Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Application
Claims 1, 7-8, 14-15, and 20-29 have been examined in this application.
The filling date of this application number recited above is 24-January-2023. No priority has been claimed in the Application Data Sheet, thus the examination will be undertaken in consideration of the effective filing date as the priority date.
No information disclosure statement (IDS) has been filed to date.
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 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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, 7-8, 14-15, 20-22, 24-25, and 27-28 are rejected under 35 U.S.C. 103 as being unpatentable over Zagat et al. (US 11451639 B1), in view of BARNETT et al. (US 20160019641 A1) in further view of SONG et al. (US 20220309187 A1) and Jones-McFadden et al. (US 20170011351 A1), in view of Jakobsson et al. (US 20220398340 A1), and in view of Bourne (US 20090192702 A1).
As per Claims 1, 8, and 15, Zagat discloses a computer-implemented method implemented for interacting with an authenticated client device of a user, the computer-implemented method comprising:
…
generating and displaying a graphical user interface (GUI) on the authenticated client device, the GUI including a branch employee widget comprising an electronic visual tile that displays encrypted employee profile data relating to the recommended financial institution branch employees (see Figure 2A displaying a user interface presenting data associated with a user profile interface);
launching a scheduling platform and then causing the scheduling platform to display a user-selectable appointment calendar in the branch employee widget (See Figure 2A – 226, as disclosed [Col 23 Lines 58-67] “In at least one example, the user profile interface 156 can include application data 226 associated with one or more relevant applications. The applications can include first-party applications that are associated with an organization of the user associated with the user profile and/or third-party applications that are accessible to users of the communication platform. In the illustrative example, application data 226 associated with a single scheduling application, is presented via the user profile interface 156” and see also Figure 2C – 240, as disclosed [Col 24 Lines 58-63 to Col 25 Lines 28-32] “In the illustrative example of FIG. 2C, in response to receiving an indication of selection of the application data 226, or a link associated therewith, the communication platform causes a presentation of an application data window 240 in association with the user interface 148 … As illustrated in FIG. 2C, the application data window 240 associated with the scheduling application can include selectable options to enable the requesting user 214 to schedule an appointment with the user”);
receiving, in response to user manipulation of the displayed user-selectable appointment calendar, transmission of a user-initiated calendar appointment request with the recommended financial institution branch employee ([Col 4 Lines 61-67] “The communication platform can cause data associated with the third-party scheduling application to be presented via the user profile, such as to enable the first user to schedule a meeting with the second user via the scheduling application without leaving a user profile interface of the communication platform” and see also [Col 25 Lines 52-56] “In various examples, responsive to receiving an indication of selection of a selectable option associated with an open time, the communication platform can send scheduling information to the third-party service provider 108, such as to schedule the meeting between the two users at the open time”);
scheduling, via the scheduling platform in response to receiving transmission of the user-initiated calendar appointment request, a virtual appointment with the recommended financial institution branch employee ([Col 12 Lines 33-39] “For example, the second user can provide information to the communication platform to associate a third-party scheduling application with the second user account of the communication platform. Such an association can facilitate scheduling appointments in association with the third-party scheduling application via a communication platform interface”);
Although Zagat teaches of the system of providing user profile data for scheduling an appointment, the prior art does not seem to explicitly disclose of utilizing machine learning module to provide recommendations based on the user’s location data. However, BARNETT teaches:
receiving, by one or more server computers comprising a sensor module and a machine learning (ML) module, a service request from the authenticated client device for a financial service offered by a financial institution (see Figure 3 – step 302, as disclosed [0034] “A user can initiate an electronic activity at 302. For example, a user can initiate a mortgage application through the website of a bank”);
training, by the one or more server computers, the ML model as a trained ML model via one or more ML algorithms of the ML module based on training user data ([0032] “In some examples, the computing system's physical location recommendation can be at least partially based on machine learning of the user's activities and behaviors, including the user's past behaviors when completing activities at a physical location … This machine learning can be any suitable machine learning implementation, such as a rule-based machine learning algorithm and/or a neural network-based machine learning algorithm”);
transmitting, by the one or more server computers, a request for authorization to detect of a geographic location of the authenticated client device (See Figure 4 – step 402, as disclosed [0044] “In some examples, process 400 can be performed as part of step 306 in FIG. 3. A recommendation for a physical location can be requested at 402. This request can correspond to a user requesting a physical location, or the computing system determining that a physical location recommendation is needed (e.g., similar to step 304 in FIG. 3)”);
