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 .
Detailed Action
This Non-Final Rejection Office Action is in response to Applicant’s filing of 03/28/2024.
Claims 1 – 37 are pending.
The effective filing date of the present application is 12/01/2022.
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 – 37 are rejected under 35 U.S.C. 101 because the claimed invention is the claimed invention is directed to an abstract idea without significantly more.
At Step 1 of eligibility analysis, the instant claims are directed towards a system and a method; thus, all claims fall within one of the four statutory categories considered appropriate subject matter.
At Step 2A, Prong One, of analysis, the claims set forth a method of document review, editing, and modifying, and then display using a customized format. The claims describe limitations that can practically be performed in the human mind, including for example, observations (receiving, validating, identifying), evaluations (classifying reconstructing, transforming), judgments, and opinions (modify, adjustment). These limitations then describe a mental process. An example of a claim that recites a mental process is a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” Electric Power Group, LLC v. Alstom,S.A.
It is further noted that claims can recite a mental process even if they are claimed as being performed on a computer. Because the claims recite limitations that can practically be performed in the human mind, (from a customer, from a user) the limitations fall within the mental processes grouping, and the claim recites an abstract idea.
Claim 19, which is illustrative of claims 1 and 37, contains those elements that define this abstract idea (and are highlighted below):
A computer-implemented method for applying rules via artificial intelligence for document processing, the method being performed by at least one processor, comprising:
receiving a plurality of documents from a customer via a first user interface;
validating a number and a type of the plurality of documents;
selecting a plurality of machine learning models based on the plurality of documents;
identifying a file type and a format of the plurality of documents based on the plurality of machine learning models;
extracting a first data set from the plurality of documents based on the plurality of machine learning models using the identification of the file type and the format of the plurality of documents;
classifying the first data set based on the plurality of machine learning models using the identification of the file type and the format of the plurality of documents;
reconstructing the first data set into a structured data set based on the plurality of machine learning models using the extraction and classification of the first data set;
transforming the structured data set into a customized new presentation of the structured data set;
receiving input from a user via a second user interface to modify the customized new presentation;
performing an adjustment to the plurality of machine learning models based on the input from the user;
modifying the customized new presentation based on the adjusted plurality of machine learning models; and
displaying to the customer via the first user interface the modified customized new presentation.
At Step 2A, Prong Two, the Examiner has determined that the identified abstract idea (judicial exception) is not integrated into a practical application because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP 2106.05(f). Further, in MPEP 2106.05(f) it is noted that simply adding a general-purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Therefore, according to the MPEP, this is not solely limited to computers but includes other technology that, recited in an equivalent to “apply it,” is a mere instruction to perform the abstract idea on that technology.
Claims 1, 19, and 37, recite only the following additional elements:
A computer system, the system comprising: a database; a memory storing instructions; and at least one processor configured to execute the stored instructions;
a first user interface;
a plurality of machine learning models;
a structured data set (embedded code);
a second user interface.
The computer system and interfaces are mere instructions to apply the abstract idea to a computer, per MPEP 2106.05(f). Applicant has described these computing elements generically in their disclosure, at Specification [0020, 0024, 0025, and 0028] and Figure 1B as filed. See [0025]: “A user may access customer UI 104 via, e.g., a web-enabled device such as a personal computer.”
Machine learning models describe mere instructions to implement an abstract idea or other exception on a computer – via artificial intelligence. Noting that a machine learning model in AI is an algorithm that is trained on a dataset, the Examiner looks to the instant disclosure as how this algorithm (plurality of machine learning models) is employed. “The artificial intelligence in system 100 may optimize and/or leverage the usage of the one or more machine learning models and/or algorithms to process the data in the plurality of documents to meet a customer’s request for an output of transformed data.” Specification [0022]. See also [0033]: “For example, AI module 108 may comprise a plurality of machine learning models and/or algorithms that have been trained to specific processing tasks based on, e.g., the file type (such as .docx, pdf, .xls., .png, etc.), the industry (such as, e.g., health care, human resources, finance, etc.), and/or specific document types (such as, e.g., financial statements, invoices, etc.). Thus, the disclosure broadly and generically describes the system for processing documents. This use of AI is an equivalent to “apply it,” and is a mere instruction to perform the abstract idea on that technology.
The recitation of structured data is a reference to data formatted in a certain way that is also instructions to implement the abstract idea on a computer as exemplified in Intellectual Ventures I v. Capital One Fin. Corp., 850 F.3d 1332, 121 USPQ2d 1940 (Fed. Cir. 2017). Those claims were found to be directed to the abstract idea of "collecting, displaying, and manipulating data." (Emphasis added). Analogous to the instant claims is merely using the abstract idea in the context of structured data within the plurality of documents. Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application. The claims are directed to an abstract idea.
