DETAILED ACTION
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is a FINAL office action in response to the Applicant’s response filed 22 May 2026.
Claim 1 has been amended.
Claims 1-10 are currently pending and have been examined.
Response to Arguments
Applicant's arguments filed 22 May 2026 with respect to the 101 rejection have been fully considered but they are not persuasive.
With respect to the claims, the Applicant argues on page 5 of their response, “The Office Action characterizes the claims as being directed to organizing human activity involving review generation or review management. Respectfully, this characterization oversimplifies the claims and fails to consider the claims as a whole, as required by Enfish, LLC V. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016). When properly characterized, the claims are directed to a specific computer-implemented architecture for automated review generation, confirmation processing, and lifecycle management using distributed server-side processing.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. With respect to claim 1, the Examiner notes that paragraph 7 of the previous Non-Final Rejection stated:
“The limitations of sending an information query to a party, wherein the information query comprises a request for data related to at least one entity, at least one review, or a combination thereof, wherein the party receives the information query and aggregates the data related to the at least one entity, the at least one review, or a combination thereof based on the information query, and wherein the party provides the at least one review related to the at least one entity in the information query; as drafted, under the broadest reasonable interpretation, encompass the management of commercial activity (marketing, business relations), and steps that can be performed in the human mind. That is, other than reciting the use of generic computer elements (information server, central server, communication network, user device), the claims recite an abstract idea. In particular, the claims recite sending an information query to a party requesting information related to an entity and/or review, the party receiving the request and aggregating the information, and the party providing the information; which encompasses managing marketing (business information and reviews), and managing the business relations between the party and the businesses. As such, the claims recite elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. In addition, the claims further recite sending an information query to a party, said party receiving the query and aggregating a response, and said party providing the response; which encompass elements that can be performed in the human mind (observation, evaluation, judgement). As such, the claims recite elements that fall into the “Mental Processes” grouping of abstract ideas. The claims recite an abstract idea.” (Emphasis added).
As shown and emphasized here, the Examiner identified the specific elements of the claims that recited an abstract idea, explained why the elements recite an abstract idea, provided the abstract groupings for which the limitations fall under, and identified the additional elements in the claim. That is, the Examiner did not oversimplify the claim and did not fail to consider the claim as a whole, but instead conducted an analysis in accordance with MPEP 2106.04(II)(A)(1) which states, “Prong One asks does the claim recite an abstract idea, law of nature, or natural phenomenon? In Prong One examiners evaluate whether the claim recites a judicial exception, i.e. whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. While the terms "set forth" and "described" are thus both equated with "recite", their different language is intended to indicate that there are two ways in which an exception can be recited in a claim. For instance, the claims in Diehr, 450 U.S. at 178 n. 2, 179 n.5, 191-92, 209 USPQ at 4-5 (1981), clearly stated a mathematical equation in the repetitively calculating step, and the claims in Mayo, 566 U.S. 66, 75-77, 101 USPQ2d 1961, 1967-68 (2012), clearly stated laws of nature in the wherein clause, such that the claims "set forth" an identifiable judicial exception. Alternatively, the claims in Alice Corp., 573 U.S. at 218, 110 USPQ2d at 1982, described the concept of intermediated settlement without ever explicitly using the words "intermediated" or "settlement."” (Emphasis added). As shown and emphasized here, the Examiner is to analyze the claim and determine whether it recites (sets forth or describes) an abstract idea. In this case, the Examiner specifically showed such a recitation in the claims, and the Applicant’s argument of oversimplification is divorced from the actual rejection itself. As such, the Applicant’s argument is not considered persuasive, as it does not address the specific language of the rejection. Further, it is noted that claims 5 and 10 have similarly been analyzed in paragraph 12 of the previous Non-Final Rejection, and for similar reasons as discussed above, the Applicant’s argument is not considered persuasive, as it does not address the specific language of the rejection. Therefore, the Examiner maintains that this rejection is proper.
The Applicant continues on page 5 of their response:
“Independent claim 1 recites: an information server, a central server communicatively coupled to the information server, at least one user device, network-based query processing, aggregation of entity and review-related data, and generation of a "presumed review" computed by the central server.
Independent claims 5 and 10 further recite: automated initiation of a review process, presuming a review based on historical data, sending confirmation requests, initiating counters based on time and/or attempts, and dynamically updating reviews based on user responses or counter expiration events.
These limitations collectively define a specific technological workflow for automated review computation and review-state management within a networked computer system.
The claims, therefore, are not directed merely to the abstract concept of "reviewing," "rating," or "organizing opinions." Rather, they recite a concrete technological implementation that performs machine-driven review generation and automated review lifecycle handling.
Additionally, the claimed operations cannot practically be performed in the human mind.
The claims require: communication between distributed system components, aggregation of data through networked servers, server-side computation of presumed reviews, automated confirmation-request generation, counter-based event tracking, and automated review updating based on asynchronous events.”
The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. First, with respect to the Applicant’s argument that, “These limitations collectively define a specific technological workflow for automated review computation and review-state management within a networked computer system,” the Examiner is not persuaded. In particular, while the Applicant asserts that the limitations define a workflow for automated review computation and review-state management within a networked computer system, this is not a reason as to why these specific limitations would recite an abstract idea in accordance with MPEP 2106.04. In this case, the Applicant has failed to rebut the rejection which stated, “In particular, the claims recite sending an information query to a party requesting information related to an entity and/or review, the party receiving the request and aggregating the information, and the party providing the information; which encompasses managing marketing (business information and reviews), and managing the business relations between the party and the businesses. As such, the claims recite elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. In addition, the claims further recite sending an information query to a party, said party receiving the query and aggregating a response, and said party providing the response; which encompass elements that can be performed in the human mind (observation, evaluation, judgement). As such, the claims recite elements that fall into the “Mental Processes” grouping of abstract ideas,” (with respect to claim 1), and “In particular, the claims recite receiving a request for a review process initiation from a user, presuming a review for the user based on historical information, providing the presumed review to the user along with a time limit to confirm or reject the review, and updating the review based on the user confirmation; which encompasses the writing a review for a user upon request, and receiving their approval/disapproval in a time period; which is the management of commercial activity (reviews/marketing, business relations between the user and a business). As such, the claims recite elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. In addition, the claims further recite receiving a request for a review process initiation from a user, presuming a review for the user based on historical information, providing the presumed review to the user along with a time limit to confirm or reject the review, and updating the review based on the user confirmation; which encompass elements that can be performed in the human mind (observation, evaluation, judgement). As such, the claims recite elements that fall into the “Mental Processes” grouping of abstract ideas,” (with respect to claims 5 and 10). As shown here, the Examiner specifically identified and explained why the argued claim elements do recite an abstract idea, which the Applicant has not addressed. Further, it is noted that the claims do not reference any “review-state management” and thus the Applicant’s argument is not reflective of the claimed invention. Thus, the Applicant’s argument is deemed not persuasive. Second, with respect to the Applicant’s argument, “The claims, therefore, are not directed merely to the abstract concept of "reviewing," "rating," or "organizing opinions." Rather, they recite a concrete technological implementation that performs machine-driven review generation and automated review lifecycle handling,” the Examiner is not persuaded. In this case, it is noted that the Applicant has failed to actually identify any elements of the claim, and instead merely referred to a general concepts that they view the claims encompass, which is not persuasive. For example, it is it noted that the previous rejection stated with respect to claim 1, in paragraph 7 of the Non-Final Rejection, “The limitations of sending an information query to a party, wherein the information query comprises a request for data related to at least one entity, at least one review, or a combination thereof, wherein the party receives the information query and aggregates the data related to the at least one entity, the at least one review, or a combination thereof based on the information query, and wherein the party provides the at least one review related to the at least one entity in the information query; as drafted, under the broadest reasonable interpretation, encompass the management of commercial activity (marketing, business relations), and steps that can be performed in the human mind. That is, other than reciting the use of generic computer elements (information server, central server, communication network, user device), the claims recite an abstract idea. In particular, the claims recite sending an information query to a party requesting information related to an entity and/or review, the party receiving the request and aggregating the information, and the party providing the information; which encompasses managing marketing (business information and reviews), and managing the business relations between the party and the businesses. As such, the claims recite elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. In addition, the claims further recite sending an information query to a party, said party receiving the query and aggregating a response, and said party providing the response; which encompass elements that can be performed in the human mind (observation, evaluation, judgement). As such, the claims recite elements that fall into the “Mental Processes” grouping of abstract ideas.” (Emphasis added). As shown and emphasized here, the rejection specifically identified the claim elements recited in the claim, and specifically explained why these elements recite an abstract idea in accordance with MPEP 2106.04; which the Applicant has failed to rebut or directly refute. Further, as shown above, the Examiner has shown that review generation is an abstract idea. It is additionally noted, that the Applicant has failed to claim any “automated review lifecycle handling,” and thus, the Applicant’s argument is deemed not reflective of the claimed invention. Third, with respect to the Applicant’s argument that, “Additionally, the claimed operations cannot practically be performed in the human mind;” and “The claims require: communication between distributed system components, aggregation of data through networked servers, server-side computation of presumed reviews, automated confirmation-request generation, counter-based event tracking, and automated review updating based on asynchronous events,” the Examiner is not persuaded that this is sufficient to prevent the claims from reciting an abstract idea. It is noted that MPEP 2106.04(a)(2)(III)(c) states, “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").” (Emphasis added). As shown and emphasized here, the claims can still recite a mental process even if they are claimed as being performed on a computer. With respect to the Applicant’s claims, it is noted that the claimed elements can be performed in the human mind, even though they are recited as being performed on a computer, as noted in the previous rejection, which the Applicant has failed to explain why it is deficient. Further, with respect to the Applicant’s argument, “aggregation of data through networked servers, server-side computation of presumed reviews, automated confirmation-request generation, counter-based event tracking, and automated review updating based on asynchronous events,” it is noted that the Applicant has failed to specifically identify the claim elements that these general elements refer to, as these are not claim limitations in claims 1, 5, or 10. Thus, the Examiner maintains that this rejection is proper.
