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 .
Status of Application
This communication is a Final Office Action in response to the Arguments, Remarks, and Amendments filed on the 11/03/2025. Currently claims 1-18 are pending. No claims are allowed.
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 1-18 are rejected under 35 U.S.C. §101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) with no practical application and without significantly more.
Under MPEP 2106, when considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (step 1). If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea) (step 2A prong 1), and if so, it must additionally be determined whether the claim is integrated into a practical application (step 2A prong 2). If an abstract idea is present in the claim without integration into a practical application, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself (step 2B).
In the instant case, claims 1-18 are directed to a system, method, and non-transitory computer-readable media. Thus, each of the claims falls within one of the four statutory categories (step 1). However, the claims also fall within the judicial exception of an abstract idea (step 2). While claims 1, 9, and 15, are directed to different categories, the language and scope are substantially the same and have been addressed together below.
Under Step 2A Prong 1, the test is to identify whether the claims are “directed to” a judicial exception. Examiner notes that the claimed invention is directed to an abstract idea in that the instant application is directed to certain methods of organizing human activity specifically commercial interactions and behaviors and managing personal behavior and/or interactions between people (see MPEP 2106.04(a)(2)(II)) and mental processes (see MPEP 2106.04(a)(2)(III).
Claim 1: receiving, via a graphical user interface, information from the client; determining a characteristic associated with the information; determining and displaying, via the graphical user interface, a reactive response to the information based on the characteristic associated with the information, wherein the reactive response includes presenting a prompt to the client, and wherein the prompt is a prompt that requests additional information from the [[user]] client specific to the determined characteristic, receiving the additional information from the client in response to the prompt, wherein the additional information comprises a document; verifying that the received information matches a required document type; and presenting, via the graphical user interface, a notification that the additional information is accepted
Claim 9: receiving, via a graphical user interface, information from the client; determining a characteristic associated with the information, wherein the characteristic relates to an ownership interest in a company; [[and]] determining and displaying, via the graphical user interface, a reactive response to the information, based on the characteristic associated with the information, wherein the reactive response includes presenting a prompt to the user, and wherein the prompt is a prompt that requests additional information from the user specific to the determined characteristic receiving the additional information from the client in response to the prompt, wherein the additional information comprises a document; verifying that the received information matches a required document type; and presenting, via the graphical user interface, a notification that the additional information is accepted
Claim 15: A non-transitory computer-readable medium storing instructions to service a client account, executable by a processing resource to: request, via a graphical user interface, information from a user, wherein the information requested includes a particular type of document; receive the document from the client; verify that the received document is the particular type of requested document based on the characteristic associated with the information; and provide, via the graphical user interface, a notification to the user that the document is accepted, based on verification that the received document is the particular type of requested document
Examiner notes that claims 1-18 recite a receiving information, analyzing the request or submitted document, and outputting the result of the determination and verification which is directed to concepts that are performed mentally and a product of human mental work. Because the limitations above closely follow the steps of collecting information, analyzing the information, and displaying the results of the analysis, and the steps involved human judgments, observations and evaluations that can be practically or reasonably performed in the human mind, the claim recites an abstract idea consistent with the “mental process” grouping set forth in the see MPEP 2106.04(a)(2)(III).
Alternatively, Examiner notes that claims 1-18 recite a method and system for receiving client information, entity information, and documents, determining if the business documents have missing parts or errors, and outputting the result of the document and information analysis in order manage client and entity or business information, and is similar to the abstract idea identified in MPEP 2106.04(a)(2)(II) in grouping “II” in that the claims recite certain methods of organizing human activity such as business interactions. This is merely further embellishments of the abstract idea and does not further limit the claimed invention to render the claims patentable subject matter. The limitations, substantially comprising the body of the claim, recite standard processes found in standard practice in ingesting any business specific information related to both a client and/or an entity in order to manage business interactions. Using business or entity or document type to organize, manage, and fix missing information in submitted information with the CRM. Because the limitations above closely follow the steps standard in interactions between people and businesses such as managing documents related to clients, businesses and documents, and the steps of the claims involve organizing human activity, the claim recites an abstract idea consistent with the “organizing human activity” grouping set forth in the see MPEP 2106.04(a)(2)(II).
The conclusion that the claim recites an abstract idea within the groupings of the MPEP 2106.04(a)(2) remains grounded in the broadest reasonable interpretation consistent with the description of the invention in the specification. For example, [App. Spec ¶ 3], “a method receiving information from the client”. Accordingly, the Examiner submits claims 1, 9, and 15, recite an abstract idea based on the language identified in claims 1-18, and the abstract ideas previously identified based on that language that remains consistent with the groupings of Step 2A Prong 1 of the MPEP 2106.04(a)(1).
