DETAILED ACTION
This is a final office action on the merits. The U.S. Patent and Trademark Office (the Office) has received claims 1 – 28 in application 17/696,168.
Claims 1-5, 10, and 20 are canceled.
Claims 6 and 15 are amended.
Claims 6-9, 11-19, and 21-27 are pending and have been examined on the merits.
Notice of Pre-AIA or AIA Status
The present application, filed on or after 16 March 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
103
Applicant's arguments filed 11/12/2025 have been fully considered but they are not persuasive.
Applicant argues Otranen, Cozens, and Hines does not teach “querying one or more data sources using a query to retrieve historical user behavior data…wherein the query is associated with the user data.”
Not persuasive. Hines teaches data sources queried. The system “monitor new subscription requests attributable to an ESU's invitations (Abstract)” and “accessing information stored in a plurality of service specific electronic contact lists of a service user (Claim 17).” Otranan teaches querying against a member database based on received contacts “compare user contacts with a service member database to determine a member status (Abstract).”
Applicant asserts Cozens only mentions machine learning briefly and not a trained machine learning model and no probability.
Not persuasive. Cozens teaches “a machine learning derived decision function (¶ 0045).” The machine learning derived decision functions “define a set of weights…and a decision threshold value (¶ 0045).” The machine learning derived decision functions also “continuingly learn from user responses and adjust the decision function accordingly (¶ 0045).” Cozens uses a threshold (score) framing “score is above the threshold (¶ 0045)” which is a numerical likelihood or decision metric. One of ordinary skilled in the art would have modify Cozen’s machine learning derived decision function with Otranen and Hines because the combined system is already dependent on identifying which users to invite and when to prompt onboarding and Cozens teaches a known technique for data driven classification that improves the accuracy and adaptability of determinations using learned weights and continued learning.
Applicant disagrees the prior art teaches “dynamically determining a customized incentive.”
Hines teaches that the application “may then rank or otherwise rate the ESU based on the ESU's performance in recruiting new users and the service provider may compensate the ESU based on the ranking or rating. The compensation may include monetary compensation, e.g., a reduction of a monthly service bill and/or reward points (¶ 0014).” This shows that Hines teaches a user-specific incentive.
Applicant disagrees the prior art teaches onboarding a second user triggered by an interactive element.
Not persuasive. Otranan teaches generating invitations “directed to non-member user contact entities inviting the non-member user contact entities to join an exemplary online service (¶ 0049).” Hines teaches “sending electronic invitations…inviting them to subscribe (¶ 0016)” which is the onboarding of new users. Cozens teaches an interactive element that the user interacts within.
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.
The factual inquires set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1066), that are applied for establishing a background for determining obviousness under 35 U.S.C. § 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 6-9, 11-19, and 21-27 are rejected under 35 U.S.C. § 103 as being unpatentable over Otranan et al. (US20090276436A1) hereinafter Otranen in view of Cozens et al. (US20140188714A1) hereinafter Cozens and in further view of Hines et al (US20100161377A1) hereinafter Hines.
Regarding Claim 6. Otranen teaches:
A system comprising: one or more processors; and computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
Otranen - . It will be understood that each block, step, or operation of the flowcharts, and combinations of blocks, steps or operations in the flowcharts, can be implemented by various means, such as hardware, firmware, and/or software including one or more computer program code portions, program instructions, or executable program code portions. For example, one or more of the procedures described above may be embodied by computer program code instructions. In this regard, the computer program instructions which embody the procedures described above may be stored by a memory device of the apparatus and executed by a processor in the apparatus (¶ 0061).
receiving, from one or more interactions through an interactive user interface of an application running on an electronic device,
Otranen - receiving user contacts associated with a user in response to an invitation associated with the user (Claim 1). configured to receive user contacts associated with a user. The user contacts may be received from a server, a mobile terminal, or the like (Abstract).
wherein the interactive user interface provides user-specific information about a user, and
Otranen - Any type of data may be synchronized amongst the platforms and made available for access. Types of data may include status information, content, user profile information, shared files (e.g., documents, photos, media content, etc.), user contacts, invitations, service membership information, relationship group information, or the like (¶ 0034).