The Applicant continues on page 6 of their response, “In CardioNet, LLC v. InfoBionic, Inc., 955 F.3d 1358 (Fed. Cir. 2020), the Federal Circuit explained that claims directed to specific computerized data-processing operations were not mental processes merely because humans could conceptually analyze information. Similarly, here, while humans may conceptually "form opinions," the claimed invention recites a machine-implemented architecture performing automated review generation, event management, and dynamic updating operations that cannot practically be performed mentally.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. First, it is noted, with respect to the Applicant’s argument that, “the claimed invention recites a machine-implemented architecture performing automated review generation, event management, and dynamic updating operations that cannot practically be performed mentally,” the Examiner is not persuaded. In this case, it is noted that the claims do not recite any elements regarding event management or updating operations, and thus the Applicant’s assertions are for elements beyond the scope of the claims, and thus not reflective of the claimed invention. Second, with respect to the assertion that these elements cannot practically be performed mentally, the Examiner is not persuaded. In this case, the Applicant has failed to provide any explanation as to why the claimed elements identified in the previous and current rejection, be performed in the human mind, as defined in MPEP 2106.05(a)(2)(III). Notably, while the Applicant has stated that the claims reference a machine-implemented architecture performing the functions, it is noted that merely invoking the use of a generic computer as a tool to carry out the abstract idea, does not prevent the claim from reciting a mental process, as discussed above. Third, with respect to the Applicant’s argument regarding specific computerized data-processing operations as not mental processes, the Examiner notes that the Applicant has failed to identify any specific computerized data-processing operations that are recited in the claims. In this case, it is noted that MPEP 2106.04(a)(2)(III)(A) states, “Claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations. See SRI Int’l, Inc. v. Cisco Systems, Inc., 930 F.3d 1295, 1304 (Fed. Cir. 2019) (declining to identify the claimed collection and analysis of network data as abstract because "the human mind is not equipped to detect suspicious activity by using network monitors and analyzing network packets as recited by the claims"); CyberSource, 654 F.3d at 1376, 99 USPQ2d at 1699 (distinguishing Research Corp. Techs. v. Microsoft Corp., 627 F.3d 859, 97 USPQ2d 1274 (Fed. Cir. 2010), and SiRF Tech., Inc. v. Int’l Trade Comm’n, 601 F.3d 1319, 94 USPQ2d 1607 (Fed. Cir. 2010), as directed to inventions that ‘‘could not, as a practical matter, be performed entirely in a human’s mind’’).” With respect to the Applicant’s claims, it is noted that the Applicant has failed to explain why, with respect to claim 1 “at least one user device sends an information query to the information server, the central server, or both through a communication network; wherein the information query comprises a request for data related to at least one entity, at least one review, or a combination thereof… receives the information query and aggregates the data related to the at least one entity, the at least one review, or a combination thereof based on the information query; wherein the central server provides the at least one review related to the at least one entity in the information query; wherein the at least one review is a presumed review…;” and with respect to claim 5 (and similarly claim 10), “receiving a request for a review process initiation for at least one user interaction; presuming a review for at least one entity for the at least one user interaction based on historical data; sending a confirmation request with the review to the at least one user; initiating a counter against the confirmation request, wherein the counter is based on time, attempts, or a combination thereof; updating the review based on a response of the user to the confirmation request or counter expiration,” are elements that cannot be performed by the human mind. Notably, as the previous and current rejections state, and as discussed above with respect to MPEP 2106.04(a)(2)(III), merely reciting the use of generic computer elements as tools to carry out the recited elements, and performing a mental process in a computer environment, are insufficient from preventing a claim from reciting a “mental process.” Therefore, the Examiner maintains that this rejection is proper.
The Applicant continues on page 6 of their response, “Likewise, in McRO, Inc. v. Bandai Namco Games America Inc., 837 F.3d 1299 (Fed. Cir. 2016), the court held that automation of a previously subjective human activity through specific computational rules constituted patent-eligible subject matter. Here, the claims similarly automate review generation and review management through defined server-side operations and rule-based processing. The claims, therefore, are not directed to a mental process.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. With regards to McRO, the Examiner notes that the CAFC did not evaluate the claims as being directed to a mental process or not, but instead determined that the incorporation of the claimed rules improved the technological process, which is an evaluation under step 2A prong two and step 2B of the Alice/Mayo test (as discussed in MPEP 2106.04(d) and MPEP 2106.05(a); and is not relevant to determining if the claims recite a mental process. As such, the Applicant’s argument fails to show the identified claim elements in the rejection do not recite an abstract idea, and the Examiner maintains that this rejection is proper.
The Applicant continues on pages 6 and 7 of their response:
“The focus of the claims is not interpersonal behavior, economic practices, or human decision- making. Instead, the claims recite a specific distributed computing architecture that changes how computerized review systems generate and manage review information.
In particular, the claims improve computerized review systems by: Generating reviews automatically instead of relying exclusively on manual review submission, Managing review confirmation through automated counters and expiration logic, Dynamically updating review states through system-triggered operations, And enabling server-side processing of interaction-related historical data.
This is analogous to Enfish, where the Federal Circuit held that claims improving the way computers operate are not abstract merely because they involve data organization.
Similarly, in DDR Holdings, LLC V. Hotels.com, 773 F.3d 1245 (Fed. Cir. 2014), the claims were patent-eligible because they addressed a problem specific to computer networks and employed a computer-centric solution. Here, the present claims address problems specific to computerized review systems, including incomplete review datasets, delayed reviews, sparse participation, and unreliable review availability.
The claims, therefore, are directed to a technological solution rooted in computer network functionality, not merely to the organization of human activity.”