If the claims are directed toward the judicial exception of an abstract idea, it must then be determined under Step 2A Prong 2 whether the judicial exception is integrated into a practical application. Examiner notes that considerations under Step 2A Prong 2 comprise most the consideration previously evaluated in the context of Step 2B. The Examiner submits that the considerations discussed previously determined that the claim does not recite “significantly more” at Step 2B would be evaluated the same under Step 2A Prong 1 and result in the determination that the claim does not integrate the abstract idea into a practical application.
The instant application fails to integrate the judicial exception into a practical application because the instant application merely recites words “apply it” (or an equivalent) with the judicial exception or merely includes instructions to implement an abstract idea. The instant application is directed to a method instructing the reader to implement the identified method of organizing human activity of business interactions (i.e., managing client information) on generically claimed computer structure. For instance, the additional elements or combination of elements other than the abstract idea itself include the elements such as “graphical user interface” recited at a high level of generality. These elements do not themselves amount to an improvement to the interface or computer, to a technology or another technical field. This is consistent with Applicant’s disclosure which states that the computing device amounts to “The computing device 470 can be a combination of hardware and instructions to share information. The hardware, for example can include a processing resource 472 and/or a memory resource 476 (e.g., computer-readable medium (CRM), database, etc.). A processing resource 472, as used herein, can include a number of processors capable of executing instructions stored by the memory resource 476.Processing resource 472 can be integrated in a single device or distributed across multiple devices. The instructions (e.g., computer- readable instructions (CRI)) can include instructions stored on the memory resource 476 and executable by the processing resource 472 to implement a desired function (e.g., provide a notification, etc.).” (App. Spec. ¶ 87).
Accordingly, the claimed “system” read in light of the specification employs any wide range of possible devices comprising a number of components that are “well-known” and included in an indiscriminate “computer”, and “graphical user interface”, (e.g., processing device, modules). Thus, the claimed structure amounts to appending generic computer elements to abstract idea comprising the body of the claim. The computing elements are only involved at a general, high level, and do not have the particular role within any of the functions but to be a computer-implemented method using a generically claimed “computer”, and “graphical user interface” and even basic, generic recitations that imply use of the computer such as storing information via servers would add little if anything to the abstract idea.
Similarly, reciting the abstract idea as software functions used to program a generic computer is not significant or meaningful: generic computers are programmed with software to perform various functions every day. A programmed generic computer is not a particular machine and by itself does not amount to an inventive concept because, as discussed in MPEP 2106.05(a), adding the words “apply it” (or an equivalent) with the judicial exception, or more instructions to implement an abstract idea on a computer, as discussed in Alice, 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)), is not enough to integrate the exception into a practical application. Further, it is not relevant that a human may perform a task differently from a computer. It is necessarily true that a human might apply an abstract idea in a different manner from a computer. What matters is the application, “stating an abstract idea while adding the words ‘apply it with a computer’” will not render an abstract idea non-abstract. Tranxition v. Lenovo, Nos. 2015-1907, -1941, -1958 (Fed. Cir. Nov. 16, 2016), slip op. at 7-8.
Here, the instructions entirely comprise the abstract idea, leaving little if any aspects of the claim for further consideration under Step 2A Prong 2. In short, the role of the generic computing elements recited in claims 1, 9, and 15, is the same as the role of the computer in the claims considered by the Supreme Court in Alice, and the claim as whole amounts merely to an instruction to apply the abstract idea on the generic computerised system. Therefore, the claims have failed to integrate a practical application (2106.04(d)). Under the MPEP 2106.05, this supports the conclusion that the claim is directed to an abstract idea, and the analysis proceeds to Step 2B.
While many considerations in Step 2A need not be reevaluated in Step 2B because the outcome will be the same. Here, on the basis of the additional elements other than the abstract idea, considered individually and in combination as discussed above, the Examiner respectfully submits that the claims 1, 9, and 15, does not contain any additional elements that individually or as an ordered combination amount to an inventive concept and the claims are ineligible.
With respect to the dependent claims do not recite anything that is found to render the abstract idea as being transformed into a patent eligible invention. The dependent claims are merely reciting further embellishments of the abstract idea and do not claim anything that amounts to significantly more than the abstract idea itself.