wherein the electronic device receives user data associated with the user through the one or more interactions;
Otranen - Client application 730 may be a software or hardware application residing and operating on a platform, such as a computer, mobile terminal, or the like, that may be used to interact with the service 700. In some embodiments, the client application 730 may reside and operate on the apparatus 200, the user platforms 245, 250, or the like, and may operate in the same manner as apparatus 200, the user platforms 245, 250, or the like. The client application may be downloaded to and/or installed on the platform. In some embodiments, the client application 730 may be specifically tailored to interact with the service 700. Via the client application 730, the platform, and the user of the platform, may interact with the service 700 to send and receive data, such as user contacts, between the client application 730 and the service 700 (¶ 0039).
querying one or more data sources using a query to retrieve…from the one or more data sources, wherein the query is associated with the user data;
Otranen - The contact comparator 232 may be configured to compare user contacts with a service member database to determine a member status associated with each user contact. Means for comparing user contacts with a service member database may include the processor 205, the contact comparator 232, algorithms for comparing user contacts with a service member database (¶ 0047).
an interactive element,
Otranen invitations may be provided for by the invitation generator 234 (¶ 0049).
wherein an interaction with the interactive element triggers onboarding of a second user onto a program associated with the application and
Otranen - an invitation may state “You have 3 contacts that are already members of this online service, would you like to join?” In other words, invitations may include information regarding who else is a member of the online service and thus, encouraging the non-member to join (¶ 0049).
Otranen does not teach, however Cozens discloses:
…using a trained machine learning model to generate a probability of the user engaging in behavior that is non-compliant according to at least one rule associated with the application;
Cozens - the decision function may be a machine learning derived decision function. In general, machine learning derived decision functions define a set of weights for a set of payment signals and a decision threshold value (¶ 0045).
updating the interactive user interface to output, in association with the application running on the electronic device,
Cozens - an email payment system tracks and updates the status of the payment transaction in the sender and recipient's email message with the payment object. For example, a copy of the email message with the payment object is stored in the sender's stored folder, or a special email payments folder. The initial status in the payment object in the sender's copy of the email will indicate “awaiting action” or another indicator showing action is needed by the recipient. At the same time the payment object in the recipient's copy of the email will indicate that “action is needed” from the recipient. If the recipient accepts the payment, the sender and recipient's status are updated in the payment object of their copy of the email message with the payment object to indicate the payment is “processing.” Upon completion of the payment transaction, the sender and recipient's status in the payment object of the email are updated to “completed.” If the recipient rejects the payment, the sender and recipient's status in the payment object of the email are updated to “declined.” Similar status updates are provided when the original payment object is a payment request. Upon acceptance of the payment request, the status updates follow a similar process as described previously regarding acceptance and rejection of a payment. In certain example embodiments, the status updates are encoded in a hypertext markup language and executed by API calls to the payment processor at regular intervals and/or prior to a request to display the email message with the email payment object. In certain other example embodiments, the payment processor sends push notifications to the email client containing the status updates (¶ 0025).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date to modify Otranen’s contact-based invitation and onboarding system with Cozen’s referral incentive logic to increase user acquisitions and conversions.
The combination of Otranen and Cozens does not disclose, however Hines discloses:
…historical user behavior data corresponding to the user…
Hines - monitor new subscription requests attributable to an ESU's invitations (historical data) (Abstract).
dynamically processing, at least the user data, the historical user behavior data, and additional data corresponding to at least one other user…
Hines - retrieving information identifying prospective service users (PSUs) from respective contact lists; sending invitations to subscribe to the targeted service to the PSUs; monitoring new subscription requests attributable to the invitations; and (Claim 1).
dynamically determining, based on the probability associated with the user, a customized incentive associated with the user that is customized to modify the probability; and
Hines - The number of new users resulting from such invitations may be monitored by the provider of the targeted service or by a third party. The existing users, as well as any new users, may be compensated based on the number of new service requests to encourage further user-driven recruiting efforts. Additional programs or service features can be implemented to encourage participation, minimize service switching and reduce churn. By offering existing users incentives to encourage the enlistment of new users, the disclosed methods may enable an emerging provider to overcome barriers to switching that consumers may otherwise exhibit (¶ 0011).
conveys the customized incentive to the user.