The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. First, with respect to the Applicant’s argument that, “The focus of the claims is not interpersonal behavior, economic practices, or human decision- making. Instead, the claims recite a specific distributed computing architecture that changes how computerized review systems generate and manage review information,” the Examiner is not persuaded. In particular, as discussed above with respect to the Applicant’s argument regarding whether the claims recite a “Mental Process,” as set forth in MPEP 2106.04 when describing step 2A prong one of the Alice/Mayo test, the Examiner is to analyze the claim and determine whether it recites (sets forth or describes) an abstract idea. In this case, the Examiner specifically showed such a recitation in the claims, and the Applicant’s argument of “the focus of the claims” is divorced from the actual rejection itself, and the requirements under 35 USC 101; as such, the Applicant’s argument is not persuasive. Second, with respect to the Applicant’s argument that, “In particular, the claims improve computerized review systems by: Generating reviews automatically instead of relying exclusively on manual review submission, Managing review confirmation through automated counters and expiration logic, Dynamically updating review states through system-triggered operations, And enabling server-side processing of interaction-related historical data,” the Examiner is not persuaded. Initially, the Examiner notes that determining whether the claims are directed to an improvement in computer functionality, another technology, or technical field, is not part of the analysis under step 2A prong one (i.e. determining whether a claim recites an abstract idea); and instead is evaluated under step 2A prong 2 and step 2B (i.e. determining whether the additional elements, along and in combination with the recited abstract idea, integrate the abstract idea into a practical application, or add significantly more to the abstract idea) as discussed in MPEP 2106.04(d) and MPEP 2106.05(a). As such, such an argument is deemed not persuasive at showing whether the claimed elements recite an abstract idea into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Further, with respect to the assertion that the claims perform, “Generating reviews automatically instead of relying exclusively on manual review submission, Managing review confirmation through automated counters and expiration logic, Dynamically updating review states through system-triggered operations, And enabling server-side processing of interaction-related historical data,” the Examiner notes that this is not a rebuttal that the claims recite managing commercial activity (marketing, business relations). With respect to claim 1, it is noted that the Examiner stated in paragraphs 7 of the previous Non-Final Rejection, “That is, other than reciting the use of generic computer elements (information server, central server, communication network, user device), the claims recite an abstract idea. In particular, the claims recite sending an information query to a party requesting information related to an entity and/or review, the party receiving the request and aggregating the information, and the party providing the information; which encompasses managing marketing (business information and reviews), and managing the business relations between the party and the businesses. As such, the claims recite elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.” As shown here, the Examiner identified the claim elements that recite the abstract idea, explained why the recite the abstract idea, and identified the abstract grouping the abstract idea falls into. As such, the Applicant’s argument is deemed not persuasive, as it is not reflective of the claims or the rejection being argued. Third, with respect to the Applicant’s argument that, “This is analogous to Enfish, where the Federal Circuit held that claims improving the way computers operate are not abstract merely because they involve data organization,” the Examiner is not persuaded. In this case, the Examiner notes that claim 1 states, “at least one user device sends an information query to the information server, the central server, or both through a communication network; wherein the information query comprises a request for data related to at least one entity, at least one review, or a combination thereof; wherein the central server or the information server receives the information query and aggregates the data related to the at least one entity, the at least one review, or a combination thereof based on the information query; wherein the central server provides the at least one review related to the at least one entity in the information query; wherein the at least one review is a presumed review computed by the central server.” Further, claim 5 (and similarly claim 10) states, “receiving a request for a review process initiation for at least one user interaction; presuming a review for at least one entity for the at least one user interaction based on historical data; sending a confirmation request with the review to the at least one user; initiating a counter against the confirmation request, wherein the counter is based on time, attempts, or a combination thereof updating the review based on a response of the user to the confirmation request or counter expiration.” With respect to these elements, it is noted that none of these elements are directed to computer functionality (e.g. how a computer processes information, how a computer stores information, how a computer recalls information in memory, how a computer would send and receive information, etc.), but instead are elements that include managing marketing (business information and reviews), and managing the business relations between the party and the businesses. Further, it is noted that MPEP 2106.04(a)(2)(II)(B) states, “An example of a claim reciting a commercial or legal interaction, where the interaction is an agreement in the form of contracts, is found in buySAFE, Inc. v. Google, Inc., 765 F.3d. 1350, 112 USPQ2d 1093 (Fed. Cir. 2014). The agreement at issue in buySAFE was a transaction performance guaranty, which is a contractual relationship. 765 F.3d at 1355, 112 USPQ2d at 1096. The patentee claimed a method in which a computer operated by the provider of a safe transaction service receives a request for a performance guarantee for an online commercial transaction, the computer processes the request by underwriting the requesting party in order to provide the transaction guarantee service, and the computer offers, via a computer network, a transaction guaranty that binds to the transaction upon the closing of the transaction. 765 F.3d at 1351-52, 112 USPQ2d at 1094. The Federal Circuit described the claims as directed to an abstract idea because they were "squarely about creating a contractual relationship--a ‘transaction performance guaranty’." 765 F.3d at 1355, 112 USPQ2d at 1096.” (Emphasis added). As shown here, the MPEP sets forth that merely invoking a computer performing the steps of the commercial activity, as still reciting the management of commercial interactions. Further, the same section continues, “An example of a claim reciting advertising is found in Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 714-15, 112 USPQ2d 1750, 1753-54 (Fed. Cir. 2014). The patentee in Ultramercial claimed an eleven-step method for displaying an advertisement (ad) in exchange for access to copyrighted media, comprising steps of receiving copyrighted media, selecting an ad, offering the media in exchange for watching the selected ad, displaying the ad, allowing the consumer access to the media, and receiving payment from the sponsor of the ad. 772 F.3d. at 715, 112 USPQ2d at 1754. The Federal Circuit determined that the "combination of steps recites an abstraction—an idea, having no particular concrete or tangible form" and thus was directed to an abstract idea, which the court described as "using advertising as an exchange or currency." Id.” (Emphasis added). As shown here, the MPEP continues to show that merely invoking the commercial activity on a computer, does not prevent it from reciting advertising, which is the management of commercial activity. Thus, the Applicant has failed to show that the claims do not recite the management of commercial activity, as shown in the previous rejections. Fourth, with respect to the Applicant’s argument that, “Similarly, in DDR Holdings, LLC V. Hotels.com, 773 F.3d 1245 (Fed. Cir. 2014), the claims were patent-eligible because they addressed a problem specific to computer networks and employed a computer-centric solution. Here, the present claims address problems specific to computerized review systems, including incomplete review datasets, delayed reviews, sparse participation, and unreliable review availability,” the Examiner is not persuaded. In this case, the Examiner notes that the Applicant has identified their problem as, “problems specific to computerized review systems, including incomplete review datasets, delayed reviews, sparse participation, and unreliable review availability,” however none of these elements are specific to problems specific to computer networks, and as such, DDR Holdings is not relevant to the Applicant’s argument. Further, it is noted that problems in, “incomplete review datasets, delayed reviews, sparse participation, and unreliable review availability,” are problems in the commercial activity of generating and providing reviews, which is not computer functionality, a technology, or technical field. Further, it is noted that the Applicant has provided no evidence that the claims address, “incomplete review datasets, delayed reviews, sparse participation, and unreliable review availability,” and as such, the conclusory argument of the problem is deemed not relevant to the claim language itself. Therefore, the Examiner maintains that this rejection is proper.
The Applicant continues on page 7 of their response:
“Conventional review systems primarily rely on explicit user-submitted reviews, leading to incomplete datasets, delayed review availability, sparse coverage, inconsistent user participation, and reduced system reliability.
The present claims improve computerized review systems through:
Server-side computation of presumed reviews, Automated confirmation workflows, Counter-driven review-state management, Dynamic review updating, AI- or rule-based review prediction, And confidence-level processing.
These features improve the way the computerized review platform operates.
The claims, therefore, are analogous to Enfish (improved data architecture), McRO (automation using defined processing rules), CardioNet (improved machine data analysis), and Finjan, Inc. V. Blue Coat Systems, Inc., 879 F.3d 1299 (Fed. Cir. 2018), where behavior-based processing improved computer security functionality.”
The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. First, with respect to the Applicant’s argument that the claims “improve computerized reviews systems through: Server-side computation of presumed reviews, Automated confirmation workflows, Counter-driven review-state management, Dynamic review updating, AI- or rule-based review prediction, And confidence-level processing,” the Examiner is not persuaded. In this case, the Applicant has failed to identify any elements of the claims that reflect, “Automated confirmation workflows, Counter-driven review-state management, Dynamic review updating, AI- or rule-based review prediction, And confidence-level processing,” and as such, the Applicant has failed to show the claims reflect their argument. Notably, no workflows are recited in the claims, no state management are in the claims, no dynamic updating is in the claims, no artificial intelligence is in the claims 1, 5, or 10 (it is noted that claim 7 recite “wherein presuming a review includes predicting a review based on the historical data using artificial intelligence or preset rules,” however this is merely reciting the use of rules or a computer to perform the actions, without explaining how; and is not in the independent claims, and thus would not be included in the analysis of those claims), no confidence-level processing is in the claims. As such, the Applicant’s arguments fail to reflect the argued claims, and therefore fails to show the claims are directed to the argued system. Second, with respect to the Applicant’s argument that, “These features improve the way the computerized review platform operates,” it is noted that the Applicant has failed to provide any evidence of such a conclusory statement, and further it is not relevant at determining whether the claims recite an abstract idea, as discussed above. Therefore, the Examiner is not persuaded by the Applicant’s argument. Third, with respect to the Applicant’s argument that, “The claims, therefore, are analogous to Enfish (improved data architecture), McRO (automation using defined processing rules), CardioNet (improved machine data analysis), and Finjan, Inc. V. Blue Coat Systems, Inc., 879 F.3d 1299 (Fed. Cir. 2018), where behavior-based processing improved computer security functionality,” the Examiner is not persuaded. In this case, as discussed above, the Applicant’s claims are not directed towards computer functionality, but instead are directed towards the management of commercial activity. As such, the Examiner maintains that this rejection is proper.
The Applicant continues on page 8 of their response:
“The claims recite a specific technological environment involving:
Communication networks, Distributed server architecture, Centralized review computation, Data aggregation operations, Confirmation-request processing, Counter-based event management, and Automatic review updating workflows.
The ordered combination of these elements transforms interaction-related data into a system- generated review output, dynamically managed through automated server-side processing.