Claims 2-8, 10-14, and 16-18 are directed to further embellishments of the abstract idea in that they are directed to aspects of the central theme of the abstract idea identified above, as well as being directed to data processing and transmission which the courts have recognized as insignificant extra-solution activities (see at least M.P.E.P. 2106.05(g)). Data transmission is one of the most basic and fundamental uses there are for a generic computing device is not sufficient to amount to significantly more. The examiner takes the position that simply appending the judicial exception with such a well understood step of data transmission is not going to amount to significantly more than the abstract idea.
Therefore, since there are no limitations in the claim that transform the abstract idea into a patent eligible application such that the claim amounts to significantly more than the abstract idea itself, the claims are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter. See MPEP 2106.
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 (i.e., changing from AIA to pre-AIA ) 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.
The factual inquiries 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.
Claim(s) 1-18 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 20190236347 A1 to Guzman et al. (hereinafter Guzman) in view of U.S. Patent Application Publication No. US 20230061009 A1 to Peng et al. (hereinafter Peng).
Referring to Claim 1, Guzman A method for servicing a client account, comprising:
receiving, via a graphical user interface, information from the client (see at least Guzman: ¶ 29-30 “the document analyzer 120 is configured to retrieve an electronic document, e.g., from the first database 130, and analyze the document, based on information from the data source 150, to determine if any data elements required for a successful VAT refund are missing”; see at least Guzman: ¶ 48 “FIG. 3 is an example flowchart 300 illustrating a method for identification of missing data element within an electronic file according to one embodiment. At S310, the operation starts when an electronic document associated with a transaction made by, for example, an enterprise employee, is received. The electronic document may be collected from a database, e.g., the first database 130 of FIG. 1. The electronic document may be a scanned digital image of an expense record submitted by the enterprise employee that includes therein data elements as further described herein above with respect of FIG. 1. The transaction may be for a purchase of goods and services.”; see also Guzman: ¶ 63 “Obtaining the electronic document may include, but is not limited to, receiving the electronic document (e.g., receiving a scanned image) or retrieving the electronic document (e.g., retrieving the electronic document from an enterprise system, a merchant enterprise system, or a database).”);
Guzman fails to explicitly state that the system is receiving the information from a client via a graphical user interface (further addressed below).
determining a characteristic associated with the information (see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”’); and
determining and displaying, via the graphical user interface, a reactive response to the information based on the characteristic associated with the information, wherein the reactive response includes presenting a prompt to the user, and wherein the prompt is a prompt that requests additional information from the client specific to the determined characteristic (see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”’).
Guzman fails to explicitly state that the system is receiving the information from a client via a graphical user interface (further addressed below).
Examiner notes that Guzman specifically discloses the system automatically generating a “response” to the query that presents the missing information required to complete the document, the document system then automatically generates the required missing information and updates the document. Guzman does not specifically go into detail regarding the user interface, and the system prompting the user to submit further or additional information that is required.
Guzman fails to state:
receiving, via a graphical user interface, information from the client;
determining and displaying, via the graphical user interface
and wherein the prompt is a prompt that requests additional information from the client specific to the determined characteristic
receiving the additional information from the client in response to the prompt, wherein the additional information comprises a document;
verifying that the received information matches a required document type; and
presenting, via the graphical user interface, a notification that the additional information is accepted
However, Peng, which talks about a method and system document analyzing, teaches it is known to provide a user graphical interface to receiving transaction information and document information via the graphical user interface (see Peng: ¶ 28 “The user device 110, in one embodiment, includes a user interface (UI) application 112 (e.g., a web browser, a mobile payment application, etc.), which may be utilized by the user 140 to interact with the merchant server 120 and/or the service provider server 130 over the network 160.”), prompting the user via a request to the client for the client to submit additional information comprising a document (see Peng: ¶ 30 “The image analysis module 118 may present a notification on the user device 110 indicating that the document captured by the user 140 does not satisfy the set of requirements and prompting the user to re-capture the document.”; see also Peng: ¶ 41 and 45-46 “the image analysis module 200 may present an alert on the user device 110, and may prompt the user 140 to capture another document that would satisfy the set of requirements or re-capture the same document using a different background, etc.”), and verifying that the received information matches the requirement document type (see Peng: ¶ 45-46).
Furthermore, the combination of Guzman and Peng teaches presenting, via the graphical user interface, a notification that the additional information is accepted (see at least Guzman: ¶ 52 “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Peng: ¶ 45-46 “the image analysis module 200 may transmit the image from the user device 110 to the service provider server 130 via the user interface application 112 if it is determined that the document satisfies the set of requirements.”: discussing the graphical user interface presenting the information to the user).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements (as disclosed by Peng) to the known method and system for document analysis to identify missing parts or data sets within the document based on stored requirements wherein the system automatically modifies the document based on the missing data and stored information (as disclosed by Guzman) to determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.). One of ordinary skill in the art would have been motivated to apply the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements because it would determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.) (see Peng ¶ 3).
