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 .
Claim Rejections - 35 USC § 101
Claims 21-40 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 21
Step 1 This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. The claim recites a computer-implemented method comprising determining features, applying a machine learning model to predict document type, predicting actions, modifying interfaces, receiving selections, executing actions, and generating modified documents. Thus, the claim is a process, which is one of the statutory categories of invention under 35 U.S.C. § 101.
Step 2A Prong 1 This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
Limitation 1 “determining, using at least one processor, one or more features associated with an electronic document in response to detecting interaction with the electronic document via an electronic document interface” This limitation is classified as a Mental Process. The determination of features and detection of user interactions represent conventional data evaluation steps that can be conceptually performed by a human reviewing documents. A person could observe how users interact with various documents, note what characteristics are associated with each interaction type, and compile this information into feature profiles without any specialized computer technology beyond basic observation and recording capabilities.
Limitation 2 “applying, using the at least one processor, a machine learning model trained using one or more historical sample features of one or more historical electronic documents to predict a type of the electronic document while interaction with the electronic document is occurring” This limitation is classified as a Mental Process. Prediction and classification represent a process that can be performed by a person reviewing historical data patterns. The ML model functions here as a tool to achieve predictive results through pattern recognition from training examples, similar to how pen-and-paper calculations or statistical analysis could accomplish the same outcome through manual comparison of document characteristics against known categories and their associated features.
Limitation 3: “predicting, using the at least one processor, using the machine learning model, one or more actions to be performed or can be performed on the electronic document based on a content of the electronic document, the type of the electronic document, and one or more historical actions performed on the one or more historical electronic documents having the type of the electronic document” This limitation is classified as a Mental Process. Predicting recommended actions based on document content, classification results, and historical action patterns represents decision-making logic that can be conceptually performed by a human. A person could review similar documents, observe what actions were previously taken on comparable documents, analyze those historical behaviors, and recommend appropriate next steps. This is an evaluation and comparison process executable in the mind or with pen-and-paper.
Step 2A Prong 2 This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
The additional elements:
modifying, using at least one processor, the electronic document interface to include an electronic element identifying the one or more actions
receiving, using at least one processor, using the electronic element, a selection of at least one action in the one or more action and executing the at least one action on the electronic document
modifying, using at least one processor, the electronic document in response to the executing
generating, using at least one processor, based on the modifying, a modified electronic document
MPEP § 2106.05(a) "Improvements to the Functioning of a Computer or to Any Other Technology or Technical Field
The claim merely recites desired end-results-predicting document types and actions, modifying interfaces, executing selections-without listing specific technical mechanisms showing how the computer achieves these results in an unconventional way. The additional elements do not provide improvements to the computer such as increasing processing speed, reducing required memory, improving network efficiency, or enhancing data security. The claim treats the computer merely as a tool for performing an abstract idea rather than improving the computer itself, automating conventional human activities with generic computing hardware.
MPEP § 2106.05(b) Particular Machine
The claim recites at least one processor without any indication that it is a specific, specialized device customized for document tasks. This standard microprocessor does not add meaningful constraints beyond what any modern computer could do. The core inventive concept can be performed by hand or with pen and paper without requiring specialized hardware. The computer is simply being used as a tool to execute automated mental processes.
MPEP § 2106.05(c) Particular Transformation
The claim describes modifying electronic documents and interfaces, but this represents mere data manipulation. Modifying an interface display and digital files are conventional computer operations that do not qualify as particular transformations. This represents transforming information representations rather than physical articles with tangible properties.
MPEP § 2106.05(e) Other Meaningful Limitations
The additional elements do not restrict the use of the judicial exception to a specific application that would prevent monopolizing the abstract idea itself. Each additional element represents standard, off-the-shelf software components used in completely normal ways, such as basic GUI programming, fundamental application input development, routine computer file execution, and conventional output generation. Even as an ordered combination, these elements merely follow the conventional workflow of an interactive software system presenting calculated results to a user.