causing, by the one or more server computers, the sensor module to detect a current geographic location of the client device (See Figure 4 – step 404, as disclosed [0045] “The computing system can select a physical location at 404. The selected location can be identified in accordance with the examples disclosed above. For example, the selected location can be one of a plurality of locations that can be in general proximity to the user's current location”);
causing, by the one or more server computers, the trained ML model to analyze user behavioral patterns and then determine a frequency of service of the user at a branch location of the financial institution ([0032] “In some examples, the computing system's physical location recommendation can be at least partially based on machine learning of the user's activities and behaviors, including the user's past behaviors when completing activities at a physical location. For example, a machine learning algorithm can learn the physical locations at which the user most often completes activities, and can give those locations more weight in the recommendation determination (i.e., be more likely to recommend those locations as compared with other locations)”);
recommending, by the one or more server computers based on the determination by the trained ML model, a financial institution branch employee at the branch location of the financial institution (See Figure 4 – step 414, as disclosed [0050] “If the selected location does have sufficient resources to complete the user's activity, the computing system can provide the selected location as a recommended physical location to the user at 414. This can include providing address information for the physical location, and any tasks that the user may need to complete at the physical location”);
It would have been obvious to one of ordinary skill in the art at the time of the invention to utilize machine learning to provide recommendations based on user location as in BARNETT in the system executing the method of Zagat with the motivation of offering to improve user experience and efficiency to determine the user’s needs by providing more accurate recommendations as taught by BARNETT over that of Zagat.
Although BARNETT teaches of the system of providing recommendations based on the user’s current location data, the prior art does not seem to explicitly disclose of providing authorization for the user’s location data. However, SONG teaches:
transmitting, by the one or more server computers, a request for authorization to detect a geographic location of the authenticated client device (See Figure 5 which displays an interface asking permission to access device location, or see also [0058] “For example, when continuing accessing the permission to ‘use position’ while executing the permission ‘to use the position’ in a navigation application, the server 108 may determine the use of the permission to ‘use the position’ in the navigation application as the positive evaluation”);
It would have been obvious to one of ordinary skill in the art at the time of the invention to utilize permission to access user location data as in SONG in the system executing the method of BARNETT with the motivation of offering to provide [0012] “improvements in the reliability of evaluation criterion for considering one or more access permissions for an application” as taught by SONG over that of BARNETT.
Although BARNETT teaches of the system of utilizing machine learning to learn user’s behavior data to provide a proper branch location recommendation for the requested service, the prior art does not seem to explicitly disclose of recommending a specific branch employee at the location. However, Jones-McFadden teaches:
causing, by the one or more server computers, the sensor module to detect a current geographic location of the client device (See Figure 3 – step 230, as disclosed [0044] “As illustrated by block 230, the system determines current and potential future locations of the user and compares these with the locations of the one or more specialists” or see also [0066] “As illustrated at block 706, the system continuously analyses the user profile to determine a change in current or potential future locations of the user, reflecting the location dependency. In some embodiments, the steps concerning location dependency are substantially similar to that of the time dependency described above … For example the system may monitor GPS, AR technology, WiFi connectivity of the user device or analyze, in real time, the social media updates of the user to recognize that the user at a location B, wherein location B is the user's new current location”);
…
recommending, by the one or more server computers based on the determination by the trained ML model, a financial institution branch employee at the branch location of the financial institution (See Figure 3 – step 226 and 234, as disclosed [0042] “Next, as illustrated by block 226, the system may identify one or more specialists, advisors or associates to help the user with the user's potential concerns or user intents” and [0047] “Finally, as illustrated in block 234, the system transmits the determined suitable one or more appointments to the user … In some embodiments the transmission includes details associated with the appointment including but not limited to … details associated with the one or more specialists”).
It would have been obvious to one of ordinary skill in the art at the time of the invention to utilize recommending a specific branch employee at the location based on the user’s current location data as in Jones-McFadden in the system executing the method of BARNETT with the motivation of offering to improve user experience and time efficiency by improving the recommendation system as taught by Jones-McFadden over that of BARNETT.