Hines - By offering existing users incentives to encourage the enlistment of new users, the disclosed methods may enable an emerging provider to overcome barriers to switching that consumers may otherwise exhibit. Invitations from friends and peers may alleviate apprehension to switching while simultaneously fostering a user community that reduces subscriber chum. For example, leveraging personal networks of existing users as a base for targeting marketing efforts may provide the foundation for relevant enhancements such as IPTV chat, sharing of recently viewed programs/photos/favorites guides, etc (¶ 0011).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date to modify Otranen’s contact-based invitation/onboarding flow and Cozen’s referral reward program with Hine’s UI-update mechanisms to compute a user-specific risk metric from user and external data.
Regarding Claim 7. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 6, the operations further comprising: analyzing the user data to determine a characteristic associated with the user, wherein dynamically determining the customized incentive is based at least in part on the probability and the characteristic.
Cozens - To initiate a payment request or payment, a sender composes an email to a recipient and indicates an intent to pay the recipient. In certain example embodiments, the intent can be indicated by clicking on a button or other user interface object within the email client. In other example embodiments, the email payment system may analyze the email for payment signals. For example, the email payment system may analyze text in an email for such payment signals as “$” or a phrase such as “I owe you” in the body of the email (¶ 0019).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date to modify Otranen’s contact-based invitation/onboarding flow and Cozen’s referral reward program with Hine’s UI-update mechanisms to compute a user-specific risk metric from user and external data.
Regarding Claim 8. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 6, wherein at least a portion of the user data is received during an onboarding process for onboarding the user to a payment service, and wherein the user data includes at least one of a phone number or an electronic mail address.
Otranen - A user contact may include information for directing communications to a user contact entity (e.g., an individual or other entity). In this regard, information for directing communications to a user contact entity may include a phone number, a mailing address, an email address, a user identifier, a social networking account identifier, or the like. A user may be associated with a list or other grouping of user contacts. The user contacts associated with a user may be representative of the user's friends, family members, business associates, or the like ( ¶ 0041).
Regarding Claim 9. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 6, wherein dynamically determining the customized incentive associated with the user includes analyzing the probability associated with the user using a second machine learning model.
Cozens - or example, signals like a “$” or a phrase like “I owe you” may be used to indicate the email relates to an intent to send payment. In addition, the decision function may be a machine learning derived decision function. In general, machine learning derived decision functions define a set of weights for a set of payment signals and a decision threshold value. If the decision function score is above the threshold value the payment signals detected indicate an intent to send a payment. Machine learning derived decision functions are able to continuingly learn from user responses and adjust the decision function accordingly (¶ 0045).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date to modify Otranen’s contact-based invitation/onboarding flow and Cozen’s referral reward program with Hine’s UI-update mechanisms to compute a user-specific risk metric from user and external data.
Regarding Claim 11. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 6, the operations further comprising: modifying the customized incentive is based at least in part on at least one of: a period of time having lapsed since a time associated with dynamically determining the customized incentive; or receipt of the additional user after the time associated with dynamically determining the customized incentive.
Otranen - In this manner, data modified on one platform may be available to another platform. For example, the modified contact information may be automatically transmitted from the user platform 245 to the contact server 240 or the apparatus 200 for synchronization purposes. As such, the user may later access the modified contact information via user platform 250 and/or a browser (¶ 0035).
Regarding Claim 12. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 6, wherein the operations further comprise: dynamically determining a second customized incentive associated with the user and a third user, and updating the interactive user interface to output, in association with the application running on the electronic device, a second interactive element, wherein an interaction with the second interactive element triggers onboarding of the third user onto the program associated with the application and conveys the second customized incentive to the user.
Otranen - In this manner, data modified on one platform may be available to another platform. For example, the modified contact information may be automatically transmitted from the user platform 245 to the contact server 240 or the apparatus 200 for synchronization purposes. As such, the user may later access the modified contact information via user platform 250 and/or a browser (¶ 0035).
Regarding Claim 13. The combination of Otranen, Cozen, and Hines further discloses:. The system of claim 12, wherein the second customized incentive is different than the customized incentive based at least in part on a first affinity metric associated with the third user being different than a second affinity metric associated with the second user.
