Prosecution Insights
Last updated: April 19, 2026
Application No. 18/829,913

PRESENTATION AND CONTROL OF USER INTERACTION WITH A MULTI-TAB USER INTERFACE ELEMENT

Final Rejection §101
Filed
Sep 10, 2024
Examiner
CIRNU, ALEXANDRU
Art Unit
3622
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Capital One Services LLC
OA Round
4 (Final)
43%
Grant Probability
Moderate
5-6
OA Rounds
3y 0m
To Grant
64%
With Interview

Examiner Intelligence

Grants 43% of resolved cases
43%
Career Allow Rate
186 granted / 430 resolved
-8.7% vs TC avg
Strong +21% interview lift
Without
With
+20.8%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
38 currently pending
Career history
468
Total Applications
across all art units

Statute-Specific Performance

§101
46.4%
+6.4% vs TC avg
§103
29.6%
-10.4% vs TC avg
§102
10.9%
-29.1% vs TC avg
§112
9.6%
-30.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 430 resolved cases

Office Action

§101
Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . DETAILED ACTION Status of the Application This action is in response to the Amendment filed on 3/17/2026, and is a Final Office Action. Claims 1, 3-10, 12-22 are pending in the application. 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, 3-10, 12-22 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 1 is directed towards a system, thus meeting the Step 1 eligibility criterion. Claim 1 does recite the abstract concept of a commercial interaction/fundamental economic practice, which has been identified as an abstract idea by the MPEP. The relevant claimed limitations include: identify, based on a user identifier associated with a user account associated with a user, one or more account identifiers associated with the user identifier, wherein each account identifier is associated with one or more categories of a plurality of categories that each represents a type of interaction of one or more interactions associated with the one or more account identifiers / determine, for each category of the plurality of categories, a total category amount / transmit, based on determining the total category amount , user interface data, associated with a multi-tab user interface element for a display/ receiving information indicating a selection of the action button / determine, based on receiving the information indicating the selection of the action button, benefits information associated with the first category and based on geographical information associated with the user device and historical interaction amounts of the user / transmit updated user interface data, associated with the multi-tab user interface element, indicating the benefits information / each tab of the plurality of tabs, corresponding to a category, of the plurality of categories / each tab, in an arrangement of the multi-tab user interface, is arranged in a decreasing order based on the total category amount of the corresponding category/ obtain interaction data associated with a plurality of interactions between the user and one or more third parties / wherein the interaction data includes at least an interaction amount, interaction time, and third party information/ the total category amount is a sum of interaction amounts for a plurality of interactions in a particular category, of the plurality of categories, that occur within a particular time frame / wherein the arrangement of the multi-tab user interface element is dynamically updated based on changes in the interaction data / wherein the multi-tab user interface element is personalized to the user. Claim 1 also recites the abstract concept of a mental concept – i.e. mental process that can be performed in the human mind or using pen/paper, including an observation/evaluation/judgment, which has been identified as an abstract idea by the MPEP: identify, based on a user identifier associated with a user account associated with a user, one or more account identifiers associated with the user identifier, wherein each account identifier is associated with one or more categories of a plurality of categories that each represents a type of interaction of one or more interactions associated with the one or more account identifiers / determine, for each category of the plurality of categories, a total category amount. These claimed limitations, under their broadest reasonable interpretation, cover performance in the human mind but for the recitation of generic computing elements – see below, thus still being in the mental process category. This judicial exception is not integrated into a practical application. Claim 1 includes the additional elements of a user device / multi-tab user interface and displaying data in a multi-tab user interface (‘Multi-tab user interface including a plurality of tabs corresponding to the plurality of categories and associated with benefits information associated with the user account / an action button associated with a first category of the plurality of categories’) , and training/ a machine learning model to analyze/determine data (categorize, using a machine learning model , the plurality of interactions according to the plurality of categories / wherein the machine learning model is a supervised machine learning model and is trained based on the interaction data and categories for an interaction of the plurality of interactions / determine benefits information associated with the first category using the machine learning model). The device/interface represent generic computing elements that perform the claimed limitations. Presenting data in a multi-tab user interface represents insignificant extra-solution activity. Training and using a machine learning model to analyze/determine data does no more than apply or link the use of the recited judicial exception to a particular technological environment/field of use. The additional elements do not , alone or in combination, improve the functioning of the computing device or another technology/technical field, nor do they apply or use the judicial exception in some other meaningful way beyond generally linking its use to a particular technological environment. The claim is directed to an abstract idea. Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception, because as noted above, the claimed computing elements represent generic computing elements; they are recited at a high level of generality. Training and using a machine learning model to analyze/determine data does no more than apply or link the use of the recited judicial exception to a particular technological environment/field of use. Presenting content in a multi-tab user interface represents insignificant extra-solution activity- i.e. it represents a well known and commonly means of presenting content in a digital computing environment, as known to one of ordinary skill in the art at the effective filing date of the invention; Shahrbabaki (20040113948), publication date of June 17, 2004, describes that “another common application navigation structure is the multi-tab interface” – at least para 8. The additional elements do not , alone or in combination, improve the functioning of the computing device or another technology/technical field, nor do they apply or use the judicial exception in some other meaningful way beyond generally linking its use to a particular technological environment. Therefore, Claim 1 does not amount to significantly more than the abstract idea itself. The claim is not patent eligible. Independent Claims 7, 16 are directed towards a method and computer readable medium, thus meeting the Step 1 eligibility criterion; the claims do recite the same abstract idea as Claim 1. Claims 7, 16 perform the claimed limitations using only generic components of a networked computer system. Therefore, claims 7, 16 are directed to an abstract idea without significantly more for the reasons given in the discussion of claim 1. Remaining dependent claims 3-6, 8-10, 12-15, 17-22 further recite and narrow the abstract ideas of independent claims 1/7/16. The claims recite the additional elements of terminals / using a trained machine learning model to analyze/determine data / training and using an unsupervised machine learning model to analyze/determine data. The terminals represent generic computing elements, and are recited at a high level of generality. Training and using a trained machine learning model / an unsupervised machine learning model to analyze/determine data does no more than apply or link the use of the recited judicial exception to a particular technological environment. The additional elements do not, alone or in combination, improve the functioning of the computing device or another technology/technical field, or apply or use the judicial exception in some other meaningful way beyond generally linking its use to a particular technological environment. Therefore, claims 2-6, 8-15, 17-20 do not amount to significantly more than the abstract idea itself. The claims are not patent eligible. The prior art of record does not teach neither singly nor in combination the limitations of claims 1, 3-10, 12-22. The most relevant prior art identified, Shahrbabaki (20040113948), teaches presenting accessed objects in a multi-tabbed interface; however, it lacks the combination of claimed elements of the pending independent claims: identify, based on a user identifier associated with a user account associated with a user, one or more account identifiers associated with the user identifier, wherein each account identifier is associated with one or more categories of a plurality of categories that each represents a type of interaction of one or more interactions associated with the one or more account identifiers; determine, for each category of the plurality of categories, a total category amount; transmit, based on determining the total category amount and to a user device associated with the user, user interface data, associated with a multi-tab user interface element for a display of the user device, including: a plurality of tabs corresponding to the plurality of categories and associated with benefits information associated with the user account, and an action button associated with a first category of the plurality of categories; receive, from the user device, information indicating a selection of the action button; determine, based on receiving the information indicating the selection of the action button, benefits information associated with the first category using a machine model and based on geographical information associated with the user device and historical interaction amounts of the user; and transmit, to the user device, updated user interface data, associated with the multi-tab user interface element, indicating the benefits information. Jitkoff (9110568) teaches presenting tabs of online content , and positioning them according to relative importance of each tab to a user; however, it lacks the above-noted combination of claimed elements of the pending independent claims. When taken as a whole, the claims are not rendered obvious as the available prior art does not suggest or otherwise render obvious the noted features nor does the available prior art suggest or otherwise render obvious