DETAILED ACTION
This communication is responsive to Amendment filed 06/12/2026.
Claims 1-20 are pending in this application. In the Amendment, claims 1, 3-5, 8, 11, 13-14, 17 and 20 are amended. This action is made Final.
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 .
Response to Arguments
Applicant's arguments filed 06/12/2026 have been fully considered but they are not persuasive.
Applicant argued that Nouard discusses adjusting weights but only in the context of usage for organizing layouts of UI components (Paragraphs [0048-0050]). By contrast, amended claim 1 distinctly claims, "supplying the switch distance score, the task anchor visibility score, and the customer feelings score to a machine learning model as inputs, … wherein the machine learning model is further trained to apply different weights to the switch distance score, the task anchor visibility score, and the customer feelings score according to least one of a type of the workflow, the type of activity being performed, or levels of context switching..."
The Examiner respectfully disagrees 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). R teaches “supplying the switch distance, the task anchor visibility, and the customer feelings to a machine learning model as inputs, the machine learning model being a model that is trained to learn rules for generating user interface (UI)/user experience (UX) modification suggestions for reducing context-switching for the application based on switch distance, the task anchor visibility, and the customer feelings” (R, para.30, 33, 55-56, 62-65, 96; collected info supplied to generate recommendations using machine learning). Nouard is combined to teach the use of weights (Nouard, para.49, 51, 53, 77, weight reflects type of activity and how often user interacts).
Claim Rejections - 35 USC § 103
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over R et al. (“R”, US 2020/0104148) in view of Warner (US 2008/0229254) in view of Clarke et al. (“Clark”, US 2023/0367472) and further in view of Nouard et al. (“Nouard”, US 2022/0100299).
As per claim 1, R teaches a data processing system comprising:
a processor (R, para.105, Fig.6, processor 604);
a display screen (R, para.104, Fig.6, output device 602/603); and
a memory in communication with the processor, the memory comprising executable instructions that, when executed by the processor (R, para.106-107, Fig.6, memory 608/610), cause the data processing system to perform functions of:
monitoring a workflow executed at least in part by an application on a computing device using a context-switching evaluation system (R, para.20, 30, 36, 42, 44, 52; UI usage measurement system 110 monitors interactions), the workflow including a task anchor associated with a primary context for the workflow and at least one context-switching step in which a current context is switched between the primary context and a secondary context (R, Fig.3, Fig.3A, primary context 305A; Fig.3B-C, secondary context 305B-C; para.66-71, 86, 92, selection of page buttons 310/315/320 switches context);
automatically determining a switch distance for the workflow using a switch distance determination component of the context-switching evaluation system, the switch distance corresponding to a measurement of a distance between a first location corresponding to a location of the task anchor and a second location corresponding to the location of the secondary context of the at least one context-switching step (R, para.32-33, 41, 45, 52, 85-86, interaction data includes navigation to other pages/apps, cursor movements, coordinates of click/tap; Fig.4D, vector paths 460, para.96, seek to reduce superfluous multiple interactions);
automatically determining a task anchor visibility which is indicative of visibility of the task anchor on the display screen during the workflow using a task anchor visibility determination component of the context-switching evaluation system (R, para.34, 41, 70-75, off-screen element not visible);
automatically determining a customer feelings based on user feedback pertaining to at least one of the application and the workflow using a user feelings determination component of the context-switching evaluation system (R, para.33, 41, user accept recommendation);
supplying the switch distance, the task anchor visibility, and the customer feelings to a machine learning model as inputs, the machine learning model being a model that is trained to learn rules for generating user interface (UI)/user experience (UX) modification suggestions for reducing context-switching for the application based on switch distance, the task anchor visibility, and the customer feelings (R, para.30, 33, 55-56, 62-65, 96; collected info supplied to generate recommendations using machine learning); and
generating at least one UI/UX modification suggestion for the application based on at least one of the switch distance using a context-switching insights component of the context-switching evaluation system, the task anchor visibility, and the customer feelings (R, para.31, 35, 97; recommendations to reduce interactions); and
presenting the at least one UI/UX modification suggestion for the application in a user interface of the context-switching evaluation system (R, para.31, 35, 73-75, 97-98; recommendations displayed to reduce interactions).
Although R teaches collecting cursor movements (R, para.15, 45, 52, 86), R does not explicitly teach a switch distance score corresponding to a measurement of a distance a cursor is moved on the display screen between a first location and a second location. Warner teaches a system of calculating cursor movements wherein a switch distance score corresponding to a measurement of a distance a cursor is moved on the display screen between a first location and a second location (Warner, para.63, 92, 98, 123, 150, history of previous cursor movements; distance between start point and current position). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include Warner’s teaching with R’s system in order to reduce large movements.
Additionally, the system of R and Warner does not explicitly teach the visibility score which is indicative of a degree to which the task anchor is obscured on the display screen by the secondary context. Clarke teaches an interface wherein the visibility of elements are based on a visibility score (Clarke, para.598-599, 701-702, threshold amount) which is indicative of a degree to which the task anchor is obscured on the display screen by the secondary context (Clarke, para.598-599, 701-702, threshold amount i.e. degree of notification visible determines manner in which notifications are displayed). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include Clarke’ teaching with the system of R and Warner in order to avoid cluttering of the interface.