Furthermore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements (as disclosed by Peng) to the known method and system for document analysis to identify missing parts or data sets within the document based on stored requirements wherein the system automatically modifies the document based on the missing data and stored information (as disclosed by Guzman) to determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.), because the claimed invention is merely applying a known technique to a known method ready for improvement to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). In other words, all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art at the time of the invention (i.e., predictable results are obtained by applying the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements to the known method and system for document analysis to identify missing parts or data sets within the document based on stored requirements wherein the system automatically modifies the document based on the missing data and stored information to determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.)). See also MPEP § 2143(I)(D).
Referring to Claim 2, the combination of Guzman and Peng teaches the method of claim 1, further comprising receiving a document from the client, wherein the document from the client is received in response to the prompt presented to the user (see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”’).
Referring to Claim 3, the combination of Guzman and Peng teaches the method of claim 2, further comprising making a determination with respect to the document provided from the client (see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”’).
Referring to Claim 4, the combination of Guzman and Peng teaches the method of claim 3, wherein the determination with respect to the document includes authenticating the document based on a type of document associated with the prompt presented to the user (see at least Guzman: ¶ 38 “configured to validate the first electronic document based on templates.”; see also Guzman: ¶ 60 “It may be determined that if the document type is identified the options for completing the supplier's name, i.e. the missing data element, are ten options.”).
Referring to Claim 5, the combination of Guzman and Peng teaches the method of claim 3, wherein the determination with respect to the document includes determining a validity of information included in the document (see at least Guzman: ¶ 38 “configured to validate the first electronic document based on templates.”; see also Guzman: ¶ 60 “It may be determined that if the document type is identified the options for completing the supplier's name, i.e. the missing data element, are ten options.”).
Referring to Claim 6, the combination of Guzman and Peng teaches the method of claim 5, wherein the validity of information included in the document is determined through accessing a third party database (see at least Guzman: ¶ 38 “configured to validate the first electronic document based on templates.”; see also Guzman: ¶ 60 “It may be determined that if the document type is identified the options for completing the supplier's name, i.e. the missing data element, are ten options.”; see also Guzman: ¶ 66 “An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof.”).
Referring to Claim 7, the combination of Guzman and Peng teaches the method of claim 3, wherein making the determination includes: making a determination that a problem exists with the document provided, and providing a list of corrective actions to a representative in response to a determination that the problem exists with the document provided (see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”’).
Referring to Claim 8, the combination of Guzman and Peng teaches the method of claim 3, wherein the method further includes: extracting information from the document, and entering the extracted information into an additional step associated with the servicing of the client account (see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”’).
Referring to Claim 9, the combination of Guzman and Peng teaches a method for servicing a client account, comprising:
receiving, via a graphical user interface, information from the client (see at least Guzman: ¶ 29-30 “the document analyzer 120 is configured to retrieve an electronic document, e.g., from the first database 130, and analyze the document, based on information from the data source 150, to determine if any data elements required for a successful VAT refund are missing”; see at least Guzman: ¶ 48 “FIG. 3 is an example flowchart 300 illustrating a method for identification of missing data element within an electronic file according to one embodiment. At S310, the operation starts when an electronic document associated with a transaction made by, for example, an enterprise employee, is received. The electronic document may be collected from a database, e.g., the first database 130 of FIG. 1. The electronic document may be a scanned digital image of an expense record submitted by the enterprise employee that includes therein data elements as further described herein above with respect of FIG. 1. The transaction may be for a purchase of goods and services.”; see also Guzman: ¶ 63 “Obtaining the electronic document may include, but is not limited to, receiving the electronic document (e.g., receiving a scanned image) or retrieving the electronic document (e.g., retrieving the electronic document from an enterprise system, a merchant enterprise system, or a database).”);
Guzman fails to explicitly state that the system is receiving the information from a client via a graphical user interface (further addressed below).
determining a characteristic associated with the information, wherein the characteristic relates to an ownership interest in a company (see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”’); and
determining and displaying, via the graphical user interface, a reactive response to the information, based on the characteristic associated with the information wherein the reactive response includes presenting a prompt to the user, and wherein the prompt is a prompt that requests additional information from the user specific to the determined characteristic (see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”’).
Guzman fails to explicitly state that the system is receiving the information from a client via a graphical user interface (further addressed below).
Examiner notes that Guzman specifically discloses the system automatically generating a “response” to the query that presents the missing information required to complete the document, the document system then automatically generates the required missing information and updates the document. Guzman does not specifically go into detail regarding the user interface, and the system prompting the user to submit further or additional information that is required.