MPEP 2106.05(f) Mere Instructions to Apply an Exception
The claim essentially tells a generic processor to perform document feature analysis, apply pattern recognition for prediction, and recommend actions, and then use conventional software operations to implement these instructions. This generic implementation lacks specific steps explaining how to accomplish the exception in an unconventional way. The functional language could equally describe what a human analyst would do when reviewing documents, comparing them against historical examples, and recommending next steps based on observed patterns. These elements are functionally equivalent to adding words like "apply using standard computer operations" without meaningful limits.
MPEP 2106.05(g) Insignificant Extra-Solution Activity
The additional elements represent standard data display, user interaction handling, file modification, and output generation added to implement results rather than core components of the exception itself. They do not use the prediction results to perform meaningful technical operations beyond standard computer functionality. They place no actual boundaries on how document classification can be performed, and the core exception still operates identically if these peripheral elements are removed from the claim.
MPEP 2106.05(h) Field of Use and Technological Environment
The claim does not restrict use to any particular industry field like banking, healthcare, or education. The recitation of an "electronic document interface" and processor-based operations are simply a field of use that attempts to limit the abstract idea to a particular technological environment.
Step 2B None of the additional elements represent unconventional steps or configurations beyond routine, well-understood practices in software development and document management systems. GUI modification for displaying recommendations, input reception through interface elements, file execution based on user selection, and output generation are all standard programming operations performed daily by developers building interactive applications. The claim limitations do not describe a specific, non-generic solution to a specific technical problem. While the specification may discuss document classification challenges, the claims themselves recite generic computer operations without explaining how they solve any particular technological deficiency in existing systems or improve computing functionality beyond what conventional software already accomplishes. The ordered combination of additional elements does not add "significantly more" than the abstract concept itself because each element represents standard computer functions used to implement pre- and post-solution activities around a mental process exception. The claim merely utilizes generic processors, displays, input mechanisms, file systems, and output generation capabilities in their most conventional forms—no independent inventive concept exists that would render this patent eligible under 35 U.S.C. § 101.
Claim 22 recites “wherein the one or more actions are identified based on the type of the electronic document.” This additional limitation merely clarifies how the abstract mental process operates rather than providing a technical solution. A person could equally determine what actions to recommend based on whether a document has been classified as a contract, invoice, or other category without any specialized computer technology. The claim does not have any additional limitations that amount to significantly more than the abstract idea.
Claim 23 recites “wherein the type of the electronic document is determined by the machine learning model using the one or more features of the electronic document.” A human could perform similar classification by manually comparing document characteristics against known categories and their defining attributes using pen-and-paper analysis or spreadsheet calculations. It simply states that a prediction tool performs standard classification based on input features. The claim does not have any additional limitations that amount to significantly more than the abstract idea.
Claim 24 recites “wherein the one or more features of the electronic document include at least one of: one or more terms used within the electronic document, one or more clauses used within the electronic document, one or more images within the electronic document, one or more entities associated with the electronic document, one or more permissions associated with the electronic document, one or more actions taken on the electronic document, one or more templates used to generate the electronic document, one or more characteristics of one or more entities, one or more characteristics of one or more entities associated with the electronic document, or any combination thereof.” Each listed feature type represents conventional information elements that can be extracted and evaluated by a human reviewer examining document content. This limitation is post-solution activities. The claim does not have any additional limitations that amount to significantly more than the abstract idea.
Claim 25 recites "wherein the electronic document interface is generated on a computing device." Merely specifying that conventional computer equipment generates the interface does not amount to significantly more than the abstract idea.
Claim 26 recites “wherein the one or more actions include at least one of: replacing text with one or more fields of the electronic document, replacing one or more clauses of the electronic document with one or more pre-approved versions of the one or more clauses, synchronizing the electronic document with a third-party computing system.” Replacing text fields, substituting clause content with approved alternatives, and syncing documents with external systems are all standard capabilities inherent in word processing software and collaboration platforms. The claim does not have any additional limitations that amount to significantly more than the abstract idea.
Claim 27 recites “wherein the one or more actions are determined based on at least one of: one or more actions executed by one or more entities, one or more actions executed with respect to one or more another electronic documents similar to the electronic document, one or more contextually similar actions.” The actions are determined based on historical entity behavior, similar document interactions, and contextually comparable activities represent conventional data comparison and pattern recognition-a person could review past behaviors of users who worked with similar documents, observe which actions were taken on analogous files, identify contextual similarities, and recommend appropriate next steps using manual research. The claim does not have any additional limitations that amount to significantly more than the abstract idea.