Although Zagat teaches of displaying a user interface comprising user profile data, the prior art does not seem to explicitly disclose that the displayed profile data is encrypted data. However, Jakobsson teaches:
generating and displaying, by the one or more server computers, a graphical user interface (GUI) on the authenticated client device, the GUI including a branch employee widget comprising an electronic visual tile that displays encrypted employee profile data relating to the recommended financial institution branch employees ([Abstract] “updating a user profile, where the user profile comprises at least one characterization associated with the user profile; encrypting the updated user profile and securely storing the encrypted user profile; receiving a request to access the encrypted user profile from a process; determining access permissions of the process; and when the process has sufficient access permissions, decrypting the user profile and providing user profile data to the process”);
It would have been obvious to one of ordinary skill in the art at the time of the invention to utilize encrypted profile data as in Jakobsson in the system executing the method of Zagat with the motivation of offering to improve user privacy and security as taught by Jakobsson over that of Zagat.
Although Zagat teaches of scheduling an appointment on the third-party application calendar, the prior art does not seem to explicitly disclose of synchronizing the appointment to another calendar operating on the device. However, Bourne teaches:
synchronizing, via the scheduling platform, the virtual appointment with another calendar that is operating on the authenticated client device in order to record a designated appointment date and appointment time ([0029] “A user of the mobile device enters an appointment event in his or his PC- or web-based calendar 108. Typically, the event data includes fields for date, time, activity, and location … The PC- or web-based calendar 108 at some point is synchronized to a mobile PIM native calendar 110 … In particular, the calendar module 112 preferably is automatically synchronized to the mobile PIM calendar 110 whenever a new appointment event is added to the calendar 110”).
It would have been obvious to one of ordinary skill in the art at the time of the invention to utilize calendar synchronization as in Bourne in the system executing the method of Zagat with the motivation of offering to improve user experience and time efficiency for utilizing multiple calendars as taught by Bourne over that of Zagat.
As per claims 7, 14, and 20, Zagat teaches the server computing system of claim 1, the computer program product of claim 8, and the computer-implemented method of claim 15, wherein the profile data includes one or more of a digital image, job title, a geographic location, and contact information of the recommended financial institution branch employee ([Col 2 Lines 66-67 to Col 3 Lines 1-5] “The user data can include a name (e.g., full name, username, etc.), contact information (e.g., email address, phone number, etc.), location (e.g., time zone, geographical location, home location, office location, etc.), schedule information (e.g., full-time employee, part-time employee, contractor, etc.), title (e.g., work position, etc.), image (e.g., photograph, GIF, etc.), and the like”).
As per claims 21, 24, and 27 Zagat teaches the computer-implemented method of claim 15, the server computing system of claim 1, and the computer program product of claim 8, wherein the branch employee widget displays one or more search engine entry fields for selection of a new financial institution branch employee by the user ([Col 21 Lines 55-62] “In some examples, the directory interface 218 can provide a means by which the user 214 can quickly and efficiently identify another user of the communication platform. For example, the directory interface 218 can include a search mechanism 220 via which the user 214 can input a name (e.g., username, real name, nickname, etc.), role (e.g., position, title, etc.), team (e.g., group identifier, group name, etc.) associated with another user”).
As per claims 22, 25, and 28, Zagat teaches the computer-implemented method of claim 15, the server computing system of claim 1, and the computer program product of claim 8, further comprising detecting, by the one or more server computers, online communication between the authenticated client device and a second financial institution branch employee ([Col 16 Lines 34-46] “In various examples, the user interface 148 can be configured to present data associated with one or more communication channels, one or more direct messages and, in some examples, one or more workspaces. That is, in some examples, the user interface 148 can present messages sent via one or more communication channels and/or via direct message(s) in a single user interface so that the user (e.g., of the user computing device 104) can access and/or interact with data associated with the multiple channels and/or direct messaging instances that he or she is associated with and/or otherwise communicate with other users associated with the multiple channels and/or direct messaging instances”).
Claims 23, 26, and 29 are rejected under 35 U.S.C. 103 as being unpatentable over Zagat, in view of BARNETT in further view of SONG and Jones-McFadden, in view of Jakobsson, in view of Bourne, and in view of Janssens (US 20140040368 A1).