The claims, therefore, do not merely "collect and display information." Rather, they recite a defined technical workflow in which interaction-related data is received, a presumed review is computed, confirmation requests are automatically generated, counters are initiated and monitored, and review state is automatically updated based on user interaction or expiration conditions.
These operations constitute a concrete technological implementation that improves review- processing systems.”
The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. First, with respect to the Applicant’s arguments that the claims involve, “Communication networks, Distributed server architecture, Centralized review computation, Data aggregation operations, Confirmation-request processing, Counter-based event management, and Automatic review updating workflows,” the Examiner is not persuaded. In particular, as discussed above, the Applicant’s argument is merely a list of concepts “involved” in the claim, however the Applicant has failed to identify the specific elements of their claim that they view as integrating the recited abstract idea into a practical application. Further, as noted in MPEP 2106.05(f), “Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).” (Emphasis added). As shown here, merely invoking the use of a computer as a tool to carry out the abstract idea or to perform its ordinary functions, is deemed insufficient to integrate the abstract idea into a practical application. Second, with respect to the Applicant’s argument that, “The ordered combination of these elements transforms interaction-related data into a system-generated review output, dynamically managed through automated server-side processing,” the Examiner notes that this a reason for integrating an abstract idea into a practical application, as defined in MPEP 2106.04(d) and MPEP 2106.05. Instead, it appears to indicated that the use of the computer as a tool transforms data in one format to another, which is merely using the computer as a tool to carry out the abstract idea, which is deemed insufficient at integrating the abstract idea into a practical application. Third, with respect to the Applicant’s argument that, “These operations constitute a concrete technological implementation that improves review- processing systems,” the Examiner is not persuaded. The Examiner notes that that MPEP 2106.05(a) states, “If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. An indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art. For example, in McRO, the court relied on the specification’s explanation of how the particular rules recited in the claim enabled the automation of specific animation tasks that previously could only be performed subjectively by humans, when determining that the claims were directed to improvements in computer animation instead of an abstract idea. McRO, 837 F.3d at 1313-14, 120 USPQ2d at 1100-01. In contrast, the court in Affinity Labs of Tex. v. DirecTV, LLC relied on the specification’s failure to provide details regarding the manner in which the invention accomplished the alleged improvement when holding the claimed methods of delivering broadcast content to cellphones ineligible. 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016).” (Emphasis added). As shown and emphasized here, if it is asserted that the invention improves computer functionality or another technology, the Applicant must provide evidence in their specification to support such the improvement, and that the claims must reflect the improvement. In this case, the Applicant has failed to provide any evidence of the argued improvement, and instead merely relied upon a conclusory argument that the claims improve computer processing systems, which is not persuasive. Further, it is noted that review systems, are not a technology themselves, but instead are the abstract idea of review generation and marketing. With respect to this, MPEP 2106.05(a)(II) states, “Notably, the court did not distinguish between the types of technology when determining the invention improved technology. However, it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. For example, in Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.” (Emphasis added). In this case, the improvement in writing reviews and providing them, is merely an improvement in the commercial activity, and not an improvement in computers or technology. Thus, the Examiner is not persuaded by the Applicant’s argument, and maintains that this rejection is proper.
The Applicant continues on pages 8 and 9 of their response, “The dependent claims further reinforce practical application integration: Identifier-based interaction processing, AI-based or rules-based review prediction, Confidence-level determination, Automated review-state transitions, and Structured response handling logic. These are concrete processing operations performed by the claimed system and are not merely mental steps or methods of organizing human activity.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. In this case, the Examiner notes that the Applicant has failed to identify any claims specifically argued, or the limitations in any claims that they are arguing, and instead relied on general statements of functions and logic, which is not reflective of the claims. As such, the Applicant’s argument is deemed generally conclusory, and is deemed not persuasive.
The Applicant continues on page 9 of their response:
“Here, the claims recite a non-conventional arrangement in which:
Interaction-related data is aggregated, Presumed reviews are computed server-side, Review confirmation requests are automatically generated, Counters are initiated and monitored, Review states are updated automatically, And predictive review operations may include AI processing and confidence-level determination.
The Office Action does not provide evidence that the ordered combination was well understood, routine, or conventional.
Importantly, conventional review systems merely stored and displayed user-submitted reviews. The present claims instead implement an automated review-generation and lifecycle- management framework that dynamically generates, validates, tracks, and updates reviews through server-driven processing logic.”
The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. First, with respect to the Applicant’s arguments regarding the claims reciting, “Interaction-related data is aggregated, Presumed reviews are computed server-side, Review confirmation requests are automatically generated, Counters are initiated and monitored, Review states are updated automatically, And predictive review operations may include AI processing and confidence-level determination,” it is noted that the Applicant’s argument has failed to identify the specific arrangement of claim elements in the claims that encompass these elements. As such, the Applicant’s argument regarding general concepts in the claims, instead of a specific combination of elements is deemed not convincing, as it is not reflective of the claims. Second, with respect to the Applicant’s argument regarding, “The Office Action does not provide evidence that the ordered combination was well understood, routine, or conventional,” is it noted that the requirement of evidence showing well understood, routine, or conventional activity is only in the instance in which the Examiner has indicated elements as well understood, routine, or conventional, as stated in MPEP 2106.07(a)(III), “At Step 2A Prong Two or Step 2B, there is no requirement for evidence to support a finding that the exception is not integrated into a practical application or that the additional elements do not amount to significantly more than the exception unless the examiner asserts that additional limitations are well-understood, routine, conventional activities in Step 2B.” Thus, the Applicant’s argument regarding the lack of evidence is not persuasive, as it is not a requirement placed on the Examiner. Therefore, the Examiner maintains that this rejection is proper.
The Applicant continues on page 11 of their response, “As in Example 47, the present claims do not merely recite information analysis in the abstract. Rather, they recite a defined technological implementation in which server-side processing operations generate and manage computed outputs within a practical system architecture.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. With respect to Example 47, the Examiner noted that the Office stated for claim 3:
“The consideration of whether the claim as a whole includes an improvement to a computer or to a technological field requires an evaluation of the specification and the claim to ensure that a technical explanation of the asserted improvement is present in the specification, and that the claim reflects the asserted improvement. See MPEP 2106.04(d)(1). According to the background section, existing systems use various detection techniques for detecting potentially malicious network packets and can alert a network administrator to potential problems. The disclosed system detects network intrusions and takes real-time remedial actions, including dropping suspicious packets and blocking traffic from suspicious source addresses. The background section further explains that the disclosed system enhances security by acting in real time to proactively prevent network intrusions.
The claimed invention reflects this improvement in the technical field of network intrusion detection. Steps (d)-(f) provide for improved network security using the information from the detection to enhance security by taking proactive measures to remediate the danger by detecting the source address associated with the potentially malicious packets. Specifically, the claim reflects the improvement in step (d), dropping potentially malicious packets in step (e), and blocking future traffic from the source address in step (f). These steps reflect the improvement described in the background. Thus, the claim as a whole integrates the judicial exception into a practical application such that the claim is not directed to the judicial exception.
The additional elements in steps (d)-(f), when considered in combination, integrate the abstract idea into a practical application because the claim improves the functioning of a computer or technical field. See MPEP 2106.04(d)(1) and 2106.05(a). The claimed invention reflects this improvement in the technical field of network intrusion detection. Thus, the claim as a whole integrates the judicial exception into a practical application (Step 2A, Prong Two: YES), such that the claim is not directed to the judicial exception. (Step 2A: NO). The claim is eligible.” (Emphasis added).
In this case, as shown and emphasized above, Example 47 claim 3, specifically when view in combination, recited an improvement in the functioning of a computer or technical field; as supported by the “specification” of the Example. Unlike this Example, the Applicant has failed to show evidence of an improvement in the functioning of a computer or technical field, and instead have merely asserted of an improvement, and that the improvement is in the commercial activity. It is further noted that while the Applicant asserts that the server side processing operations in their claims integrate the abstract idea into a practical system architecture, it is noted that these computer components are merely being invoked as a tool to carry out the abstract idea, and the Applicant’s lack of disclosure regarding computer functionality or some other technology improvement, fails to show that the claims are integrated into a practical application. Therefore, the Examiner maintains that this rejection is proper.
Applicant's arguments filed 22 May 2026 with respect to the art teaching computing a presumed review in claim 1 have been fully considered but they are not persuasive.
With respect to the claims and prior art, the Applicant argues on pages 12 and 13 of their response:
“Importantly, aggregating or combining stored review records is fundamentally different from computing a presumed review as required by the present claims. In Narula, reviews exist before query processing, and the JOIN operation merely combines or organizes the retrieved review information for display. Even if Narula applies weighting, filtering, ranking, or other processing to existing reviews, such operations merely affect the presentation of existing review records and do not disclose the computation of the review itself based on aggregated data.