Claim 28-40 are similar to claim 21-27. The claims are rejected based on the same reasons.
Response to Arguments
Section – 35 U.S.C. 101
Pg. 9-10: Applicant argues that “… It is respectfully submitted that the currently claimed subject matter is neither directed to a) mathematical concepts, b) certain methods of organizing human activity, and c) mental processes. The recited subject matter does not fall into the categories of "Mental Processes" or "Mathematical Concepts" for at least the reasons below.
In particular, a human mind is not equipped to execute the combination of steps recited in the amended claim 21. Specifically, as previously stated, a human mind is not a machine learning model that is capable of performing a deep analysis of an electronic document to determine its features (e.g., a metadata) as well as historical features of historical documents to predict a specific type of document in real time (i.e., "while interaction with the electronic document is occurring," as recited in claim 21). In view of the complexity associated with a specific electronic document as well as other (e.g., historical) electronic documents, simultaneous analysis involved in the prediction of a particular type of electronic document while interaction (e.g., by a user) with the document is happening is beyond capacity of a human mind, and hence, cannot be practically performed in it…”
Applicant argues that “a human mind” is not equipped to execute the combination of steps recited in amended claim 21. Examiner respectfully disagrees because a claim recites a mental process if the steps can be conceptually performed in the mind or with pen and paper, regardless of whether a machine is used in practice.
The core limitations of Claim 21 fall within the “Mental Processes” because they describe basic information gathering, pattern recognition, and decision-making logic:
Determining features in response to detecting interaction: A human reviewer can observe user interactions while reading documents, noting which characteristics correlate with each interaction type. This is routine observation and recording of data.
Applying an ML model to predict document type: The recitation of a "machine learning model" describes the automated implementation of conventional pattern recognition. A person can perform this same step by reviewing historical data patterns, identifying characteristics of past document types, and classifying a new document based on those observed patterns.
Predicting actions based on content, type, and historical actions: This represents basic decision-making logic. A person can examine document content, identify its classification, look at what actions were taken on similar historical documents, and recommend appropriate next steps based on those data relationships.
Applicant emphasizes that the prediction occurs “while interaction with the electronic document is occurring.” This phrase merely adds a temporal constraint regarding when the steps take place. A person can perform real-time classification on-the-fly while reading and interacting with a document.
Applicant's argument concerning the complexity and simultaneous nature of the analysis. Computational complexity, data volume, or the speed of execution do not dictate eligibility. The underlying steps in the claim can be conceptually performed by a human, not whether a computer can execute them faster and more efficiently than a person.
Pg. 10, Applicant argues that “… Amended limitations of claim 21 go even further beyond capacity of the human mind by reciting further prediction actions performed by the machine learning model, where such model predicts actions to be performed or that can be performed on the electronic document. Such actions are predicted by the machine learning model using content of the electronic document, the predicted type of the electronic document, and historical actions performed on historical electronic documents having the type of the electronic document. Hence, the machine learning model, in real time, predicted type of the electronic document, analyzed the document, identified other electronic documents of the same type, determined actions performed on such documents, and predicted actions for performance on the electronic document. The human mind is clearly not equipped with such ability…”
Applicant argues that the human mind is not equipped to perform the prediction steps using an ML model with content, type, and historical actions.
Claim limitations are evaluated based on whether they can be conceptually performed by humans using mental processes, not based on computational speed, efficiency, or how fast a machine can execute the steps compared to a person.
The predicting actions based on content, type, and historical data describe a process a person can perform manually. A person can read a document to identify its substance, classify the document into a category or type, review what actions similar documents received in the past, and recommend appropriate next steps based on those observed patterns. This sequence represents basic decision-making and evaluation logic.
The “machine learning model” describes a tool for automation of conventional pattern recognition methodology. A human performs an identical analysis when manually comparing document characteristics against known categories and their associated historical behaviors. The claim does not describe specific ML algorithms or structural improvements to computing operations; it simply states that prediction occurs using trained models.