Guzman fails to state:
receiving, via a graphical user interface, information from the client;
determining and displaying, via the graphical user interface
and wherein the prompt is a prompt that requests additional information from the client specific to the determined characteristic
receiving the additional information from the client in response to the prompt, wherein the additional information comprises a document;
verifying that the received information matches a required document type; and
presenting, via the graphical user interface, a notification that the additional information is accepted
However, Peng, which talks about a method and system document analyzing, teaches it is known to provide a user graphical interface to receiving transaction information and document information via the graphical user interface (see Peng: ¶ 28 “The user device 110, in one embodiment, includes a user interface (UI) application 112 (e.g., a web browser, a mobile payment application, etc.), which may be utilized by the user 140 to interact with the merchant server 120 and/or the service provider server 130 over the network 160.”), prompting the user via a request to the client for the client to submit additional information comprising a document (see Peng: ¶ 30 “The image analysis module 118 may present a notification on the user device 110 indicating that the document captured by the user 140 does not satisfy the set of requirements and prompting the user to re-capture the document.”; see also Peng: ¶ 41 and 45-46 “the image analysis module 200 may present an alert on the user device 110, and may prompt the user 140 to capture another document that would satisfy the set of requirements or re-capture the same document using a different background, etc.”), and verifying that the received information matches the requirement document type (see Peng: ¶ 45-46).
Furthermore, the combination of Guzman and Peng teaches presenting, via the graphical user interface, a notification that the additional information is accepted (see at least Guzman: ¶ 52 “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Peng: ¶ 45-46 “the image analysis module 200 may transmit the image from the user device 110 to the service provider server 130 via the user interface application 112 if it is determined that the document satisfies the set of requirements.”: discussing the graphical user interface presenting the information to the user).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements (as disclosed by Peng) to the known method and system for document analysis to identify missing parts or data sets within the document based on stored requirements wherein the system automatically modifies the document based on the missing data and stored information (as disclosed by Guzman) to determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.). One of ordinary skill in the art would have been motivated to apply the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements because it would determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.) (see Peng ¶ 3).
Furthermore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements (as disclosed by Peng) to the known method and system for document analysis to identify missing parts or data sets within the document based on stored requirements wherein the system automatically modifies the document based on the missing data and stored information (as disclosed by Guzman) to determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.), because the claimed invention is merely applying a known technique to a known method ready for improvement to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). In other words, all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art at the time of the invention (i.e., predictable results are obtained by applying the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements to the known method and system for document analysis to identify missing parts or data sets within the document based on stored requirements wherein the system automatically modifies the document based on the missing data and stored information to determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.)). See also MPEP § 2143(I)(D).
Referring to Claim 10, the combination of Guzman and Peng teaches the method of claim 9, wherein the additional information includes information related to a type of the company (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”).
Referring to Claim 11, the combination of Guzman and Peng teaches the method of claim 9, wherein the additional information relates to a percentage ownership interest for a number of parties holding an ownership interest in the company (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”).
Referring to Claim 12, the combination of Guzman and Peng teaches the method of claim 11, further comprising verifying that the percentage ownership interests equals a particular amount (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”).
Referring to Claim 13, the combination of Guzman and Peng teaches the method of claim 9, wherein the additional information relates to whether the company or an owner of the company is a publicly traded company (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”).
Referring to Claim 14, the combination of Guzman and Peng teaches the method of claim 13, further comprising presenting the client with a request for documentation specific to the company or the owner of the company (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”).
Referring to Claim 15, the combination of Guzman and Peng teaches non-transitory computer-readable medium storing instructions to service a client account, executable by a processing resource to:
request, via a graphical user interface, information from a user, wherein the information requested includes a particular type of document (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”);
receive the document from the client (see at least Guzman: ¶ 29-30 “the document analyzer 120 is configured to retrieve an electronic document, e.g., from the first database 130, and analyze the document, based on information from the data source 150, to determine if any data elements required for a successful VAT refund are missing”; see at least Guzman: ¶ 48 “FIG. 3 is an example flowchart 300 illustrating a method for identification of missing data element within an electronic file according to one embodiment. At S310, the operation starts when an electronic document associated with a transaction made by, for example, an enterprise employee, is received. The electronic document may be collected from a database, e.g., the first database 130 of FIG. 1. The electronic document may be a scanned digital image of an expense record submitted by the enterprise employee that includes therein data elements as further described herein above with respect of FIG. 1. The transaction may be for a purchase of goods and services.”; see also Guzman: ¶ 63 “Obtaining the electronic document may include, but is not limited to, receiving the electronic document (e.g., receiving a scanned image) or retrieving the electronic document (e.g., retrieving the electronic document from an enterprise system, a merchant enterprise system, or a database).”); Guzman fails to explicitly state that the system is receiving the information from a client via a graphical user interface (further addressed below).
verify that the received document is the particular type of requested document based on the characteristic associated with the information (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”); and
provide, via the graphical user interface, a notification to the user that the document is accepted, based on verification that the received document is the particular type of requested document (see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”’).