By contrast, the present claims require that "the at least one review is a presumed review" computed via the central server based on aggregated data. Thus, the claimed review is itself a server-derived evaluative output, rather than a retrieved collection of already existing user- authored reviews. Narula nowhere discloses generating, deriving, or computing a presumed review from aggregated data related to an entity and review information. Instead, Narula merely retrieves and presents reviews that were previously authored and stored in the reviews database.
This distinction is significant because Narula computes only the arrangement or presentation of existing review information, whereas the present claims require computation of the review itself. Accordingly, the operations disclosed in Narula do not disclose the claimed "presumed review computed via the central server."
The Examiner respectfully disagrees with the Applicant’s interpretation of the cited prior art of record and the broadest reasonable interpretation of the Applicant’s claimed invention. With respect to claim 1, the Examiner notes that the Applicant has amended the claim to state, “wherein the central server or the information server receives the information query and aggregates the data related to the at least one entity, the at least one review, or a combination thereof based on the information query; wherein the central server provides the at least one review related to the at least one entity in the information query; wherein the at least one review is a presumed review computed by the central server.” As shown here, the Applicant has claimed that the server (the central or the information server) aggregates data related to an entity or a review, the central server provides the review related to the entity to the user, and the review is a presumed review computed by the server. In this case, the Applicant has failed to claim any steps as to how the server computes a “presumed review,” and instead merely left it broadly claimed. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., server-derived evaluative output) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Notably, while the Applicant has claimed that the review is computed by a server, the Applicant has put no bounds on how this is accomplished. With respect to Narula, it is noted that Narula states in paragraph 81, “FIG. 6 illustrates, in a sequence diagram, an example of a method of reviews lookup 600, in accordance with some embodiments. The method 600 begins with the device 10 receiving an INPUT 602 from a user requesting a review for a business. The business name and/or phone number may be provided as a function call variable. Next, the device 10 may send a GET review message 604 to the review engine 222. The message 604 may include the business name and/or phone number as a function call variable. Next, the review engine 222 may send a GET data message 606 to the phonebook repository 143 to obtain an identifier for the business for which the review is being requested. Next, the phonebook repository 143 may send a return data message 608 to the review engine 222. The return data message 608 may include the business name, address, phone number and Foreign Key (FK). Next, the review engine 222 may send a GET rating message 610 to the reviews database 142. The GET rating message 610 may include the FK as a function call variable. Next, the reviews database 142 may send a return message 612 to the review engine 222. This message 612 includes the rating. Next, the review engine 222 sends a return review message 614 to the device 10, which then displays it 616 for the user. The review message 614 may comprise review data pertaining to the business, including the name, address, phone number and rating.” (Emphasis added). Narula continues in paragraph 90, “With respect to FIG. 6, an example of looking-up the reviews 600 of a business/service provider on a mobile device is provided. For example, a user opens a mobile App 10 and types 602 the name or phone number of the business/service provider. The user then clicks a Submit button that sends 604 a ‘GET’ query containing the Business Name and/or Phone Number to the review engine 222. The review engine 222 forwards 606 this request to the phonebook repository 143 that returns 608 the Foreign Key (FK), Name, Phone, Address, and Operating Hours of the business/service provider to the review engine 222. The review engine 222 then sends a ‘GET’ query 610 containing the FK to the system reviews database 142 and receives 612 the Business/Service Summary, Specialization, Rating, Comments, and FK. The review engine 222 may then perform a ‘JOIN’ on the data received from the phonebook repository 143 and the system reviews database 142 and generate the result comprising Name, Phone, Address, Operating Hrs, Business/Service Summary, Specialization, Rating, and Comments. The business/service providers review is shown on the mobile device as Name, Phone, Address, Operating Hrs, Business/Service Summary, Specialization, Rating, and Comments.” (Emphasis added). Narula continues in paragraph 91, “FIG. 7 illustrates, in a spreadsheet table, an example of a search result 700 for an online review, in accordance with some embodiments. In this example, the search result 700 is for “Orthopaedic Doctors in New York”. The search result 700 shows, in columns, the keyword 702 search query, doctor images 704, corresponding doctor names 706, overall rank (or overall score) 708 for each doctor, filter options 710 used to review the doctor, social rank 712 being the rank provided by the review, each reviewer name 714, the reviewer relationship 716 to the user requesting the search result 700, rating options 718 used to review the doctor, and values 720 on a 5 point scale with 1 being lowest and 5 being highest, for the ratings options 718. A user may then select a doctor based on the overall rank 708, social rank 712 of preferred reviewers, ratings values 720 for specific features 718, or a combination thereof.” (Emphasis added). As shown and emphasized here, Narula has disclosed a system where a user requests a review lookup to a server and includes businesses they’re interested in (e.g. claim element, “An information server; a central server communicatively coupled to the information server; and at least one user device sends an information query to the information server, the central server, or both through a communication network; Wherein the information query comprises a request for data related to at least one entity, at least one review, or a combination thereof”); wherein the server receives the query and aggregates the data related to the entity or review based on the query (e.g. claim element, “Wherein the central server or the information server receives the information query and aggregates the data related to the at least one entity, the at least one review, or a combination thereof based on the information query”); wherein the server provides the review to the user, and wherein the review is computed by a server (e.g. claim limitation “wherein the at least one review is… computed by the central server”). In this case, the collection of a review by the server from a repository is the “computing” of the review. Notably, as discussed above, the Applicant’s claims do not recite how exactly the server computes the review, merely that it is a presumed review that is computed (i.e. processed) by the server. With the aspect that the review is “presumed,” it is noted that this newly amended element was not previously in claim 1, and thus, Narula is not relied upon in the current rejection; however, Chapman does teach a server computing a presumed review. In particular, Chapman states in paragraph 15, “Evaluation server 140 may obtain the new evaluation target, and review generation logical circuit 124 may apply the user-specific evaluation profile to the new evaluation target to predict the user's evaluation of the new evaluation target. The predicted evaluation may be used to generate and display the predicted evaluation on the graphical user interface for the user to review and edit. In some examples, the predicted evaluation may be used to auto-complete the evaluation as displayed on the graphical user interface.” (Emphasis added). As shown and emphasized here, Chapman has disclosed a server predicting (i.e. presuming) a review for a target based on a user request. As such, the cited prior art of record is noted as teaching a server computing a presumed review. Therefore, the Examiner maintains that the amended rejection below is proper.
Applicant's arguments filed 22 May 2026 with respect to the art teaching presuming a review of claims 5 and 10 have been fully considered but they are not persuasive.