Pg. 10, Applicant argues that “… The predictions are then used for selection, via an electronic user interface, of specific actions from the predicted actions for performance on the electronic document. This involves various graphical processes, e.g., modification of electronic interfaces, selection of specific electronic elements corresponding to particular actions, etc. Once such actions are selected (or confirmed), the current subject matter executes them to generate a modified electronic document.
As such, the combination of the above steps along with all the underlying multiple-purpose programmable hardware and software components/networks (e.g., programmable processors, memory, etc.), etc. are entirely outside the realms of a human brain or a mathematical concepts…”
Using standard hardware and interfaces to run an abstract idea does not make a claim patent eligible.
The claim recites modifying an interface to show actions and receiving a user selection. These steps are standard ways to show results after calculations are finished. A human could simply write these recommendations on a piece of paper and let a user select one from the list. The computer screen is just a tool to present information, not a new technical improvement to computer hardware.
The claim recites executing an action and making a modified document. These steps are standard data editing tasks like replacing text or saving a file. A human could do the same work by writing changes in a notebook or printing a new page. The computer is only used to automate standard file editing.
Applicant mentions that the claim uses standard hardware like processors and memory. The claim does not change or improve how these processors and memory work. It just uses them as tools to run the mental process faster.
Applicant argues that the whole combination of steps is outside the human brain. The core part of the claim is predicting document types and actions. This core part is a method that a human can conceptually do. The extra steps-like showing a menu, clicking a button, and saving a file-are just ordinary software steps. The claim does not describe any real improvement to computer technology, such as making the processor faster or saving memory space. It only describes the final results of a standard document management system.
Pg. 10-11, Applicant argues that “… As stated prior-filed Amendment and Response, as noted in the 2019 PEG Update: "While a claim limitation to a process that 'can be performed in the human mind, or by a human using a pen and paper' qualifies as a mental process, a claim limitation that 'could not, as a practical matter, be performed entirely in a human mind' (even if aided with pen and paper) would not qualify as a mental process".1 Clearly, as a practical matter, there is no way for a human mind to perform the operations recited in the amended claim 21. As such, the combination of limitations recited in claim 21 does not qualify as a mental process even if a human would attempt to perform them with the aid of a pen and paper. Hence, the Examiner's assertion that claim 21 is directed to an abstract idea is improper.
The current subject matter, as recited in claim 21, presents a technical improvement to the Thus, claim 21 does not recite a mental process or a mathematical concept. Accordingly, the Office's rejection fails to meet the Office's burden to establish a primafacie case that the subject matter of claim 21 is directed to an abstract idea of a mental process or a mathematical concept…”
Applicant argues that these steps cannot be practically done by a human mind.
The correct test under the guidance asks if the steps can be conceptually performed using human analysis. It does not look at whether a computer has a practical speed advantage over manual work.
The core steps in Claim 21 represent basic information processing that a human can conceptually do with pen and paper:
Finding features and detecting interaction: A reviewer can watch how users interact with documents. The reviewer can write down which characteristics match each interaction type. This is simple observation and recording.
Predicting document type with ML: The machine learning phrase describes automating conventional pattern recognition. A human analyst can do this same work by looking at old documents, finding feature patterns, and sorting a new document by comparing it to known categories.
Recommending next actions: This is basic decision-making logic. A person can read a document, see its category, look up what actions were taken on similar documents in the past, and recommend the next steps based on those patterns.
Applicant states that the claim presents a technical improvement. However, the text of Claim 21 does not show any real improvement to computer technology. It does not make the processor faster, and it does not save memory space. Because the claim lacks specific technical steps to fix a computer defect, it does not integrate the abstract idea into a practical application.
The claim adds steps like updating an interface, receiving user selections, editing files, and creating new documents. These extra steps are ordinary post-solution activities. They use generic computer hardware to display and save the results of the mental process. Adding standard computer functions around a mental process does not make an abstract idea eligible for a patent.
Applicant argues that a human cannot practically perform these steps because of data volume or speed. Computational complexity or fast execution speeds do not remove a claim from the abstract idea category.
