Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on November 06, 2025, has been entered.
Response to Arguments
Applicant’s comments with respect to the rejection under 35 USC 112, along with the amendments to claims 1, 11 and 16, have been fully considered and are persuasive. The rejection under 35 USC 112 of claims 1, 11 and 16 has been withdrawn.
Applicant's arguments filed with respect to rejections under 35 USC 101 have been fully considered but they are not persuasive. Applicant argues the claims are not directed to a method of organizing human activity and points to claim language such as extracting data from a data store, executing a first machine learning model defined by a classifier, etc., cannot be performed by a human mind. First, whether the steps can be performed in the human mind is not relevant to certain methods of organizing human activity. Certain methods of organizing human activity is limited to activity that falls within the enumerated sub-groupings of fundamental economic principles or practices, commercial or legal interactions, and managing personal behavior and relationships or interactions between people. The sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the "certain methods of organizing human activity" grouping. As described in the rejection, the claims are directed to the rules and instructions one would follow to compile a survey for a set of respondents. In addition, implementing a survey, i.e., between managers and employees as discussed in the specification, is business relations, also a sub category of certain methods of organizing human activity. The use of an application executing machine learning models to facilitate how the surveys are generated does not provide a technological improvement. The improvement is to the customized survey that includes analysis and evaluation of predicted answers which is an abstract concept as laid out in the rejection below.
Per 2106.04(a) I, “When finding that a claim is directed to such an improvement, it is critical that examiners give the claim its broadest reasonable interpretation (BRI) and evaluate both the specification and the claim. The specification should disclose sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement, and the claim itself must reflect the improvement in technology. Other important considerations are the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome, and whether the BRI is limited to computer implementation.” And further, from 2106.05(a), “If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. An indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art.”
On page 11, Applicant refers to several examples of how the invention “improves system efficiency across processing, memory, storage and network layers”. The specification, however, does not include an explicit recitation of any such improvement to the technology or functioning of a computer. The Federal Circuit has indicated that a claim must include more than conventional implementation on generic components or machinery to qualify as an improvement to an existing technology. See Affinity Labs of Tex. v. DirecTV, LLC. In this case, the claims only require a computing process executed by a general purpose computer. In addition, in FairWarning, IP, LLC v. Iatric Sys., accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, was found to be insufficient to show an improvement in computer-functionality.
In response to Applicant’s assertion that the machine learning models execution closes the feedback loop and refines the classifiers operating data, the spec at [0058] refers to the machine learning which is described at such a high level of generality that it amounts to adding the words apply it with the abstract idea. While applicant contends that the system reduces unnecessary computations, lowers CPU cycles, memory usage, bandwidth consumption, etc., Examiner points out the specification does not discuss these as improvements of the claimed invention as discussed in the paragraph above. For these reasons, the comparison to Desjardins is unfounded. The facts of the claims in Desjardins do not align with the facts of the instant application. In addition, the specification was relied on in the Desjardins case to support the technological improvement whereas, there is not an analogous description of any technological improvement in the instant specification.
Applicant argues that the claimed invention is statutory by attempting to analogize the claimed invention to the claims analyzed and found eligible in the Federal Circuit’s McRO decision, specifically by alleging that the amended claims recite specific software based structures and processes that improve computer operation and integrate the abstract idea into a practical application. Examiner emphasizes that the claims in McRO were directed toward using limited rules in a process specifically designed to achieve an improved technological result in conventional industry practice, such that the claimed solution represents a technological improvement over the existing, manual 3-D animation techniques. Therefore, McRO’s claims are distinguishable from Applicant's claims because the limited rules or “mathematical relationships" involved in the claimed invention are not rooted in, or reasonably understood as encompassing, a technological solution that represents a technological improvement. The “mathematical relationships” of the claimed invention merely evaluate survey information (i.e. via market exchange value, relative proximity, etc.) in efforts to generate a survey with a subset of questions based on data predictors. The additional elements in the claims amount to instructions to implement the abstract idea on a computer and do not integrate the abstract idea into a practical application. For these reasons, the claims do not meet the requirements of Step 2B.
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.
Claim(s) 1, 5, 7-11, 16 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. Claim(s) 1, 5, 7-11, 16 is/are directed to a method, system, and computer program product. Thus, all the claims are within the four potentially eligible categories of invention (a process, a machine and an article of manufacture, respectively), satisfying Step 1 of the Subject Matter Eligibility (SME) test.