With respect to claim 5, the Applicant argues on page 15 of their response, “Applicant respectfully submits that Chapman merely discloses a prediction or suggestion mechanism based on historical user data, and the predicted evaluation remains dependent upon subsequent user action and approval. In contrast, the presently claimed invention is directed to a presumed review generated and maintained by the system itself, where the review exists as a system-controlled review artifact subject to automated lifecycle management, including automatic finalization upon counter expiration. Thus, a system prediction using historical data is fundamentally different from a system presumed review using historical data, both structurally and functionally.” The Examiner respectfully disagrees with the Applicant’s interpretation of the cited prior art of record and the broadest reasonable interpretation of the claimed invention. With respect to claim 5, the Examiner notes that the claim states, “receiving a request for a review process initiation for at least one user interaction; presuming a review for at least one entity for the at least one user interaction based on historical data.” As shown here, the Applicant has claimed receiving a request for a review process initiation, presuming a review for an entity based on historical data, and sending a confirmation request with a review to the user. Notably, the Applicant has not disclosed how a review is presumed besides being based on historical data. With regards to the Applicant’s argument that, “presently claimed invention is directed to a presumed review generated and maintained by the system itself, where the review exists as a system-controlled review artifact subject to automated lifecycle management, including automatic finalization upon counter expiration,” the Examiner is not persuaded. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., the presumed review is maintained by the system (notably claim 5 doesn’t not recite any system), the review exists as a system-controlled review artifact subject to automated lifecycle management, including automatic finalization upon counter expiration) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Notably, nothing in the claim refers to the review exists as a system-controlled review artifact subject to automated lifecycle management, or automatic finalization upon counter expiration. With respect to a counter, it is noted that the claim states, “sending a confirmation request with the review to the at least one user ; initiating a counter against the confirmation request, wherein the counter is based on time, attempts, or a combination thereof; updating the review based on a response of the user to the confirmation request or counter expiration.” As shown here, the Applicant has claimed sending the presumed review for confirmation to the requesting user, initiating a counter against the confirmation request, and updating the review based on a response or the counter expiration. That is, there is no finalization of a review, and instead the review is updated upon either a user response or a counter expiring. Notably, the Applicant has not claimed updating a review is finalizing the review, or that the counter must expire to perform any updating or finalization. Next, with respect to the Applicant’s argument that, “a system prediction using historical data is fundamentally different from a system presumed review using historical data,” the Examiner is not persuaded. In this case, as stated above, the claim recites “presuming a review for at least entity for the at least one user interaction based on historical data.” In the instance of Chapman, the reference states in paragraph 15, “Evaluation server 140 may obtain the new evaluation target, and review generation logical circuit 124 may apply the user-specific evaluation profile to the new evaluation target to predict the user's evaluation of the new evaluation target. The predicted evaluation may be used to generate and display the predicted evaluation on the graphical user interface for the user to review and edit. In some examples, the predicted evaluation may be used to auto-complete the evaluation as displayed on the graphical user interface.” (Emphasis added). Chapman continues in paragraph 24, “Review determination logical circuit 114 may be configured to determine, with the user evaluation prediction logical circuit, a predicted user review of the review target by applying the user-specific evaluation profile to the review target-specific characteristics.” (Emphasis added). Further paragraph 47 states, “In some examples, method 200 may include obtaining a user-created review of the review target at step 212. For example, the user-created review may be obtained from client computers 104 and/or from one or more reviewers 150. Method 200 may also include determining a review discrepancy at step 214 as a difference between the user-created review and the predicted review. Method 200 may also include modifying the user-specific evaluation profile based on the review discrepancy (e.g., continuing to train and refine the user-specific evaluation profile).” (Emphasis added). Further paragraph 52 states, “Evaluation server 140 may generate, train, modify, and/or apply user-specific evaluation profile 402. In operation 422, evaluation server 140 may obtain user-specific evaluation profile 402 and apply it to a review target to generate a predicted review. In operation 424, evaluation server 140 may obtain user-specific evaluation profile 402 and apply it to a review target to generate a tailored review, e.g., by auto-completing answers to review questions based on a predicted review. The tailored review may be presented to the user through reviewer interface 150. In operation 426, evaluation server 140 may obtain user-specific evaluation profile 402 and apply it to a review target to generate a predicted review, and compare the predicted review with a new review obtained from reviewer interface 150 to determine a review discrepancy as a difference between the predicted review and new review. The review discrepancy may be used by evaluation server 140 to modify and/or train user-specific evaluation profile 402.” (Emphasis added). As shown and emphasized here, Chapman has disclosed the server predicting (i.e. presuming) a review for a target based on user profiles and user reviews (i.e. historic information). With regards to the Applicant’s claims, it is noted that the Applicant has not set forth any definition or constraints on historical data, or how historical data is used to presume a review. As such, the Applicant’s argument that predicting a review using historical data and a system presuming a review using historical data are fundamentally different, is deemed not persuasive. It is further noted to this argument, claim 7 explicitly states, “wherein presuming a review includes predicting a review based on the historical data using artificial intelligence or preset rules.” (Emphasis added). As such, the Applicant’s argument that these are fundamentally different is directly contrary to the Applicant’s claims. Therefore, the Examiner maintains that this rejection is proper.
Applicant's arguments filed 22 May 2026 with respect to the art teaching a counter of claims 5 and 10 have been fully considered but they are not persuasive.
With respect to claims 5 and 10, the Applicant argues on page 16 of their response, “The counter in Bowen is therefore fundamentally different from the claimed counter. In Bowen, the timing constraint governs a human decision-making process applied to user- provided content In contrast, the claimed counter operates within a system-controlled review- generation process, in which the system already presumes the review and is automatically finalized upon the counter's expiration. Bowen does not disclose or suggest a counter that triggers automatic submission or finalization of a system-generated review in the absence of user input, nor does it disclose reminder-based or attempt-based counter mechanisms tied to such a process.” The Examiner respectfully disagrees with the Applicant’s interpretation of the cited prior art of record and the broadest reasonable interpretation of the claimed invention. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Notably, with respect to the Applicant’s argument against Bowen, it is noted that the cited rejection was made in combination, specifically, Chapman in view of Bowen. With regards to the claims, it is noted that claim 5 states, “sending a confirmation request with the review to the at least one user; initiating a counter against the confirmation request, wherein the counter is based on time, attempts, or a combination thereof; updating the review based on a response of the user to the confirmation request or counter expiration.” As shown here, the Applicant has claimed sending a confirmation request for a review to a user, initiating a counter against the confirmation request (which can be based on time or attempts), and updating the review based on a response from the user or counter expiration. With respect to Chapman, it is noted that Chapman states in paragraph 15, “Evaluation server 140 may obtain the new evaluation target, and review generation logical circuit 124 may apply the user-specific evaluation profile to the new evaluation target to predict the user's evaluation of the new evaluation target. The predicted evaluation may be used to generate and display the predicted evaluation on the graphical user interface for the user to review and edit. In some examples, the predicted evaluation may be used to auto-complete the evaluation as displayed on the graphical user interface.” (Emphasis added). Chapman continues in paragraph 25, “Review obtaining logical circuit 116 may be configured to obtain, from the user interface, a user-created review of the review target. In some examples, review determination logical circuit 114 may be configured to compare the user-created review to the predicted user review to determine a review discrepancy. In examples where the reviews or evaluations are generated quantitatively, the review discrepancy may be a quantitative difference between the predicted review and the user-generated review. In examples where the review or evaluation is qualitative or freeform, the review discrepancy may also be qualitative (e.g., text-based descriptions) or quantitative (e.g., a percentage).” (Emphasis added). Further, paragraph 47, “In some examples, method 200 may include obtaining a user-created review of the review target at step 212. For example, the user-created review may be obtained from client computers 104 and/or from one or more reviewers 150. Method 200 may also include determining a review discrepancy at step 214 as a difference between the user-created review and the predicted review. Method 200 may also include modifying the user-specific evaluation profile based on the review discrepancy (e.g., continuing to train and refine the user-specific evaluation profile).” (Emphasis added). As shown here, Chapman has disclosed predicting a review for a target, presenting it to a user for confirmation, receiving a user response (including a user written review or edits from the user), and then updating the review based on the response from the user. As such, Chapman has disclosed, “Sending a confirmation request with the review to the at least one user; Updating the review based on a response of the user to the confirmation request or counter expiration,” wherein the “counter expiration,” is merely invoked as an option when updating the review. As the counter portion is optional language, the element is satisfied if the review is updated based on a response of the user, which is what Chapman teaches. With regards to Bowen, it is noted that Bowen states in paragraph 342, “Optionally, if the CNN approves the user-provided content, the user-provided content may be presented to a human for human review and approval (e.g., via an approval user interface) prior to printing the product with the user provided content. A confidence score associated the CNN evaluation/classifications may be generated and presented to the human reviewer.” (Emphasis added). Further, paragraph 343 states, “The human may be given a specified period of time (e.g., 1 hour, 12 hours, 24 hours) to review the user provided content. A countdown clock (which may be graphic and/or textual) may be presented in association with the approval request, where the clock indicates how much time is left in the specified review period of time. If the human reviewer approves the user provided content, or takes no action within the specified time period, the printing process may automatically proceed. If the human reviewer rejects the user provided content within the specified time period, the printing of the user provided content on the product and shipping of same may be inhibited, and a rejection notification may be generated and transmitted to the user. FIG. 32B illustrates an example user interface that lists orders pending for review, with an indication as to how much time (e.g., how many hours) are remaining for review. If an order entry is selected an order summary may be accessed and presented including one or more sides of the ordered item (including user customizations and user provided content), a customer identifier, customer contact data (e.g., an email or short message address), a textual countdown clock, and accept and reject controls.” (Emphasis added). As shown and emphasized here, Bowmen describes presenting a user output from a CNN, wherein the presentation includes a countdown timer for which the user has to approve or deny the presented information. As such, Bowen teaches the claimed element, “Initiating a counter against the confirmation request, wherein the counter is based on time, attempts, or a combination thereof.” Thus, the combination of Chapman and Bowen teaches the claimed elements of, “sending a confirmation request with the review to the at least one user; initiating a counter against the confirmation request, wherein the counter is based on time, attempts, or a combination thereof; updating the review based on a response of the user to the confirmation request or counter expiration.” Therefore, the Examiner maintains that this rejection is proper.
Applicant's arguments filed 22 May 2026 with respect to the art claim 6 have been fully considered but they are not persuasive.