Otranen - Similarly, the business that made the application available to the user may also wish to have the user share the application with the user's friends, family, and business contacts. In this manner, the business may gain additional exposure for the application and attract more users. The increased utilization of the application by additional users may result in increased profits for the business from, for example, advertising associated with the application (¶ 0004).
Regarding Claim 14. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 6, wherein the operations further comprise: ranking contacts of the user in a ranked order, the contacts including at least a first contact and a second contact, wherein the second is the first contact; and causing the interactive user interface to present a second interactive element for receiving the customized incentive or a different customized incentive in exchange for the user referring the second contact to the program associated with the application, wherein a relative positioning of the interactive element and the second interactive element in the interactive user interface is based at least in part on the ranked order.
Otranen - Similar to the client application 730, the client web browser application 710 may be a software or hardware application residing and operating on a platform, such as a computer, mobile terminal, or the like, that may be used to interact with the service 700. In this regard, the client web browser application 710 may be a generic network communication application for interacting with various network entities, including the service 700. In some embodiments, the client web browser application 710 may reside and operate on the apparatus 200, the user platforms 245, 250, the computer 250, or the like, and may operate in the same manner as the apparatus 200, the user platforms 245, 250, or the like. Via the client web browser application 710, the platform, and the user of the platform, may interact with the service 700 to send and receive, as well as synchronize, data, such as usage attributes, between the client web browser application 710 and the service 700. The client web browser application 710 may facilitate the gathering and storage of usage attributes for subsequent transmission to the service 700 (¶ 0040).
Regarding Claim 15. Otranen teaches:
A computer-implemented method comprising: receiving, by a computing platform and from one or more interactions through an interactive user interface of an application running on an electronic device,
Otranen - receiving user contacts associated with a user in response to an invitation associated with the user (Claim 1). configured to receive user contacts associated with a user. The user contacts may be received from a server, a mobile terminal, or the like (Abstract).
wherein the interactive user interface provides user-specific information about a user, and
Otranen - Any type of data may be synchronized amongst the platforms and made available for access. Types of data may include status information, content, user profile information, shared files (e.g., documents, photos, media content, etc.), user contacts, invitations, service membership information, relationship group information, or the like (¶ 0034).
wherein the electronic device receives user data associated with the user through the one or more interactions;
Otranen - Client application 730 may be a software or hardware application residing and operating on a platform, such as a computer, mobile terminal, or the like, that may be used to interact with the service 700. In some embodiments, the client application 730 may reside and operate on the apparatus 200, the user platforms 245, 250, or the like, and may operate in the same manner as apparatus 200, the user platforms 245, 250, or the like. The client application may be downloaded to and/or installed on the platform. In some embodiments, the client application 730 may be specifically tailored to interact with the service 700. Via the client application 730, the platform, and the user of the platform, may interact with the service 700 to send and receive data, such as user contacts, between the client application 730 and the service 700 (¶ 0039).
querying one or more data sources using a query to retrieve…from the one or more data sources, wherein the query is associated with the user data;
Otranen - The contact comparator 232 may be configured to compare user contacts with a service member database to determine a member status associated with each user contact. Means for comparing user contacts with a service member database may include the processor 205, the contact comparator 232, algorithms for comparing user contacts with a service member database (¶ 0047).
wherein an interaction with the interactive element triggers onboarding of a second user onto a program associated with the application and
Otranen - an invitation may state “You have 3 contacts that are already members of this online service, would you like to join?” In other words, invitations may include information regarding who else is a member of the online service and thus, encouraging the non-member to join (¶ 0049).
Otranen does not teach, however Cozens discloses:
…using a trained machine learning model, a probability that the user is non-compliant with at least one rule;
Cozens - the decision function may be a machine learning derived decision function. In general, machine learning derived decision functions define a set of weights for a set of payment signals and a decision threshold value (¶ 0045).