Guzman fails to explicitly state that the system is receiving the information from a client via a graphical user interface (further addressed below).
Examiner notes that Guzman specifically discloses the system automatically generating a “response” to the query that presents the missing information required to complete the document, the document system then automatically generates the required missing information and updates the document. Guzman does not specifically go into detail regarding the user interface, and the system prompting the user to submit further or additional information that is required.
Guzman fails to state:
receiving, via a graphical user interface, information from the client;
providing, via the graphical user interface, a notification that the additional information is accepted
However, Peng, which talks about a method and system document analyzing, teaches it is known to provide a user graphical interface to receiving transaction information and document information via the graphical user interface (see Peng: ¶ 28 “The user device 110, in one embodiment, includes a user interface (UI) application 112 (e.g., a web browser, a mobile payment application, etc.), which may be utilized by the user 140 to interact with the merchant server 120 and/or the service provider server 130 over the network 160.”), prompting the user via a request to the client for the client to submit additional information comprising a document (see Peng: ¶ 30 “The image analysis module 118 may present a notification on the user device 110 indicating that the document captured by the user 140 does not satisfy the set of requirements and prompting the user to re-capture the document.”; see also Peng: ¶ 41 and 45-46 “the image analysis module 200 may present an alert on the user device 110, and may prompt the user 140 to capture another document that would satisfy the set of requirements or re-capture the same document using a different background, etc.”), and verifying that the received information matches the requirement document type (see Peng: ¶ 45-46).
Furthermore, the combination of Guzman and Peng teaches presenting, via the graphical user interface, a notification that the additional information is accepted (see at least Guzman: ¶ 52 “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Peng: ¶ 45-46 “the image analysis module 200 may transmit the image from the user device 110 to the service provider server 130 via the user interface application 112 if it is determined that the document satisfies the set of requirements.”: discussing the graphical user interface presenting the information to the user).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements (as disclosed by Peng) to the known method and system for document analysis to identify missing parts or data sets within the document based on stored requirements wherein the system automatically modifies the document based on the missing data and stored information (as disclosed by Guzman) to determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.). One of ordinary skill in the art would have been motivated to apply the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements because it would determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.) (see Peng ¶ 3).
Furthermore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements (as disclosed by Peng) to the known method and system for document analysis to identify missing parts or data sets within the document based on stored requirements wherein the system automatically modifies the document based on the missing data and stored information (as disclosed by Guzman) to determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.), because the claimed invention is merely applying a known technique to a known method ready for improvement to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). In other words, all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art at the time of the invention (i.e., predictable results are obtained by applying the known technique of prompting a client, via a graphical user interface, to input additional documents and information when the information does not match set requirements to the known method and system for document analysis to identify missing parts or data sets within the document based on stored requirements wherein the system automatically modifies the document based on the missing data and stored information to determine whether the submitted document satisfies a set of requirements (e.g., whether the submitted document corresponds to the required document type, whether the submitted document has missing information, etc.)). See also MPEP § 2143(I)(D).
Referring to Claim 16, the combination of Guzman and Peng teaches the non-transitory computer-readable medium of claim 15, further comprising instructions executable to verify the contents of the document, through accessing an external database (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”; see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”).
Referring to Claim 17, the combination of Guzman and Peng teaches the non-transitory computer-readable medium of claim 16, further comprising instructions executable to verify that the document is valid based on the contents of the document matching information included in the external database (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”; see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”).