With respect to claim 6, the Applicant argues on page 17 of their response, “In contrast, the claimed invention utilizes a unique identifier that is determined in connection with a specific user interaction and corresponding entity at the outset of the process, and this identifier is used to initiate and control the system-driven review workflow, including the presumption of a review based on historical data. As disclosed in claim 6, the initiation of the review process comprises determining a unique identifier for the at least one user interaction and the corresponding entity. This functional role of the identifier as a trigger for initiating the review process is not disclosed or suggested in Narula.” The Examiner respectfully disagrees with the Applicant’s interpretation of the cited prior art of record and the broadest reasonable interpretation of the claimed invention. With respect to claim 6, the Examiner notes that the Applicant claims, “wherein the review process initiation comprises determining a unique identifier related to the at least user interaction and corresponding entity.” As shown here, the Applicant has claimed determining a unique identifier related to the user interaction and entity. With respect to the Applicant’s argument that, “this identifier is used to initiate and control the system-driven review workflow, including the presumption of a review based on historical data,” the Examiner is not persuaded. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., the unique identifier is used to initiate and control the system-driven review workflow) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Notably, the Applicant has not claimed that the determining of a unique identifier is a trigger for initiating and controlling a system-driven review workflow, merely that a party (as no system is stated in claim 5) receives a request for a review process initiation (as recited in claim 5), that this initiation includes determining a unique identifier (as recited in claim 6) and presuming a review (as recited in claim 5). As shown in the claims (cited above) and this recited breakdown of the claims, there is no language in the claims that the identifier is used to initiate and control the system-driven review workflow. Next, with regards to Narula, it is noted that Narula has disclosed a user requesting a review for an identified entity, and provides unique identifiers for themselves and for businesses (paragraphs 83-85 and 87-89), thus, Narula has disclosed determining a unique identifier related to the at least user interaction and corresponding entity when initiating a review process. It is noted, that if the Applicant intended the unique identifier to be generated by some system/server, and that this generation in response to a request for a review process, triggered a presumed review, as argued, then the Applicant is recommended to amend the claims to state the exact triggering mechanism and what specific steps that entails. Therefore, the Examiner maintains that this rejection is proper.
Applicant's arguments filed 22 May 2026 with respect to the hindsight have been fully considered but they are not persuasive.
With respect to the rejection, the Applicant argues on page 17 of their response, “The Examiner's proposed combination appears to be based on hindsight reconstruction using the Applicant's disclosure as a blueprint. In the absence of a proper motivation to combine and in view of the substantial structural and functional differences between the claimed invention and the cited references, the rejection under §103 is improper.” The Examiner respectfully disagrees. In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). In this case, the Examiner has relied upon only the knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure. Specifically, the Examiner has shown that the cited prior art has taught each individual element of the claims, and provided reasoning as to why the cited prior art in combination would yield predictable results. As such, the Examiner maintains that the rejection was proper, and the Examiner relied on proper reconstruction.
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 1-4 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite an information server; a central server communicatively coupled to the information server; and at least one user device sends an information query to the information server, the central server, or both through a communication network; wherein the information query comprises a request for data related to at least one entity, at least one review, or a combination thereof; wherein the central server or the information server receives the information query and aggregates the data related to the at least one entity, the at least one review, or a combination thereof based on the information query; wherein the central server provides the at least one review related to the at least one entity in the information query; and wherein the at least one review is a presumed review computed by the central server.
The limitations of sending an information query to a party, wherein the information query comprises a request for data related to at least one entity, at least one review, or a combination thereof, wherein the party receives the information query and aggregates the data related to the at least one entity, the at least one review, or a combination thereof based on the information query, wherein the party provides the at least one review related to the at least one entity in the information query, and wherein the at least one review is a presumed review; as drafted, under the broadest reasonable interpretation, encompass the management of commercial activity (marketing, business relations), and steps that can be performed in the human mind. That is, other than reciting the use of generic computer elements (information server, central server, communication network, user device), the claims recite an abstract idea. In particular, the claims recite sending an information query to a party requesting information related to an entity and/or review, the party receiving the request and aggregating the information, and the party providing the information; which encompasses managing marketing (business information and reviews), and managing the business relations between the party and the businesses. In addition, the review being a presumed review; encompasses a party predicting a review; which encompasses managing marketing (business information and reviews), and managing the business relations between the party and the businesses. As such, the claims recite elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. In addition, the claims further recite sending an information query to a party, said party receiving the query and aggregating a response, and said party providing the response; which encompass elements that can be performed in the human mind (observation, evaluation, judgement). In addition, the review being a presumed review; encompasses a party mentally evaluating and predicting a review; which can be performed in the human mind (observation, evaluation, judgement). As such, the claims recite elements that fall into the “Mental Processes” grouping of abstract ideas. The claims recite an abstract idea.
This judicial exception is not integrated into a practical application. The claims do not recite additional elements, when taken individually and in an ordered combination with the abstract idea, that improve the functioning of a computer, another technology, or technical field. The claims do not recite the use of, or apply the abstract idea with, a particular machine, the claims do not recite the transformation of an article from one state or thing into another. Finally, the claims do not recite additional elements, taken individually and in an ordered combination, that apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment. Instead, the claims recite the use of generic computer elements (information server, central server, communication network, user device) as tools to carry out the abstract idea. The claims are directed to an abstract idea.
The claim(s) does/do not include additional elements, when taken individually and in an ordered combination with the abstract idea, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using generic computer elements and machines to perform the steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are directed to non-patent eligible subject matter.
The dependent claims 2-4, when taken individually and in an ordered combination with the abstract idea, do not recite additional elements that integrate the abstract idea into a practical application, or add significantly more to the abstract idea. In particular, the claims further recite the party communicating with the user (these parties being the generic computer elements identified in claim 1), to compute a review; which encompasses computing the review requested; which is the management of commercial activities, and the performance of elements that can be performed in the human mind (observation, evaluation, judgement); as such the claims further recite elements that fall under the “Certain Methods of Organizing Human Activity” and the “Mental Processes” grouping of abstract ideas (claim 2). In addition, the claims further recite the content of a query, which is deemed merely narrowing the field of use; and thus, does not recite additional elements that integrate the abstract idea into a practical application, or add significantly more to the abstract idea (claim 3). In addition, the claims further recite the content of a review, which is deemed merely narrowing the field of use; and thus, does not recite additional elements that integrate the abstract idea into a practical application, or add significantly more to the abstract idea (claim 4).
Claims 5-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite receiving a request for a review process initiation for at least one user interaction; presuming a review for at least one entity for the at least one user interaction based on historical data; sending a confirmation request with the review to the at least one user; initiating a counter against the confirmation request, wherein the counter is based on time, attempts, or a combination thereof; and updating the review based on a response of the user to the confirmation request or counter expiration.
The limitations of receiving a request for a review process initiation for at least one user interaction, presuming a review for at least one entity for the at least one user interaction based on historical data, sending a confirmation request with the review to the at least one user, initiating a counter against the confirmation request, and updating the review based on a response of the user to the confirmation request or counter expiration; as drafted, under the broadest reasonable interpretation, encompasses the management of commercial activity (marketing, business relations), and steps that can be performed in the human mind. That is, other than reciting the use of generic computer elements (user device, server), the claims recite an abstract idea. In particular, the claims recite receiving a request for a review process initiation from a user, presuming a review for the user based on historical information, providing the presumed review to the user along with a time limit to confirm or reject the review, and updating the review based on the user confirmation; which encompasses the writing a review for a user upon request, and receiving their approval/disapproval in a time period; which is the management of commercial activity (reviews/marketing, business relations between the user and a business). As such, the claims recite elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. In addition, the claims further recite receiving a request for a review process initiation from a user, presuming a review for the user based on historical information, providing the presumed review to the user along with a time limit to confirm or reject the review, and updating the review based on the user confirmation; which encompass elements that can be performed in the human mind (observation, evaluation, judgement). As such, the claims recite elements that fall into the “Mental Processes” grouping of abstract ideas. The claims recite an abstract idea.
This judicial exception is not integrated into a practical application. The claims do not recite additional elements, when taken individually and in an ordered combination with the abstract idea, that improve the functioning of a computer, another technology, or technical field. The claims do not recite the use of, or apply the abstract idea with, a particular machine, the claims do not recite the transformation of an article from one state or thing into another. Finally, the claims do not recite additional elements, taken individually and in an ordered combination, that apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment. Instead, the claims recite the use of generic computer elements (user device, server) as tools to carry out the abstract idea. The claims are directed to an abstract idea.
The claim(s) does/do not include additional elements, when taken individually and in an ordered combination with the abstract idea, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using generic computer elements and machines to perform the steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are directed to non-patent eligible subject matter.