updating, by the computing platform, the interactive user interface to output, in association with the application running on the electronic device, an interactive element,
Cozens - an email payment system tracks and updates the status of the payment transaction in the sender and recipient's email message with the payment object. For example, a copy of the email message with the payment object is stored in the sender's stored folder, or a special email payments folder. The initial status in the payment object in the sender's copy of the email will indicate “awaiting action” or another indicator showing action is needed by the recipient. At the same time the payment object in the recipient's copy of the email will indicate that “action is needed” from the recipient. If the recipient accepts the payment, the sender and recipient's status are updated in the payment object of their copy of the email message with the payment object to indicate the payment is “processing.” Upon completion of the payment transaction, the sender and recipient's status in the payment object of the email are updated to “completed.” If the recipient rejects the payment, the sender and recipient's status in the payment object of the email are updated to “declined.” Similar status updates are provided when the original payment object is a payment request. Upon acceptance of the payment request, the status updates follow a similar process as described previously regarding acceptance and rejection of a payment. In certain example embodiments, the status updates are encoded in a hypertext markup language and executed by API calls to the payment processor at regular intervals and/or prior to a request to display the email message with the email payment object. In certain other example embodiments, the payment processor sends push notifications to the email client containing the status updates (¶ 0025).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date to modify Otranen’s contact-based invitation and onboarding system with Cozen’s referral incentive logic to increase user acquisitions and conversions.
The combination of Otranen and Cozens does not disclose, however Hines discloses:
…historical user behavior data corresponding to the user…
Hines - monitor new subscription requests attributable to an ESU's invitations (historical data) (Abstract).
dynamically processing, at least the user data, the historical user behavior data, and additional data corresponding to at least one other user…
Hines - retrieving information identifying prospective service users (PSUs) from respective contact lists; sending invitations to subscribe to the targeted service to the PSUs; monitoring new subscription requests attributable to the invitations; and (Claim 1).
conveys the customized incentive to the user.
Hines - By offering existing users incentives to encourage the enlistment of new users, the disclosed methods may enable an emerging provider to overcome barriers to switching that consumers may otherwise exhibit. Invitations from friends and peers may alleviate apprehension to switching while simultaneously fostering a user community that reduces subscriber chum. For example, leveraging personal networks of existing users as a base for targeting marketing efforts may provide the foundation for relevant enhancements such as IPTV chat, sharing of recently viewed programs/photos/favorites guides, etc (¶ 0011).
dynamically determining, based on the probability associated with the user, a customized incentive associated with the user that is customized to modify the probability; and
Hines - The number of new users resulting from such invitations may be monitored by the provider of the targeted service or by a third party. The existing users, as well as any new users, may be compensated based on the number of new service requests to encourage further user-driven recruiting efforts. Additional programs or service features can be implemented to encourage participation, minimize service switching and reduce churn. By offering existing users incentives to encourage the enlistment of new users, the disclosed methods may enable an emerging provider to overcome barriers to switching that consumers may otherwise exhibit (¶ 0011).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date to modify Otranen’s contact-based invitation/onboarding flow and Cozen’s referral reward program with Hine’s UI-update mechanisms to compute a user-specific risk metric from user and external data.
Regarding Claim 16. The combination of Otranen, Cozen, and Hines further discloses: The computer-implemented method of claim 15, wherein the customized incentive includes at least one of a fiat currency, a gift, a coupon, a discount, loyalty points, a status, a stock, a bond, a mutual fund, an exchange-traded fund (ETF), a cryptocurrency, a non-fungible token (NFT), or a purchase.
Hines - ESU compensation may include a discount on an ESU's monthly bill from the service provider. In still other embodiments, compensation may be in the form of rewards points associated with an affinity program where the reward points are exchangeable for goods and/or services (¶ 0049).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date to modify Otranen’s contact-based invitation/onboarding flow and Cozen’s referral reward program with Hine’s UI-update mechanisms to compute a user-specific risk metric from user and external data.
Regarding Claim 17. The combination of Otranen, Cozen, and Hines further discloses: The computer-implemented method of claim 15, further comprising: dynamically determining a second customized incentive associated with the user and a third user, and updating the interactive user interface to output, in association with the application running on the electronic device, a second interactive element, wherein an interaction with the second interactive element triggers onboarding of the third user onto the program associated with the application and conveys the second customized incentive to the user.