further modification of the evidence at hand. Such modifications would require substantial reconstruction relying solely on improper hindsight bias, and thus would not be obvious. Response to Arguments Applicant’s arguments have been fully considered; Applicant argues with substance: Applicant respectfully submits that the Examiner's characterization of the claims reciting "a fundamental economic practice" and "a mental process" is incorrect. For example, Applicant respectfully submits that the claims themselves do not recite a metal process or a certain fundamental economic practice, at least because claim 1 recites a variety of non-human activities and non-mathematical concepts including "one or more processors, coupled to the one or more memories, configured to:" "identify, based on a user identifier associated with a user account associated with a user, one or more account identifiers associated with the user identifier, wherein each account identifier is associated with one or more categories of a plurality of categories that each represents a type of interaction of one or more interactions associated with the one or more account identifiers," "obtain interaction data associated with a plurality of interactions between the user and one or more third parties, wherein the interaction data includes at least an interaction amount, interaction time, and third party information," "categorize, using a machine learning model, the plurality of interactions according to the plurality of categories, wherein the machine learning model is a supervised machine learning model and is trained based on the interaction data and categories for an interaction of the plurality of interactions," "determine, for each category of the plurality of categories, a total category amount, wherein the total category amount is a sum of interaction amounts for a plurality of interactions in a particular category, of the plurality of categories, that occur within a particular time frame," "transmit, based on determining the total category amount and to a user device associated with the user, user interface data, associated with a multi-tab user interface element for a display of the user device, including: a plurality of tabs corresponding to the plurality of categories and associated with benefits information associated with the user account, and an action button associated with a first category of the plurality of categories, wherein each tab, of the plurality of tabs, corresponds to a category, of the plurality of categories, and wherein each tab, in an arrangement of the multi-tab user interface element, is arranged in a decreasing order based on the total category amount of the corresponding category, wherein the arrangement of the multitab user interface element is dynamically updated based on changes in the interaction data, and wherein the multi-tab user interface element is personalized to the user," "receive, from the user device, information indicating a selection of the action button," "determine, based on receiving the information indicating the selection of the action button, benefits information associated with the first category using the machine learning model and based on geographical information associated with the user device and historical interaction amounts of the user," and "transmit, to the user device, updated user interface data, associated with the multi-tab user interface element, indicating the benefits information." (Emphasis added). Accordingly, for at least the reasons provided above, amended claim 1 does not recite a mathematical expression or a mental process. If the Examiner somehow considers claim 1 as reciting an abstract idea (which Applicant does not concede), claim 1 integrates the alleged abstract idea into a practical application. Accordingly, the specification's paragraph [0011] explains that the conventional technological processing fails to provide a streamlined and dynamic manner for users view data across various different categories without navigating through multiple different user interfaces which, in turns, wastes computing resources. The specification at [0021 ], below, explains how a machine learning model is used to determine categories states: In some implementations, the processing system may use a machine learning model to determine the category. For example, the machine learning model may be a supervised machine learning model trained based on the interaction data and/or categories manually input by the user for particular interactions. Additionally, or alternatively, the machine learning model may be an unsupervised machine learning model trained based on one or more clusters of users that have similar interactions and/or demographics (e.g., age range, income range, or sex). Paragraphs [0032] and [0033], below, discuss how the machine learning model uses interaction data to determine the benefit information and dynamically present information to the user through the multi-tab UI elements. Therefore, the present application's invention clearly improves upon conventional functioning of a technological process and the machine learning model improves resource usage. Claim 1 reflects the specification's disclosed improvement in technology by using a machine learning model to categorize interaction data, determine benefits and update the tabs on a multitab user interface. Specifically, claim 1 at least recites to "categorize, using a machine learning model, the plurality of interactions according to the plurality of categories, wherein the machine learning model is a supervised machine learning model