The dependent claims 6-9, when taken individually and in an ordered combination with the abstract idea, do not recite additional elements that integrate the abstract idea into a practical application, or add significantly more to the abstract idea. In particular, the claims further recite determining an identifier of the user interaction and business; which encompasses determining the relevant business and interaction to review, which is the management of commercial activities, and the performance of elements that can be performed in the human mind (observation, evaluation, judgement); as such the claims further recite elements that fall under the “Certain Methods of Organizing Human Activity” and the “Mental Processes” grouping of abstract ideas (claim 6). In addition, the claims further recite predicting a review based on historical data using present rules; which encompasses predicting a user’s review based on their past experiences; which is the management of commercial activities, and the performance of elements that can be performed in the human mind (observation, evaluation, judgement); as such the claims further recite elements that fall under the “Certain Methods of Organizing Human Activity” and the “Mental Processes” grouping of abstract ideas (claim 7). In addition, the use of “artificial intelligence” is recited at such a high level of generality, that it is deemed merely “apply it,” and thus, does not recite additional elements that integrate the abstract idea into a practical application, or add significantly more to the abstract idea (claim 7). In addition, the claims further recite determining a rating and confidence level based on the user interaction and historical data; which encompasses predicting a user’s review and the confidence level of said review being correct based on collected data; which is the management of commercial activities, and the performance of elements that can be performed in the human mind (observation, evaluation, judgement); as such the claims further recite elements that fall under the “Certain Methods of Organizing Human Activity” and the “Mental Processes” grouping of abstract ideas (claim 8). In addition, the claims further recite updating the review based on user responses to the presumed review; which is the management of commercial activities, and the performance of elements that can be performed in the human mind (observation, evaluation, judgement); as such the claims further recite elements that fall under the “Certain Methods of Organizing Human Activity” and the “Mental Processes” grouping of abstract ideas (claim 9).
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.
Claims 1-4 are rejected under 35 U.S.C. 103 as being unpatentable over Narula (US 2021/0365968 A1) (hereinafter Narula), in view of Chapman et al. (US 2019/0340659 A1) (hereinafter Chapman).
With respect to claim 1, the Narula teaches:
An information server; a central server communicatively coupled to the information server; and at least one user device sends an information query to the information server, the central server, or both through a communication network; Wherein the information query comprises a request for data related to at least one entity, at least one review, or a combination thereof (See at least paragraphs 81, 90, and 91 which describe a user requesting a review lookup, wherein the request is sent to a server, and includes the business they are interested in receiving the review for and their information).
Wherein the central server or the information server receives the information query and aggregates the data related to the at least one entity, the at least one review, or a combination thereof based on the information query; Wherein the central server provides the at least one review related to the at least one entity in the information query (See at least paragraphs 81, 90, and 91 which describe a user requesting a review lookup, wherein the request is sent to a server, and includes the business they are interested in receiving the review for and their information, and wherein the server provides retrieved reviews to the user).
Narula discloses all of the limitation of claim 1 as stated above. Narula does not explicitly disclose the following, however Chapman teaches:
Wherein the at least one review is a presumed review computed by the central server (See at least paragraphs 15, 24, 25, 47, and 52 which describe predicting a review for a product/service for the user).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of a user requesting a review lookup, wherein the request is sent to a server, and includes the business they are interested in receiving the review for and their information, and wherein the server provides retrieved reviews to the user of Narula, with the system and method of predicting a review for a product/service for the user based on historical information of the user and other users of Chapman. By predicting reviews for a service entity, a system will predictably be able to provide interested parties with reviews for business, which will generate more interest in the service from customers seeking reviews.
With respect to claim 2, the combination of Narula and Chapman discloses all of the limitations of claim 1 as stated above. In addition, Narula teaches:
Wherein the central server communicates with the information server, at least one user device, or a third-party server to compute the review (See at least paragraphs 81, 90, and 91 which describe a server communicating with a database and the user to aggregate reviews).
With respect to claim 3, Narula/Chapman discloses all of the limitations of claim 1 as stated above. In addition, Narula teaches:
Wherein the information query contains a unique identifier (See at least paragraphs 81, 90, and 91 which describe the user requesting a review, and providing a unique identifier (e.g. phone number, business name) which identifies the parties they wish to receive a review regarding).
With respect to claim 4, Narula/Chapman discloses all of the limitations of claim 1 as stated above. In addition, Narula teaches:
Wherein the at least one review comprises a star rating, a score, a comment, a badge, a comparative metric, or a combination thereof (See at least paragraphs 80, 90, and 91 which describe the reviews as including comments and ratings on a scale).
Claims 5 and 7-10 are rejected under 35 U.S.C. 103 as being unpatentable over Chapman, in view of Bowen (US 2020/0160612 A1) (hereinafter Bowen).
With respect to claims 5 and 10, Chapman teaches:
Receiving a request for a review process initiation for at least one user interaction (See at least paragraphs 14, 15, 23, 42, 46, and 47 which describe receiving an initiation review process for user interactions with services/businesses)
Presuming a review for at least one entity for the at least one user interaction based on historical data (See at least paragraphs 15, 24, 25, 47, and 52 which describe predicting a review for a product/service for the user based on historical information of the user and other users).
Sending a confirmation request with the review to the at least one user; Updating the review based on a response of the user to the confirmation request or counter expiration (See at least paragraphs 15, 25, 26, 47, 49, 52, and 53 which describe presenting the generated reviews to a user and receiving their approval, disapproval, or edit of the review based on their experience with the product/service, wherein the user profile and review is updated based on the user response).
Chapman discloses all of the limitations of claims 5 and 10 as stated above. Chapman does not explicitly disclose the following, however Bowen teaches:
Initiating a counter against the confirmation request, wherein the counter is based on time, attempts, or a combination thereof (See at least paragraphs 342 and 343 which describe presenting a user for confirmation regarding the output of a CNN, wherein the presentation includes a countdown timer for which the user has to approve or deny the presented information).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of generating a predicted review for a product/service based on user interactions and historical data, wherein a user is presented with the predicted review and is able to approve/disapprove/edit it based on their own experience, and updating their profile and the reviews based on the response of Chapman, with the system and method of presenting a user for confirmation regarding the output of a CNN, wherein the presentation includes a countdown timer for which the user has to approve or deny the presented information of Bowen. By providing a user with a countdown timer to respond to confirmation request, a service will predictably be able to free up resources in a faster manner due to time constraints on the user. Additionally, by placing a timer on a user to confirm a predicted review, a system will predictably be able to ensure that reviews are current and relevant.
With respect to claim 7, the combination of Chapman and Bowen discloses all of the limitations of claim 5 as stated above. In addition, Chapman teaches:
Wherein presuming a review includes predicting a review based on the historical data using artificial intelligence or preset rules (See at least paragraphs 15, 22, 24, 25, 47, and 52 which describe predicting a review for a product/service for the user based on historical information of the user and other users, and wherein the prediction is down using machine learning).
With respect to claim 8, Chapman/Bowen discloses all of the limitations of claims 5 and 7 as stated above. In addition, Chapman teaches:
Wherein predicting the review includes determining a rating and a confidence level based on the at least one user interaction and the historical data (See at least paragraphs 15, 22, 24, 25, 27-29, 47, and 52 which describe predicting a review for a product/service for the user based on historical information of the user and other users, wherein the prediction is down using machine learning, and wherein the predicted review including a rating and a confidence level that the user will like the target based on user interactions and historical data).
With respect to claim 9, the combination of Chapman and Bowen discloses all of the limitations of claim 5 as stated above. In addition, Chapman teaches:
Wherein updating the review based on a response of the user to the confirmation request or counter expiration; wherein the response includes: a. Acceptance of the review; b. Rejection with an updated review; c. Rejection; or d. No response (See at least paragraphs 15, 25, 26, 47, 49, 52, and 53 which describe presenting the generated reviews to a user and receiving their approval, disapproval, or edit of the review based on their experience with the product/service, wherein the user profile and review is updated based on the user response).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Chapman and Bowen as applied to claim 5 as stated above, and further in view of Narula.
With respect to claim 6, Chapman/Bowen discloses all of the limitations of claim 5 as stated above. Chapman and Bowen do not explicitly disclose the following, however Narula teaches:
Wherein the review process initiation comprises determining a unique identifier related to the at least user interaction and corresponding entity (See at least paragraphs 83-85 and 87-89 which describe a user requesting a review, wherein the user provides identifiers for the business they wish to review and themselves).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of generating a predicted review for a product/service based on user interactions and historical data, wherein a user is presented with the predicted review and is able to approve/disapprove/edit it based on their own experience, and updating their profile and the reviews based on the response of Chapman, with the system and method of presenting a user for confirmation regarding the output of a CNN, wherein the presentation includes a countdown timer for which the user has to approve or deny the presented information of Bowen, with the system and method of a user requesting a review, wherein the user provides identifiers for the business they wish to review and themselves of Narula. By providing user identity information and business identity information, a system will predictably be able to confirm that the user did in fact utilize the business/service, therefore preventing fraud.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL P HARRINGTON whose telephone number is (571)270-1365. The examiner can normally be reached Monday-Friday 9-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeffrey Zimmerman can be reached at (571)-272-4602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Michael Harrington
Primary Patent Examiner
24 June 2026
Art Unit 3628
/MICHAEL P HARRINGTON/Primary Examiner, Art Unit 3628
Prosecution Insights