adding steps that allow the software to analyze data with the motivation to more efficiently and accurately organize and analyze data [Sogani 0023].
Claims 19-20 are directed to the method for performing the system of claims 3 and 9-10 above. Since Myers and Sogani teach the method, the same art and rationale apply.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
A SYSTEM FOR DIGITAL ASSET EXCHANGE, A DIGITAL WALLET AND AN ARCHITECTURE FOR EXCHANGING DIGITAL ASSETS, .U.S. PGPub 20230011788 The present invention relates to a system for digital asset exchange, a digital wallet and an architecture for exchanging digital assets, and particularly, although not exclusively, to a system, wallet and architecture incorporating thereof arranged for the exchange of digital assets.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Arif Ullah, whose telephone number is (571) 270-0161. The examiner can normally be reached from Monday to Friday between 9 AM and 5:30 PM.
If any attempt to reach the examiner by telephone is unsuccessful, the examiner’s supervisor, Beth Boswell, can be reached at (571) 272-6737. The fax telephone numbers for this group are either (571) 273-8300 or (703) 872-9326 (for official communications including After Final communications labeled “Box AF”)./Arif Ullah/Primary Examiner, Art Unit 3625