Referring to Claim 18, the combination of Guzman and Peng teaches the non-transitory computer-readable medium of claim 16, further comprising instructions to determine that the document is unexpired by accessing information included in the external database (see at least Guzman: ¶ 23-24: “The first database 130 may be associated with an enterprise and is configured to store data related to transactions and purchases made by the enterprise or by representatives of the enterprise, as well as data related to the enterprise itself.”; see also Guzman: ¶ 48, 53, 63, and 69 “In an embodiment, creating the template includes analyzing the structured dataset to identify transaction parameters such as, but not limited to, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction (e.g., a date, a time, a price, a type of good or service sold, etc.), or both. In a further embodiment, analyzing the structured dataset may also include identifying the transaction based on the structured dataset.”; see at least Guzman: ¶ 29-30, 32-35, 38, 40, and 46: document analyzer using machine learning and artificial neural networks to identify documents that are lacking specific and required information; see at least Guzman: ¶ 49-52: “the electronic document is modified based on the identification of the missing one or more data elements. In an embodiment, the document is modified to include only the missing data elements.”; see also Guzman: ¶ 55 “the comparison allows for identifying errors in the original electronic document, such as wrong dates, amounts, etc. that were mistakenly entered by an employee”; see at least Guzman: ¶ 58-60: “it is determined which one of the missing data elements represents a minimum requirement for completing an eligible electronic document for VAT purposes. For example, the supplier's name, the document type and the transaction amount are missing from an electronic document.”; see also Guzman: ¶ 66 “if the merchant name can be identified but its address is missing, then the key field for the merchant address is incomplete. An attempt to complete the missing key field values is performed. This attempt may include querying external systems and databases, correlation with previously analyzed invoices, or a combination thereof”).
Response to Arguments
Applicant's arguments filed with respect to the rejection of the claims under 35 USC 101 have been fully considered but they are not persuasive.
Applicant argues that the claims “integrates a recited judicial exception into a practical application by reciting a specific document verification system that addresses technical problems in electronic document process” and “providing concrete improvements to document verification technology, including interactive client-facing prompts through a graphical user interface, dynamic receipt of supplemental client-submitted documents, automated document-type verification, and real-time acceptance notifications, thereby enhancing accuracy, security, and efficiency of electronic document verification”. Examiner respectfully disagrees.
Examiner notes that the system is merely implementing the abstract idea on a generically stated graphical user interface to output information to the user. Nothing is presented as to what amounts to improvements of graphical user interfaces.
Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer").
In evaluating whether a claim that requires a computer recites a mental process, examiners should carefully consider the broadest reasonable interpretation of the claim in light of the specification. For instance, examiners should review the specification to determine if the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept. In these situations, the claim is considered to recite a mental process.
An example of a case identifying a mental process performed on a generic computer as an abstract idea is Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 1385, 126 USPQ2d 1498, 1504 (Fed. Cir. 2018). In this case, the Federal Circuit relied upon the specification in explaining that the claimed steps of voting, verifying the vote, and submitting the vote for tabulation are "human cognitive actions" that humans have performed for hundreds of years. The claims therefore recited an abstract idea, despite the fact that the claimed voting steps were performed on a computer. 887 F.3d at 1385, 126 USPQ2d at 1504. Another example is FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 120 USPQ2d 1293 (Fed. Cir. 2016). The patentee in FairWarning claimed a system and method of detecting fraud and/or misuse in a computer environment, in which information regarding accesses of a patient’s personal health information was analyzed according to one of several rules (i.e., related to accesses in excess of a specific volume, accesses during a pre-determined time interval, or accesses by a specific user) to determine if the activity indicates improper access. 839 F.3d. at 1092, 120 USPQ2d at 1294. The court determined that these claims were directed to a mental process of detecting misuse, and that the claimed rules here were "the same questions (though perhaps phrased with different words) that humans in analogous situations detecting fraud have asked for decades, if not centuries." 839 F.3d. at 1094-95, 120 USPQ2d at 1296.
An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699. The patentee in Mortgage Grader claimed a computer-implemented system for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The interface prompts a borrower to enter personal information, which the grading module uses to calculate the borrower’s credit grading, and allows the borrower to identify and compare loan packages in the database using the credit grading. 811 F.3d. at 1318, 117 USPQ2d at 1695. The Federal Circuit determined that these claims were directed to the concept of "anonymous loan shopping", which was a concept that could be "performed by humans without a computer." 811 F.3d. at 1324, 117 USPQ2d at 1699. Another example is Berkheimer v. HP, Inc., 881 F.3d 1360, 125 USPQ2d 1649 (Fed. Cir. 2018), in which the patentee claimed methods for parsing and evaluating data using a computer processing system. The Federal Circuit determined that these claims were directed to mental processes of parsing and comparing data, because the steps were recited at a high level of generality and merely used computers as a tool to perform the processes. 881 F.3d at 1366, 125 USPQ2d at 1652-53.