As per claims 23, 26, and 29, Zagat may not explicitly disclose, but Janssens teaches the computer-implemented method of claim 22, the server computing system of claim 25, and the computer program product of claim 28, further comprising transmitting, by the one or more server computers in response to the detection, a request to the client device to replace the recommended financial institution branch employee with the second financial institution branch employee ([0005] “subsequent to causing, at least in part, the profile information regarding the first matching user to be presented in the first area, causing at least in part profile information regarding a second matching user to replace the profile information of the first matching user in the first area, wherein the profile information of the second matching user is displayed in association with the communication initiation control”).
It would have been obvious to one of ordinary skill in the art at the time of the invention to utilize replacing profiles based on communication initiation control as in Janssens in the system executing the method of Zagat with the motivation of offering to improve the recommendation system to provide adequate profile matching systems as taught by Janssens over that of Zagat.
Response to Arguments
Applicant's arguments, see pages 10 to 14, filed 13-January-2026, with respect to 35 U.S.C. 103 rejection have been fully considered but they are not persuasive. In view of MPEP 2143:
“The Supreme Court in KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007) identified a number of rationales to support a conclusion of obviousness which are consistent with the proper "functional approach" to the determination of obviousness as laid down in Graham. The key to supporting any rejection under 35 U.S.C. 103 is the clear articulation of the reason(s) why the claimed invention would have been obvious. The Supreme Court in KSR noted that the analysis supporting a rejection under 35 U.S.C. 103 should be made explicit. In Ball Aerosol v. Ltd. Brands, 555 F.3d 984, 89 USPQ2d 1870 (Fed. Cir. 2009), the Federal Circuit offered additional instruction as to the need for an explicit analysis. The Federal Circuit explained that the Supreme Court’s requirement for an explicit analysis does not require record evidence of an explicit teaching of a motivation to combine in the prior art
…
The courts have made clear that the teaching, suggestion, or motivation test is flexible and an explicit suggestion to combine the prior art is not necessary. The motivation to combine may be implicit and may be found in the knowledge of one of ordinary skill in the art, or, in some cases, from the nature of the problem to be solved. Id. at 1366, 80 USPQ2d at 1649. "[A]n implicit motivation to combine exists not only when a suggestion may be gleaned from the prior art as a whole, but when the ‘improvement’ is technology-independent and the combination of references results in a product or process that is more desirable, for example because it is stronger, cheaper, cleaner, faster, lighter, smaller, more durable, or more efficient. Because the desire to enhance commercial opportunities by improving a product or process is universal—and even common-sensical—we have held that there exists in these situations a motivation to combine prior art references even absent any hint of suggestion in the references themselves. In such situations, the proper question is whether the ordinary artisan possesses knowledge and skills rendering him capable of combining the prior art references." Id. at 1368, 80 USPQ2d at 1651.”
The prima facie obviousness under 103 has been made as “some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention”, wherein the combination of the references would provide an improved system to teach the claimed invention as a whole. Therefore, the 35 U.S.C. 103 rejection is maintained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Vltavsky et al. (US 10154372 B1) discloses [Col 3 Lines 38-57] “Depending on the purpose of the customer's visit to the physical location 104, the customer may need to access a service specific interface of the application being executed on the user device 112. For example, if the purpose of the visit is to withdraw cash from an ATM, the customer may be able to prestage the ATM transaction through an ATM user interface of the application. If the purpose of the visit is to make a deposit with a teller of the bank, the customer may be able to prestage the teller transaction through a teller user interface of the application. If the purpose of the visit is to open a new account or learn about a specific product offered by the financial institution 102, the user interface may be updated with a real-time list of employees available to assist the customer such that the customer can view employee profiles (e.g., employee characteristics) and set up an appointment with a specific employee at the branch. The financial institution 102 is able to predict the user interface most applicable to the customer's destination based on the location of the user device 112”;
Igarashi et al. (US 20010053694 A1) discloses [0009] “When the user terminal registers with the foreign agent to initiate a communication session, the service profile setting controller retrieves a relevant service profile from the service control database, and it distributes and sets the service profile to the home agent and foreign agent as their initial service profile … In response to this event signal, the service profile updating controller obtains a new service profile from the service control database, and distributes it to the home agent and foreign agent, so that the initial service profile will be replaced with the new service profile”;
THIS ACTION IS MADE FINAL. 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 HENRY H JUNG whose telephone number is (571)270-5018. The examiner can normally be reached Mon - Fri 9:30 - 5:30.
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/HENRY H JUNG/ Examiner, Art Unit 3695
/CHRISTINE M Tran/ Supervisory Patent Examiner, Art Unit 3695
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