Pg. 11, Applicant argues that “… With regard to Step 2A, Prong 2, it is respectfully submitted that the amended claim 21 recites subject matter that is integrated into a practical application, e.g., an ability to perform real- time predictions, analysis and operations by a machine learning model in connection with processing of electronic documents. This greatly reduces time that is needed to process electronic documents as well as improves accuracy of output resulting from such processes (e.g., more accurate prediction and subsequent execution of actions on a particular electronic document in view of historical actions executed on historical documents). As such, claim 21, when practically applied, effects clear improvements over existing techniques and, thus, goes beyond mere "abstract ideas".
Thus, claim 21 recites patent-eligible subject matter under 35 U.S.C. 101. As such, the Examiner's rejection is respectfully traversed and should be withdrawn.
Claims 22-40 are also directed to patent-eligible subject matter under 35 U.S.C. 101 for at least the reasons stated above with regard to claim 21. Thus, the rejections of claims 22-40 are respectfully traversed and should be withdrawn…”
Applicant argues that Claim 21 is integrated into a practical application because it saves time and improves output accuracy. The Examiner disagrees. A process that merely uses a machine to complete an abstract concept faster or with fewer errors does not create a patent-eligible application.
Applicant notes that the system reduces document processing time and improves output accuracy. However, speed and accuracy are just the desired end-results of using a computer. The actual text of Claim 21 does not write out any specific technical mechanisms. The claim simply automates a mental process to get a faster result, which is not a technological improvement.
Applicant states that the machine learning model makes predictions in real time. This phrase describes a temporal constraint regarding when the steps occur. It does not change what the computer is doing structurally. A human reviewer can also make real-time decisions on-the-fly while reading a document.
The claim adds steps like updating an interface, receiving button clicks, and saving files. These extra steps are routine post-solution and standard activities. Adding completely standard software steps to an abstract idea does not create a practical application.
The claim recites basic hardware like generic processors and memory. The hardware serves merely as a tool to execute the steps faster than a human, rather than being technically improved by the invention.
Under Step 2B, the ordered combination of steps must add an inventive concept that amounts to "significantly more" than the abstract idea. Claim 21 simply combines an ordinary mental sequence (analyzing documents and recommending actions) with a conventional software workflow (displaying results and saving a file). This configuration follows the standard layout of any basic interactive software. It does not provide an unconventional structure or a non-generic solution to a technological problem.
Because the independent claim is ineligible, dependent claims are also patent ineligible under 35 U.S.C. § 101. The rejections are maintained.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure
U.S. Pub 2023/0351091 A1 -Gil discloses a data processing system to perform functions, when executed by the processor. A document is examined to identify an enhancement for a portion of content in the document. The display of a first user interface element is enabled for previewing the identified enhancement as applied to the content. A request is received to select the identified enhancement. The display of a second user interface element is enabled for accepting the identified enhancement upon receiving the request. The first user interface element provides a preview of the document post enhancement.
U.S. Pub 2021/0174006 – Stokes discloses a system and method for facilitating complex document drafting and management is described. A data repository stores a plurality of document elements, each document element including at least a part of a clause for use in a complex document and each individual clause including provisions and terms relating to conditions affecting one or more parties, one or more of the document elements comprising a variable document element which includes variables to be substituted with content when an instance of the document element is used to create a complex document. A database encodes data objects, each data object relating to a document element in the data repository, the database defining a framework, the framework comprising a hierarchy of the data objects. A user interface is used to retrieve variable values and the complex document is compiled by retrieving the document elements from the data repository, populating the variables with the user inputs and combining the document elements according to the hierarchy. The document elements are maintained independently of the complex documents, the document elements being independently updatable and usable across multiple complex documents.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAU HAI HOANG whose telephone number is (571)270-5894. The examiner can normally be reached 1st biwk: Mon-Thurs 7:00 AM-5:00 PM; 2nd biwk: Mon-Thurs: 7:00 am-5:00pm, Fri: 7:00 am - 4:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Boris Gorney can be reached at 571-270-5626. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
HAU HAI. HOANG
Primary Examiner
Art Unit 2154
/HAU H HOANG/ Primary Examiner, Art Unit 2154
Prosecution Insights