Otranen - Client application 730 may be a software or hardware application residing and operating on a platform, such as a computer, mobile terminal, or the like, that may be used to interact with the service 700. In some embodiments, the client application 730 may reside and operate on the apparatus 200, the user platforms 245, 250, or the like, and may operate in the same manner as apparatus 200, the user platforms 245, 250, or the like. The client application may be downloaded to and/or installed on the platform. In some embodiments, the client application 730 may be specifically tailored to interact with the service 700. Via the client application 730, the platform, and the user of the platform, may interact with the service 700 to send and receive data, such as user contacts, between the client application 730 and the service 700 (¶ 0039).
Regarding Claim 18. The combination of Otranen, Cozen, and Hines further discloses: The computer-implemented method of claim 15, further comprising: ranking contacts of the user in a ranked order, the contacts including at least a first contact and a second contact, wherein the second user is the first contact; and causing the interactive user interface to present a second interactive element for receiving the customized incentive or a different customized incentive in exchange for the user referring the second contact to the program associated with the application, wherein a relative positioning of the interactive element and the second interactive element in the interactive user interface is based at least in part on the ranked order.
Otranen - The mobile terminal 10 may also comprise a user interface including an output device such as a conventional earphone or speaker 24, a ringer 22, a microphone 26, a display 28, and a user input interface, all of which are coupled to the controller 20. The user input interface, which allows the mobile terminal 10 to receive data, may include any of a number of devices allowing the mobile terminal 10 to receive data, such as a keypad 30, a touch display (not shown) or other input device. In embodiments including the keypad 30, the keypad 30 may include the conventional numeric (0-9) and related keys (#, *), and other hard and soft keys used for operating the mobile terminal 10. Alternatively, the keypad 30 may include a conventional QWERTY keypad arrangement. The keypad 30 may also include various soft keys with associated functions. In addition, or alternatively, the mobile terminal 10 may include an interface device such as a joystick or other user input interface (¶ 0024).
Regarding Claim 19. The combination of Otranen, Cozen, and Hines further discloses: The computer-implemented method of claim 15, wherein dynamically determining the customized incentive associated with the user includes analyzing the probability associated with the user using a second machine learning model.
Otranen - an invitation may state “You have 3 contacts that are already members of this online service, would you like to join?” In other words, invitations may include information regarding who else is a member of the online service and thus, encouraging the non-member to join (¶ 0049).
Regarding Claim 21. The combination of Otranen, Cozen, and Hines further discloses: The computer-implemented method of claim 15, further comprising: sending, in response to an interaction with the interactive element, an invitation to the second user; monitoring, in near real-time, invitation data indicating one or more acceptances of one or more invitations, wherein the one or more invitations include the invitation; and determining, based on the customized incentive and the invitation data, an amount of funds to transfer from a program account of the program associated with the application to a user account of the user.
Otranen - an invitation may state “You have 3 contacts that are already members of this online service, would you like to join?” In other words, invitations may include information regarding who else is a member of the online service and thus, encouraging the non-member to join (¶ 0049).
Regarding Claim 22. The combination of Otranen, Cozen, and Hines further discloses: The computer-implemented method of claim 15, wherein at least a portion of the user data is associated with an onboarding process facilitated by the program associated with the application, the trained machine learning model having been trained based on previously collected user data associated with one or more user accounts.
Otranen - A user contact may include information for directing communications to a user contact entity (e.g., an individual or other entity). In this regard, information for directing communications to a user contact entity may include a phone number, a mailing address, an email address, a user identifier, a social networking account identifier, or the like. A user may be associated with a list or other grouping of user contacts. The user contacts associated with a user may be representative of the user's friends, family members, business associates, or the like ( ¶ 0041).
Regarding Claim 23. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 6, the operations further comprising: sending, in response to an interaction with the interactive element, an invitation to the second user; monitoring, in near real-time, invitation data indicating one or more acceptances of one or more invitations, wherein the one or more invitations include the invitation; and determining, based on the customized incentive and the invitation data, an amount of funds to transfer from a program account of the program associated with the application to a user account of the user.
Otranen - an invitation may state “You have 3 contacts that are already members of this online service, would you like to join?” In other words, invitations may include information regarding who else is a member of the online service and thus, encouraging the non-member to join (¶ 0049).
Regarding Claim 24. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 7, wherein the characteristic includes at least one of a geolocation, a spending limit, or an affiliation with an entity.
