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 .
This action is in reply to the request for continued examination filed on 07/21/2025.
Claim 1 has been amended.
Claims 1-5 have been examined and are pending.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 07/21/2025 has been entered.
Remarks
With regard to the 101 rejection, the arguments have been considered but they are not persuasive. In Page 5, the Applicant amended the claim limitations and asserted that “the independent claim as amended as a whole are not “directed to” an abstract idea such as, for example, commercial interaction, and should be patent eligible under 35 U.S.C. 101.” However, under step 2A analysis, the limitations are not indicative of integration into a practical application. They are adding the words “apply it” with the judicial exception, or mere instructions to implement an abstract idea on a computer – see MPEP 2106.05(f). Also, under step 2B analysis, the limitations are not indicative of an inventive concept (aka “significantly more”). They are adding the words “apply it” with the judicial exception, or mere instructions to implement an abstract idea on a computer – see MPEP 2106.05(f). Therefore the claim is not patent eligible under 35 U.S.C. 101.
The Examiner has raised a 35 U.S.C. 103 rejection given the new ground(s) of rejection and new art has been found. Please refer to the rejection below for further details.
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 1-5 are directed to a system, a method which is one of the statutory categories of invention. (Step 1: YES).
Claims 1-5 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-5 are directed to an abstract idea, Method of Organizing Human Activity. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea.
Claim 1 recites, in part, a computer-implemented method of selecting investments for an investor's portfolio, the computer-implemented method comprising: receiving, from a user interface, data identifying one or more social-media accounts of the investor; extracting content including texts and images from the one or more social-media account; storing the content in a cloud database; executing a machine-learning model using the context as an input to generate a sentimental output from the group consisting of: positive, negative, or neutral; generating semantic tags describing the content, the semantic tags configured to be displayed on the user interface; identifying one or more market sectors, industries, or investments related to the content based one or more semantic tags selected by user operating the user interface and the sentimental output; presenting a proposed portfolio containing the one or more identified market sectors, industries, or investments; generating a short-term goal for the investor based on one or more semantic tags selected by the user; and educating the investor about a stock market using the proposed portfolio and the short- term goal. These limitations are directed to concepts performed in the human mind, via the use of generic computer components, such as Methods of Organizing Human Activity (generation of a stock portfolio by social media content). Hence, it falls within the “Commercial Interaction” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements such as computer, a user interface, a machine learning model recited at a high-level of generality (extracting, identifying, presenting) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea
Next the claim as a whole is analyzed to determine whether any element, or combination of elements, is sufficient to ensure the claim amounts to significantly more than an abstract idea. Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are merely performing the abstract idea on a generic device i.e., abstract idea and apply it. There is no improvement to computer technology or computer functionality MPEP 2106.05(a) nor a particular machine MPEP 2106.05(b) nor a particular transformation MPEP 2106.05(c). Thus, the claim is not patent eligible.
The dependent claims have been given the full two part analysis (Step 2A – 2-prong tests and step 2B) including analyzing the additional limitations both individually and in combination. The dependent claim(s) when analyzed both individually and in combination are also held to be patent ineligible under 35 U.S.C. 101 because for the same reasoning as above and the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea. The additional limitations of the dependent claim(s) when considered individually and as ordered combination do not amount to significantly more than the abstract idea.
The dependent claim(s) 2 when analyzed both individually and in combination are also held to be patent ineligible under 35 U.S.C. 101 because for the same reasoning as above and the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea. The additional limitations such as machine learning estimators, portfolio, general pricing trend, relative strength index (RSi), stochastic oscillator of the dependent claim(s) when considered individually and as ordered combination do not amount to significantly more than the abstract idea. The claim(s) does/do not include additional elements (such as a user interface) that are sufficient to amount to significantly more than the judicial exception because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
The dependent claim(s) 3 when analyzed both individually and in combination are also held to be patent ineligible under 35 U.S.C. 101 because for the same reasoning as above and the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea. The additional limitations such as machine learning estimators when considered individually and as ordered combination do not amount to significantly more than the abstract idea. The claim(s) does/do not include additional elements (such as a machine learning, a user interface) that are sufficient to amount to significantly more than the judicial exception because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
The dependent claim(s) 4, 5 when analyzed both individually and in combination are also held to be patent ineligible under 35 U.S.C. 101 because for the same reasoning as above and the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea. The concept such as selecting a proposed portfolio, determining a pricing change using a moving average , and executing an exchange of the security are directed to an abstract idea. They are adding the words “apply it” with the judicial exception, or mere instructions to implement an abstract idea on a computer – see MPEP 2106.05(f). The claim(s) does/do not include additional elements (such as a computing system) that are sufficient to amount to significantly more than the judicial exception because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Therefore, Claims 1-5 are not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3 are rejected under 35 U.S.C. 103 as being unpatentable over Ghosh et al. (US 2020/0293933 A1) in view of Misra (US 2022/0138256 A1) in further view of Drain, (US 2008/0077539 A1).