As per Prong One of Step 2A of the §101 eligibility analysis provided in the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG), the Examiner notes that the claims are directed to a judicial exception since they are directed to certain methods of organizing human activity. More specifically, in the independent claims, the steps of
extracting,
determining,
performing predictive modelling, using machine learning model amounts to instructions to perform the abstract idea using a computer to implement a mathematical model]
determining, model, data predictors for each question in the set of questions for each respondent in the set of respondents, the data predictors comprising a metric and being a type of predictor output by the
determining,
compiling,mind or with pen and paper – by the application amounts to using a computer as a tool to perform the abstract idea]
formatting,
communicating, and
updating,
recite certain methods of organizing human activity as they are directed to the rules and instructions one would follow to compile a survey for a set of respondents. In addition the claims relate to surveys between entities or companies and their managers to collect information from users or employees therefore the claimed invention is business relations which is certain methods of organizing human activity. Also, as indicated in the claim above, the steps amount to mental processes which are abstract. The recitation of an application and machine learning models defined by random forest algorithm does not negate the abstract nature of these limitations because the claim merely implements the random forest algorithm to perform mathematical operations involved with predictive modelling using a computer.
The nominal recitation of computer elements such as an application implementing machine learning models in claim 1, a non-transitory computer readable medium tangibly encoded with instructions that when executed by a processor a device perform the method, and device comprising a processor do not indicate the claimed invention is not an abstract idea as evidenced by the analysis at Prong 2 of Step 2A.
Regarding Prong Two of Step 2A, a claim directed to an abstract idea must be analyzed to determine if the claim recites additional elements that integrate the judicial exception into a practical application. Limitations that are indicative of integration into a practical application include: Improvements to the functioning of a computer, or to any other technology or technical field, as discussed in MPEP 2106.05(a); Applying or using a judicial exception to effect a particular treatment or prophylaxis for disease or medical condition – see Vanda Memo; Applying the judicial exception with, or by use of, a particular machine, as discussed in MPEP 2106.05(b); Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP 2106.05(c); and Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP 2106.05(e) and the Vanda Memo issued in June 2018.
In this case, the claims do not include limitations that meet the criteria listed above, thus the abstract idea is not integrated into a practical application. The device in claim 1 amounts to using a computer as a tool to perform the abstract idea therefore there is no integration into a practical application. In claim 11, a processor executing instructions tangibly encoded on a non-transitory computer readable media also amounts to implementing an abstract idea on a computer and therefore there is no integration into a practical application. Similarly, the device of claim 16 amounts to using a computer as a tool to perform the abstract idea and therefore the abstract idea is not integrated into a practical application. The claims invoke machine learning models merely as a tool for making the recited predictive mathematical calculations rather than purporting to improve the technology or computer. See MPEP 2106.05(f). Therefore, the limitation represents no more than mere instructions to apply the judicial exception on a computer and can also be viewed as nothing more than an attempt to generally link the use of the abstract idea to the technological environment of computers.
Further, the claims do not include limitations beyond generally linking the use of the abstract idea to a particular technological environment. When considered individually, the system and software claim elements only contribute generic recitations of technical elements to the claims. It is readily apparent for example, that the claim is not directed to any specific improvements of these elements. The invention is not directed to a technical improvement. When the claims are considered individually and as a whole, the additional elements noted above appear to merely apply the abstract concept to a technical environment in a very general sense.
The dependent claims further limit the abstract idea and recite additional elements that do not integrate the abstract idea into a practical application.
Claim 5 is directed to analyzing data predictors and determining a subset of questions which add further detail to the abstract idea without any additional elements to integrate the abstract idea into a practical application.
Claims 7, 8 and 10 are also directed to additional steps of the method which add detail to the abstract idea. The claims do not include additional elements (beyond the claimed device) to integrate the abstract idea into a practical application.
In claim 9, use of a natural language processor amounts to using a computer as a tool to process the request data. Claimed at such a high level of generality, there is no improvement to any technology and there is no integration into a practical application.
Lastly and in accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instruction to apply the exception using generic computer component. Mere instruction to apply an exception using generic computer components cannot provide an inventive concept.
Allowable Subject Matter
But for the rejection under 35 USC 101, the claims contain allowable subject matter. Specifically, the cited prior art, taken alone or in combination, fails to teach the specific combination of claim limitations. Neither Mizrahi et al, Kristal et al, or newly cited Kopikare et al teach the specific steps of determining projected answers based on question data and respondent data, determining data predictors indicating difference between respondent behavior between projected answers and past activity and determining a subset of questions – all based on analysis of the data predictors based on execution of machine learning models.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNA LOFTIS whose telephone number is (571)272-6736. The examiner can normally be reached M-F 7:00am-3:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Brian Epstein can be reached at 571-270-5389. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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JOHNNA LOFTIS
Primary Examiner
Art Unit 3625
/JOHNNA R LOFTIS/Primary Examiner, Art Unit 3625