Otranen - The connectivity program may then allow the mobile terminal 10 to transmit and receive Web content, such as location-based content and/or other web page content, according to a Wireless Application Protocol (WAP), Hypertext Transfer Protocol (HTTP) and/or the like, for example (¶ 0023).
Regarding Claim 25. The system of claim 6, wherein the user data includes at least one of a phone number, an electronic mail address, an Internet Protocol address, a geolocation, a payment card number, a bank account number, a personal name of the user, or one or more contacts of the user.
Otranen - A user contact may include information for directing communications to a user contact entity (e.g., an individual or other entity). In this regard, information for directing communications to a user contact entity may include a phone number, a mailing address, an email address, a user identifier, a social networking account identifier, or the like. A user may be associated with a list or other grouping of user contacts. The user contacts associated with a user may be representative of the user's friends, family members, business associates, or the like (¶ 0041).
Regarding Claim 26. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 6, wherein at least a portion of the user data is associated with an onboarding process facilitated by the program associated with the application, the trained machine learning model having been trained based on previously collected user data associated with one or more user accounts.
Cozens - At block 310, the email payment module 125 analyzes the email composition for one or more payment signals. A payment signal indicates the intent of the sender to send a payment to a recipient. In certain example embodiments, the payment signals may be defined by a decision function stored in the email payment module 125. The decision function may comprise a set of pre-defined payment signals. For example, signals like a “$” or a phrase like “I owe you” may be used to indicate the email relates to an intent to send payment. In addition, the decision function may be a machine learning derived decision function. In general, machine learning derived decision functions define a set of weights for a set of payment signals and a decision threshold value. If the decision function score is above the threshold value the payment signals detected indicate an intent to send a payment. Machine learning derived decision functions are able to continuingly learn from user responses and adjust the decision function accordingly (¶ 0045).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date to modify Otranen’s contact-based invitation/onboarding flow and Cozen’s referral reward program with Hine’s UI-update mechanisms to compute a user-specific risk metric from user and external data.
Regarding Claim 27. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 26, wherein the previously collected user data includes at least one of an indication of one or more types of networks used during the onboarding process, an indication of one or more versions of the application used during the onboarding process, or an indication of one or more contacts for which a respective phone number is found during the onboarding process.
Otranen - A user contact may include information for directing communications to a user contact entity (e.g., an individual or other entity). In this regard, information for directing communications to a user contact entity may include a phone number, a mailing address, an email address, a user identifier, a social networking account identifier, or the like. A user may be associated with a list or other grouping of user contacts. The user contacts associated with a user may be representative of the user's friends, family members, business associates, or the like (¶ 0041).
Regarding Claim 28. The combination of Otranen, Cozen, and Hines further discloses: The system of claim 6, wherein the user-specific information includes a prior probability that the user is non-compliant with the at least one rule at a time before receipt of the one or more interactions, and wherein dynamically calculating the probability includes updating the prior probability based on the additional data to generate the probability.
Hines - Residential gateway 120, set top box 110, and display 108 cooperate to provide IPTV services or another form of multimedia content delivery service 105-3 to household 102. Residential gateway 120 may include elements of a conventional DSL modem combined with an access point/router that supports an IP compliant local area network 111 in household 102. Residential gateway 120 may further include wireless access point functionality to enable a wireless extension of local area network 111. Local area network 111 may be compliant with an industry standard network protocol including, for example, any of the IEEE 802-family of standards (¶ 0021).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date to modify Otranen’s contact-based invitation/onboarding flow and Cozen’s referral reward program with Hine’s UI-update mechanisms to compute a user-specific risk metric from user and external data.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Canetto et al. (US20120215604A1) - A system and method to enable an account owner, such as a user of a pre-paid card, to invite another person to become a user of a pre-paid card. The account owner may find a person to “invite” based on the owner's email, contact list, social network contacts, or another suitable source of data. If the person receiving the invitation to apply for and open a pre-paid account opens such an account, then the person sending the invitation may receive an award or reward. In some cases, the person receiving the invitation may also receive an award or reward. The amount of the award or reward may depend on one or more factors, including the number of times the new account owner loads their pre-paid card, the number of transactions that the new account owner conducts using the pre-paid card, etc.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/C.C.S./Examiner, Art Unit 3698
/PATRICK MCATEE/Supervisory Patent Examiner, Art Unit 3698