and is trained based on the interaction data and categories for an interaction of the plurality of interactions," "transmit, based on determining the total category amount and to a user device associated with the user, user interface data, associated with a multi-tab user interface element for a display of the user device, including: a plurality of tabs corresponding to the plurality of categories and associated with benefits information associated with the user account, and an action button associated with a first category of the plurality of categories, wherein each tab, of the plurality of tabs, corresponds to a category, of the plurality of categories, and wherein each tab, in an arrangement of the multi-tab user interface element, is arranged in a decreasing order based on the total category amount of the corresponding category, wherein the arrangement of the multi-tab user interface element is dynamically updated based on changes in the interaction data, and wherein the multi-tab user interface element is personalized to the user," "determine, based on receiving the information indicating the selection of the action button, benefits information associated with the first category using the machine learning model and based on geographical information associated with the user device and historical interaction amounts of the user," and "transmit, to the user device, updated user interface data, associated with the multi-tab user interface element, indicating the benefits information." (Emphasis added). Accordingly, claim 1 reflects the improvement in categorizing, using a machine learning model, the plurality of interactions according to the plurality of categories, in order to determine benefits information associated with the first category using the machine learning model and based on geographical information associated with the user device and historical interaction amounts of the user to transmit updated user interface data, associated with the multi-tab user interface element, indicating the benefits information . . For at least these reasons, claim 1 integrates any alleged abstract idea into a practical application. Claims 7 and 16 recite similar features and thus integrates any alleged abstract idea into a practical application for similar reasons. Accordingly, Applicant respectfully requests that the Examiner reconsider and withdraw the rejection of claims 1, 3-10, and 12-20 under 35 U.S.C. § 101. New claim 21 depends from independent claim 1, and new claim 22 depends from claim 7. Therefore, claims 21 and 22 are patentable for at least the reasons given above with respect to claims 1 and 7. The pending claims do recite an abstract idea, and the additional elements do not, alone or in combination, integrate the recited abstract idea into a practical application nor do they represent significantly more than the abstract idea itself, as noted above. The claimed invention seeks to, when implemented, at best optimize a business practice/goal: i.e. presenting targeted content/benefits content to users. Presenting targeted content/benefits content to users represents a business practice/goal, not other technology/technical field; thus, improving this practice pertains to a business practice optimization, not to an improvement to other technology/technical field. The claimed multi-tab user interface that is used to implement the claimed invention represents a generic computing element- i.e. a generic user interface; at the effective filing date of the invention, displaying digital data in a multi-tab user interface represents a well known and commonly used means of displaying such data. The claimed invention does not, when implemented, improve the functioning of the computing device itself, or other technology/technical field. There is no technical support/technical evidence in the Spec, including that paras noted by the Applicant, that the claimed invention , when implemented, improves the functioning of the computing device itself or other technology/technical field. See Office Action above for the detailed, reasoned 35 USC 101 analysis. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee 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 ALEXANDRU CIRNU whose telephone number is (571)272-7775. The examiner can normally be reached on M-F 9:00am-5pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Ilana Spar can be reached on (571) 270-7537. The fax phone number for the organization where this application or proceeding is assigned is 571- 273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. Sincerely, /Alexandru Cirnu/ Primary Patent Examiner, Art Unit 3622 3/25/2026
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Prosecution Timeline

Sep 10, 2024
Application Filed
May 20, 2025
Non-Final Rejection — §101
Jul 28, 2025
Interview Requested
Aug 13, 2025
Applicant Interview (Telephonic)
Aug 13, 2025
Examiner Interview Summary
Aug 21, 2025
Response Filed
Sep 03, 2025
Final Rejection — §101
Oct 23, 2025
Interview Requested
Nov 06, 2025
Response after Non-Final Action
Dec 05, 2025
Request for Continued Examination
Dec 16, 2025
Response after Non-Final Action
Dec 16, 2025
Non-Final Rejection — §101
Jan 27, 2026
Interview Requested
Mar 17, 2026
Response Filed
Mar 25, 2026
Final Rejection — §101 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

5-6
Expected OA Rounds
43%
Grant Probability
64%
With Interview (+20.8%)
3y 0m
Median Time to Grant
High
PTA Risk
Based on 430 resolved cases by this examiner. Grant probability derived from career allow rate.

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