Furthermore, the system of R, Warner and Clarke does not teach a feelings score, the user feelings determination component being configured to collect the user feedback by periodically generating prompts for customer satisfaction information pertaining to usage of the application and wherein the machine learning model is further trained to apply different weights to the switch distance score, the task anchor visibility score, and the customer feelings score according to least one of a type of the workflow, the type of activity being performed, or levels of context switching. Nouard teaches a system of modifying an interface wherein the user feedback is collected and associated with a value (Nouard, para.29, 38-39, 47, 53, 55, 67-68, weights) and to collect the user feedback by periodically generating prompts for customer satisfaction information pertaining to usage of the application (Nouard, para.23, 27, 38-44, 67, 70, feedback asking for user satisfaction) and to apply different weights according to least one of a type of the workflow, the type of activity being performed, or levels of context switching (Nouard, para.49, 51, 53, 77, weight reflects type of activity and how often user interacts). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include Nouard’s teaching with the system of R, Warner and Clarke in order to determine efficient usage of space.
As per claim 2, the system of R, Warner, Clarke and Nouard teaches the data processing system of claim 1, wherein the functions further include: modifying a UI/UX interface of the application based on the at least one UI/UX modification suggestion (R, para.31, 35, 97, modify UI based on pattern of interactions).
As per claim 3, the system of R, Warner, Clarke and Nouard teaches the data processing system of claim 1, wherein the workflow includes multiple context-switching steps, each of the multiple context-switching steps including the secondary context (R, Fig.3, Fig.3A, primary context 305A; Fig.3B-C, secondary context 305B-C; para. 32-33, 45, 66-71, 86, 92, selection of page buttons 310/315/320 switches context), wherein a switch distance value is determined for each context-switching step, the switch distance value corresponding to the distance between the task anchor and the location of the secondary context wherein the switch distance score is based on combination of the switch distance value for each of the multiple context-switching steps (Warner, para.63, 92, 98, 123, 150; R, para.62, 94, aggregate interactions; Fig.4D, vector paths 460, para.52, 85-86).
As per claim 4, the system of R, Warner, Clarke and Nouard teaches the data processing system of claim 3, wherein the switch distance value for each of the multiple context-switching steps corresponds to the measurement of the distance between the task anchor and the location of the secondary context for each context-switching step on the display screen (Warner, para.63, 92, 98, 123, 150; R, para.62, 94, aggregate interactions; Fig.4D, vector paths 460, para.52, 85-86).
As per claim 5, the system of R, Warner, Clarke and Nouard teaches the data processing system of claim 1, wherein the workflow includes multiple context-switching steps, wherein a task visibility value is determined for each context-switching step, the task visibility value being indicative of an amount of the task anchor that is visible on the display screen during a context-switching step wherein a task visibility score is based on a combination of the task visibility value for each of the multiple context-switching steps (Clarke, para.598-599, 701-702, threshold amount i.e. degree of notification visible determines manner in which notifications are displayed; R, para.34, 70-75, off-screen element, para.62, 94, aggregate interactions).
As per claim 6, the system of R, Warner, Clarke and Nouard teaches the data processing system of claim 1, wherein the user feedback is collected by periodically prompting users of the application for the customer satisfaction information pertaining to the usage of the application (Nouard, para.29, 38-39, 47, 53, 55, 67-68, prompt for feedback; R, para.33, 40, 64-65, 98, prompt to accept recommendation).
As per claim 7, the system of R, Warner, Clarke and Nouard teaches the data processing system of claim 1, wherein generating the at least one UI/UX modification suggestion for the application based on at least one of the switch distance score, the task anchor visibility score, and the customer feelings score further comprises: generating a separate UI/UX modification suggestion based on each of the switch distance score, the task anchor visibility score, and the customer feelings score (R, para.73, recommendation based on specific usage measurement).
As per claim 8, the system of R, Warner, Clarke and Nouard teaches the data processing system of claim 1, further comprising displaying switch distance information, task visibility information, customer feelings information and the at least one UI/UX modification suggestion on the user interface of the context-switching evaluation system (R, para.76-87, Fig.4A-4D, visualization of interactions; Clarke, para.598-599, 701-702).
As per claim 9, the system of R, Warner, Clarke and Nouard teaches the data processing system of claim 1, wherein the context-switching evaluation system is a local application on the computing device (R, para.28, 112, local application).
As per claim 10, the system of R, Warner, Clarke and Nouard teaches the data processing system of claim 1, wherein the context-switching evaluation system is implemented as a service of a cloud-based service provider that is accessible via a network (R, para.21, 93, 112, cloud-based service).
Claims 11 and 20 are similar in scope to claim 1, and are therefore rejected under similar rationale.
Claim 12 is similar in scope to claim 2, and is therefore rejected under similar rationale.
Claim 13 is similar in scope to claim 3, and is therefore rejected under similar rationale.
Claim 14 is similar in scope to claim 5, and is therefore rejected under similar rationale.
Claim 15 is similar in scope to claim 6, and is therefore rejected under similar rationale.
Claim 16 is similar in scope to claim 7, and is therefore rejected under similar rationale.
Claim 17 is similar in scope to claim 8, and is therefore rejected under similar rationale.
Claim 18 is similar in scope to claim 9, and is therefore rejected under similar rationale.
Claim 19 is similar in scope to claim 10, and is therefore rejected under similar rationale.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Inquiries
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SAJEDA MUHEBBULLAH whose telephone number is (571)272-4065. The examiner can normally be reached Mon-Tue/Thur-Fri 10am-8pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William L Bashore can be reached on 571-272-4088. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/S.M./
Sajeda Muhebbullah Examiner, Art Unit 2174
/WILLIAM L BASHORE/ Supervisory Patent Examiner, Art Unit 2174
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