Both product claims (e.g., computer system, computer-readable medium, etc.) and process claims may recite mental processes. For example, in Mortgage Grader, the patentee claimed a computer-implemented system and a method for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The Federal Circuit determined that both the computer-implemented system and method claims were directed to "anonymous loan shopping", which was an abstract idea because it could be "performed by humans without a computer." 811 F.3d. at 1318, 1324-25, 117 USPQ2d at 1695, 1699-1700. See also FairWarning IP, 839 F.3d at 1092, 120 USPQ2d at 1294 (identifying both system and process claims for detecting improper access of a patient's protected health information in a health-care system computer environment as directed to abstract idea of detecting fraud); Content Extraction & Transmission LLC v. Wells Fargo Bank, N.A., 776 F.3d 1343, 1345, 113 USPQ2d 1354, 1356 (Fed. Cir. 2014) (system and method claims of inputting information from a hard copy document into a computer program). Accordingly, the phrase "mental processes" should be understood as referring to the type of abstract idea, and not to the statutory category of the claim.
Examples of product claims reciting mental processes include: An application program interface for extracting and processing information from a diversity of types of hard copy documents – Content Extraction, 776 F.3d at 1345, 113 USPQ2d at 1356; and A computer readable medium containing program instructions for detecting fraud – CyberSource, 654 F.3d at 1368 n. 1, 99 USPQ2d at 1692 n.1.
Examiner notes that the claimed in invention is similar to the Voter Verified, Inc., FairWarning, Mortgage Grader, Berkheimer, Content Extraction and CyberSource applications wherein the court identified computer system or “graphical user interface” is merely serving as a the generic computer, computing environment, or tool to perform the mental process.
The second part of the Alice/Mayo test is often referred to as a search for an inventive concept. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 217, 110 USPQ2d 1976, 1981 (2014) (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 71-72, 101 USPQ2d 1961, 1966 (2012)).
Evaluating additional elements to determine whether they amount to an inventive concept requires considering them both individually and in combination to ensure that they amount to significantly more than the judicial exception itself. Because this approach considers all claim elements, the Supreme Court has noted that "it is consistent with the general rule that patent claims ‘must be considered as a whole.’" Alice Corp., 573 U.S. at 218 n.3, 110 USPQ2d at 1981 (quoting Diamond v. Diehr, 450 U.S. 175, 188, 209 USPQ 1, 8-9 (1981)). Consideration of the elements in combination is particularly important, because even if an additional element does not amount to significantly more on its own, it can still amount to significantly more when considered in combination with the other elements of the claim. See, e.g., Rapid Litig. Mgmt. v. CellzDirect, 827 F.3d 1042, 1051, 119 USPQ2d 1370, 1375 (Fed. Cir. 2016) (process reciting combination of individually well-known freezing and thawing steps was "far from routine and conventional" and thus eligible); BASCOM Global Internet Servs. v. AT&T Mobility LLC, 827 F.3d 1341, 1350, 119 USPQ2d 1236, 1242 (Fed. Cir. 2016) (inventive concept may be found in the non-conventional and non-generic arrangement of components that are individually well-known and conventional).
Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)); and Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook, 437 U.S. 584, 588-90, 198 USPQ 193, 197-98 (1978) (MPEP § 2106.05(h)).
It is important to note that in order for a method claim to improve computer functionality, the broadest reasonable interpretation of the claim must be limited to computer implementation. That is, a claim whose entire scope can be performed mentally, cannot be said to improve computer technology. Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 120 USPQ2d 1473 (Fed. Cir. 2016) (a method of translating a logic circuit into a hardware component description of a logic circuit was found to be ineligible because the method did not employ a computer and a skilled artisan could perform all the steps mentally). Similarly, a claimed process covering embodiments that can be performed on a computer, as well as embodiments that can be practiced verbally or with a telephone, cannot improve computer technology. See RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1328, 122 USPQ2d 1377, 1381 (Fed. Cir. 2017) (process for encoding/decoding facial data using image codes assigned to particular facial features held ineligible because the process did not require a computer).
Examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality: ii. Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016), iii. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential); vii. Providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because "an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality," BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1287-88, 127 USPQ2d 1688, 1693-94 (Fed. Cir. 2018).
To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology. See MPEP § 2106.05(f) for more information about mere instructions to apply an exception.
Examples that the courts have indicated may not be sufficient to show an improvement to technology include: i. A commonplace business method being applied on a general purpose computer, Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Examiner notes that the claimed invention shares similar insufficient computing elements as Alice Corp. and Versata Dev. Group, Inc., in that the claimed invention is merely adding generic computer components to perform the method.
The claims stand rejected.
102 Rejections
Applicant’s arguments with respect to claim(s) 1-18 under 35 USC 102 have been considered but the rejection has been updated to reflect the submitted amendments that required further search and consideration. The claims stand rejected.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/Michael Young/Examiner, Art Unit 3626