Claim 1 is disclosed: Ghosh teaches: storing the content in a cloud database; executing a machine-learning model using the context as an input to generate a sentimental output from the group consisting of: positive, negative, or neutral (Ghosh, see at least par. [0136] “In certain embodiments, the knowledge elements within a repository of hosted 714 or private 734 data may also include statements, assertions, beliefs, perceptions, preferences, sentiments, attitudes or opinions associated with a person or a group. As an example, user ‘A’ may prefer the pizza served by a first restaurant, while user ‘B’ may prefer the pizza served by a second restaurant . . .”) “Liking” or preferring corresponds to positive sentimental;
identifying one or more market sectors, industries, or investments related to the content based one or more semantic tags selected by user operating the user interface and the sentimental output (Ghosh, see at least par. [0195] “. . . In certain embodiments, based upon a particular context, extraction, parsing, and tagging operations are performed on language, text and images they contain to generate associated datasets 1214. In certain embodiments, the resulting datasets may include various transaction histories 1216, customer relationship management (CRM) feeds 1218, market data feeds 1220, news feeds 1222, social media feeds 1224, and so forth.” & par. [0196] “ . . . the cognitive models 222 may include quantitative 1228 models, qualitative 1230 models, ranking 1232 models, news topic 1234 models, sentiment 1236 models, and so forth.” & par. [0197] “In certain embodiments, the cognitive skills 226 may include a portfolio profile builder 1242 skill, a client profile builder 1244 skill, a market data pipeline 1246 skill, a market event detection 1248 skill, a cognitive insights ranking 1250 skill, and so forth. As likewise described in greater detail herein, the resulting cognitive skills 226 may then be used in various embodiments to generate certain cognitive agents 250. In certain embodiments, the resulting cognitive agents 250 may include sourcing 432 agents, destination 434 agents, engagement 436 agents, compliance 438 agents, and so forth.”) The cited portion discusses how the system can extract the data and leverage the data feed to identify appropriate “cognitive agent” that corresponds to the market or industry indicators ;
and presenting a proposed portfolio containing the one or more identified market sectors, industries, or investments (Ghosh, see at least par. [0205] “. . . The output of the training process is an ML model which can then be used to make predictions. In certain embodiments, the training data may provide the basis for the learning algorithm to provide recommendations, perform medical diagnoses, make investment decisions, allow autonomous vehicles to recognize stop signs, and so forth.”) The output of the training process can generate or present investment recommendation or decision ;
Ghosh does not disclose the following; however, Misra teaches:
A computer-implemented method of selecting investments for an investor's portfolio, the computer-implemented method comprising: receiving, from a user interface (Misra, see at least par. [0067] “. . . In this embodiment, timeline program 110 can integrate objects depicted with a user interface such as a time selectable slide option that provides the user with the ability to view an event from multiple periods of time.”), data identifying one or more social-media accounts of the investor (see at least par. [0088] “. . . In some embodiments, timeline program 110 organizes portions of event (i.e., detected objects in media received) based on metadata associated with received content (e.g., geo location and time stamps). In embodiments where timeline program 110 is unable to read metadata associated with received content or otherwise cannot access the metadata, timeline program 110 can reference social media website and other public crowdsourced data to identify a time associated with similar content . . .”) the system can access data from social media account;
extracting content including texts and images from the one or more social-media account (Misra, see at least par. [0088] “. . . For example, where timeline program 110 receives content (e.g., image, text, audio, video, etc.) from a user, timeline program 110 can access a social media account of the user (with the user's permission) and read user generated text (e.g., any tags the user adds that describe the event) and identify other user generated tags associated with similar content (e.g., timeline program 110 can identify concert 1 by band X and find other content with time and location information for concert 1 by band X).”);
generating semantic tags describing the content, the semantic tags configured to be displayed on the user interface (Misra, see at least par. [0083] “In step 408 timeline program 110 integrates the generated visual representation into a user display . . .” & see at least par. [0088] “. . . For example, where timeline program 110 receives content (e.g., image, text, audio, video, etc.) from a user, timeline program 110 can access a social media account of the user (with the user's permission) and read user generated text (e.g., any tags the user adds that describe the event) and identify other user generated tags associated with similar content . . .”) the tags are generated based on content;
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Ghosh by performing data extraction on social media as taught by Misra, because modifying Ghosh using elements taught by Misra helps to better generate a visual representation of an event for portfolio management (abstract). Therefore, the claimed invention is obvious in view of the cited references.
Ghosh in view of Misra does not disclose the following; however, Drain teaches:
generating a short-term goal for the investor based on one or more semantic tags selected by the user (Drain, (US 2008/0077539 A1), see at least par. [0529] “ In the present example, a default is set of all companies being graded using the criteria explained above and in the short and long-term tables, which assigns the overall final grades based on a balanced view of the four main categories of the fundamental analysis . . .”);
and educating the investor about a stock market using the proposed portfolio and the short- term goal (Drain, see at least par. [0029] “Thus, the present example can provide an analysis system for determining the performance and financial condition of a plurality of business entities with the ultimate purpose being to help investors better understand the intricacies of successful investing and thereby empower them to make their own educated decisions. In addition, specific tools can be made available to aid in the investing and trading of securities, including both stocks and bonds, of the various business entities being evaluated . . .”) the analysis system provides an overview of any short term investment for investors to make educated investment.