At Step 2B of eligibility analysis, the Examiner has determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they do not amount to more than simply instructing one to practice the abstract idea within a computer environment to perform the steps that define the abstract idea. As discussed above, the additional elements of: (a computer system comprising: a database; memory storing instructions; and at least one processor; a first user interface; a second user interface; a plurality of machine learning models; a structured data set (embedded code), amounts to no more than mere instructions to implement an abstract idea on a computer. Mere instructions to apply an exception within a computer environment cannot provide an inventive concept. See MPEP 2106.05(f).
Dependent claims 2, 3, 9, 16, 20, 21, 27, and 34, contain limitations that are further refinements to the same abstract idea found in claims 1 and 19. Recitations to a type of document, subsets of those documents, and classification of data within the documents, are refinements of the method of document review, editing, and modifying. They are directed to the abstract idea identified and not patent eligible. See MPEP 2106.04(d). Further, these limitations are no more than instructions to implement the abstract idea within a computer environment, per MPEP 2106.05(f).
Dependent claims 4 – 6, 10 – 12, 22 – 24, and 28 – 30, contain limitations that are further refinements to the same abstract idea found in claims 1 and 19. Recitations to using machine learning models (master model), adjusting models, extracting data using the models, and optimizing the models, are further recitations to machine learning models via AI. This use of AI is an equivalent to “apply it,” and is a mere instruction to perform the abstract idea on that technology. See MPEP 2106.05(f).
Dependent claims 7, 8, 25, and 26, contain limitations that are further refinements to the same abstract idea found in claims 1 and 19. Recitations to a third party or local server, is no more than instructions to implement the abstract idea within a computer environment, per MPEP 2106.05(f).
Dependent claims 14 – 18, and 32 – 36, contain limitations that are further refinements to the same abstract idea found in claims 1 and 19. Recitations to corrections based on data extraction via the user interfaces, are refinements of the method of document review, editing, and modifying, and require user interaction and evaluation based on confidence. They are directed to the abstract idea identified and not patent eligible. See MPEP 2106.04(d). Further, these limitations are no more than instructions to implement the abstract idea within a computer environment, per MPEP 2106.05(f).
Dependent claims 13 and 31 contain limitations that are further refinements to the same abstract idea found in claims 1 and 19. Recitations to a JSON is no more than a reference to a structured data format; therefore, it is utilizing the computer to receive, store, or transmit data) and does not integrate a judicial exception into a practical application or provide significantly more. See MPEP 2106.05(f).
Therefore, for the reasons set above, claims 1 – 37, are directed to an abstract idea without integration into a practical application and without significantly more.
Claims Distinguished over Prior Art
Regarding claims 1, 19, and 37, prior art does not teach nor suggest a system or method as claimed. Cited prior art discloses methods for document processing using hybrid rule-based AI mechanisms (Bade). Other art teaches AI based document processors (Priestas and Tucker). However, the Examiner points to the recited combinations of elements that are not taught or suggested by the cited prior art of record within claims 1, 19, and 37; specifically:
validating a number and a type of the plurality of documents;
extracting a first data set from the plurality of documents based on the plurality of machine learning models using the identification of the file type and the format of the plurality of documents;
classifying the first data set based on the plurality of machine learning models using the identification of the file type and the format of the plurality of documents;
reconstructing the first data set into a structured data set based on the plurality of machine learning models using the extraction and classification of the first data set;
transforming the structured data set into a customized new presentation of the structured data set;
receiving an input from a user via a second user interface to modify the customized new presentation;
performing an adjustment to the plurality of machine learning models based on the input from the user;
modifying the customized new presentation based on the adjusted plurality of machine learning models; and
displaying to the customer via the first user interface the modified customized new presentation.
Dependent claims 2 – 18 and 20 – 36, based on their dependency to claims 1 and 19, and containing further limiting recitations, are also not disclosed by prior art. Accordingly, claims 1 – 37 are distinguished over prior art.
Noting that patentability of any claimed invention under 35 U.S.C. §§102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101, the Examiner points to other rejections within this Office Action.
Applicant is utilizing a combination of AI performed steps for document processing not suggested by the prior art. However, the instant additional elements in the claims amount to no more than “apply it” and do not reflect an improvement to a computer or other technology, as detailed earlier.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Bade discloses methods for document processing using hybrid rule-based AI mechanisms. Priestas and Tucker teach AI based document processors. Garg discloses a method for analysis of structured and unstructured data. The NPL document teaches automated processing of unstructured documents using AI.
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DONALD J. EDMONDS
Examiner
Art Unit 3629
/SARAH M MONFELDT/Supervisory Patent Examiner, Art Unit 3629
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