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Ghosh in view of Misra by providing short term goal for investor as taught by Drain, because modifying Ghosh in view of Misra using elements taught by Drain helps to better provide a portfolio landscape for the investor (abstract). Therefore, the claimed invention is obvious in view of the cited references.
Claim 2. Ghosh in view of Misra in further view of Drain teaches: The computer-implemented method of claim 1. However, Misra teaches: wherein the proposed portfolio has a composition weighted at least partially based on a distribution of content within the one or more social media accounts (Misra, see at least Claim 3 “. . . wherein determining a level of significance of an event in a database of events based on context comprises: accessing contextual data associated with received content; generating a score for an event by assigning weight values to one or more objects associated with the event; and adding the assigned weight values for the one or more objects.”) the weighted factor is applicable from objects such as social media account.
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Ghosh in view of Misra in further view of Drain by performing data extraction on social media as taught by Misra, because modifying Ghosh in view of Misra in further view of Drain using elements taught by Misra helps to better generate a visual representation of an event for portfolio management. Therefore, the claimed invention is obvious in view of the cited references.
Claim 3. Ghosh in view of Misra in further view of Drain teaches: The computer-implemented method of claim 1. Furthermore, Ghosh teaches: wherein the semantic tags are generated using a previously trained machine-learning estimator (Ghosh, see at least par. [0218] “. . . In certain embodiments, performing the classifying operation results in certain data elements included in the training corpus 1302 being trained for use by the opaque model 1332 . . .”).
Claims 4, 5 are rejected under 35 U.S.C. 103 as being unpatentable over Ghosh et al. (US 2020/0293933 A1) in view of Misra (US 2022/0138256 A1) in further view of Drain, (US 2008/0077539 A1) in further view of Krishnan (US 2020/0202436 A1).
Claim 4. Ghosh in view of Misra in further view of Drain teaches: The computer-implemented method of claim 1. However, Krishnan teaches: further comprising:(a) selecting a security from the proposed portfolio;(b) determining a general pricing trend of the security using an exponential moving average (EMA) (Krishnan, US 2020/0202436, see at least par. [0161] “. . . to build an algorithm that would use randomized values from historical data to predict stock prices in the future. The selection of stocks was carefully chosen and then import packages (such as ScKit-Learn, which is a free online Python-based machine learning library) were used to import the basic random forest technique itself. Next, to build the algorithm and then “train” the algorithm was performed by creating a set of estimators (decision trees—these are basically pathways that depict various outcomes based on certain decisions) that would optimize my stock investment portfolio. In addition, there is included a set of stock indicators such as Simple Moving Average, Relative Strength Index, Moving Average Convergence Divergence Signal, Exponential Weighted Moving Average, and Bollinger Bands—all of which help analyze and track stock movements and prices . . .”);(c) determining an instant pricing trend of the security using another exponential moving average (EMA);(d) determining a relative strength index (RSI) to determine an exchange momentum of the security (par. [0160] “. . , Relative Strength Index, Moving Average Convergence Divergence Signal, Exponential Weighted Moving Average, and Bollinger Bands—all of which help analyze and track stock movements and prices . . .”). ; and(e) determining a momentum of a current price of the security in relation to a price range of the security over a period of time using a stochastic oscillator (par. [0164] “The snippet code above includes the stock picks in a diversified asset portfolio and various performance indicators [such as Simple Moving Average (SMA), Relative Strength Index (RSI), Moving Average Convergence Divergence Signal (MACDS), Exponential Weighted Moving Average (EWMA), and Bollinger Bands (BBands)] found within a string of code. All of these performance indicators help analyze and track stock movements and their prices.”) stock movements correspond to momentum of current price.
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Ghosh in view of Misra in further view of Drain by performing portfolio calculations as taught by Krishnan, because modifying Ghosh in view of Misra in further view of Drain using elements taught by Krishnan helps to better generate optimal portfolio calculation. Therefore, the claimed invention is obvious in view of the cited references.
Claim 5. Ghosh in view of Misra in further view of Drain in further view of Krishnan teaches: The computer-implemented method of claim 4. However, Krishnan teaches: further comprising:(f) executing an exchange of the security (Krishnan, see at least par. [0021] “. . . presenting the predicted stock price in a graphic user interface; and providing alerts, messages or notifications on a display contained within the graphic user interface so that a user can trade on the stock in an anticipation of a predicted change in the stock price.) stocks trade can be executed upon the result of a prediction.
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Ghosh in view of Misra in further view of Drain in further view of Krishnan by performing portfolio calculations as taught by Krishnan, because modifying Ghosh in view of Misra in further view of Drain in further view of Krishnan using elements taught by Krishnan helps to better generate optimal portfolio calculation. Therefore, the claimed invention is obvious in view of the cited references.
Conclusion
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/TOAN DUC BUI/ Examiner, Art Unit 3693
/BRUCE I EBERSMAN/ Primary Examiner, Art Unit 3693