DETAILED ACTION
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 .
This communication is in response to the amendments filed on 03/20/2026. Claims 1-17, and 19-21 are currently pending in the application.
Response to Arguments
Applicant’s arguments with respect to claims 1, 10, and 17 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 5-8, 10, 14-17, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over USPGPub. No. 20230409650 to KUMAR et al. (hereinafter KUMAR) in view of US. Pat. No. 10108333 to Abrahams et al. (hereinafter Abrahams).
Regarding claim 1, KUMAR discloses a system comprising, (abstract, “The personalization service and system…”):
a memory to store specific computer-executable instructions (¶0088, “computer-readable storage media may include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules, or other data. For example, computer-readable media includes, but is not limited to, RAM, ROM, EPROM (erasable programmable read only memory)…”);
a processor in communication with the memory wherein the processor executes the specific computer-executable instructions (¶0116, “one or more non-transitory computer-readable memory devices storing instructions which, when executed by one or more processors disposed in a cloud-based computing device, cause the computing device to:...”) to at least:
receive, from a first user system corresponding to a first user, a first request comprising permission to access third party user data (¶0114, “…receive user inputs at the UI to use the personalization application to control modifications to the persona based on collective learning implemented across the online applications (third party dada).”);
in response to receiving the first request, access, via an ingestion service electronically connected to one or more third party databases, third party user data corresponding to the first user, wherein the ingestion service includes data corresponding to online behavior of the first user (¶0031, “Content experience applications can create user profiles based on a customer/user dataset that may include basic information such as demographic and location data to establish account identities for the users (i.e., who they are). The user profile is then typically adapted to a user based on observations of user behaviors while using the content experience applications (i.e., what they are doing). Applications may also utilize data from external sources to supplement identity and behavior data when creating and adapting user profiles.”);
identify and access, from the memory, a first domain persona corresponding to the first user, wherein the first domain persona includes an indication of a preference of the first user with respect to the first domain (¶0079, “Block 1805 comprises receiving a user selection of a persona, in which the persona provides an abstracted representation of the user to the plurality of online applications and to which the user experiences are responsively delivered for rendering on the computing device…”),
identify and access, via the ingestion service and from one or more third party databases, a first subset of data that is determined to be relevant or indicative of the preference of the first user (¶0051, “…collecting context data may include using computing device sensors, monitoring user behaviors and interactions with the device and applications, accessing external data sources and systems, and the like.”);
generate an insight based at least in part on the first subset of data (¶0079, “… Block 1810 comprises storing data associated with the persona in a datastore. Block 1815 comprises determining a context pertaining to the delivery of user experiences by the online applications to the computing device responsively to the persona.”); and
electronically transmit at least one portion of the insight to a data fusion system that is configured to:
generate an updated first domain persona based at least in part on the at least one portion of the insight (¶0080, “Block 1820 comprises revising the persona data in the datastore based on the context determination to update the persona. Block 1825 comprises sending the revised persona data for the updated persona to the plurality of online services for delivery of user experiences responsively to the updated persona.”).
However, KUMAR does not explicitly disclose a request comprises a first domain
wherein the insight comprises a conclusion regarding the preference of the first user with respect to the first domain;
access request to third party user data and a first domain
Abrahams discloses generate insights an insight based at least in part on the first subset of data, wherein the insight comprises a conclusion regarding the preference of the first user with respect to the first domain (Coln. 2, lines 5-28, “…the storage device containing program code configured to be run by the processor via the memory to implement a method for inferring insights from enhanced user input comprising:
the system accessing information that characterizes a user, wherein the information is selected from a group comprising: a unique identifier of the user, a domain of interest, and a user-defined personal preference… the system identifying, as a function of the enhanced scribble data, an insight related to the user.”), (Coln. 9, lines 28-35, “In some embodiments, a user may be associated with multiple domains. In the above case, for example, a second, distinct, domain “Vegetarian/Budget-priced” associated with the user, the scribble device, or the scribble itself might provide further context that allows the system to interpret the user's scribble as a request to retrieve a menu of a New York City Thai restaurant that includes low-priced vegetarian dishes”), (Claim 9, “… the non-transitory computer-readable storage medium containing program code configured to be run by the processor via the memory to implement a method for inferring insights from enhanced user input comprising: accessing, by the computerized communications system, information that characterizes a user, wherein the information that characterizes the user is selected from the group consisting of: a unique identifier of the user, a domain of interest, and a user-defined personal preference”);
access request to third party user data and a first domain (Coln. 9, lines 28-35, “In some embodiments, a user may be associated with multiple domains. In the above case, for example, a second, distinct, domain “Vegetarian/Budget-priced” associated with the user, the scribble device, or the scribble itself might provide further context that allows the system to interpret the user's scribble as a request to retrieve a menu of a New York City Thai restaurant that includes low-priced vegetarian dishes”), (Coln. 12, lines 51-67, “…The system might then store all or part of this data in an third-party airline-aggregating database, in a record format that is compatible with the database, and request that a flight-reservation system associated with the database recommend flights to the user that satisfy all the criteria described above”)
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant claimed invention to modify the system of KUMAR to include insight that comprises a conclusion regarding the preference of the first user with respect to the first domain as disclosed by Abraham and be motivated in doing so in order to eliminate a guesswork by translating raw data into actionable knowledge and aligning offerings with specific needs. It also enables the delivery of tailored content, recommendations, and services that directly appeal to the user.
Regarding claim 10, KUMAR discloses a computer-implemented method (¶0007, FIG. 1) comprising:
receiving, from a first user system corresponding to a first user, a first request (¶0114, “…receive user inputs at the UI to use the personalization application to control modifications to the persona based on collective learning implemented across the online applications (third party dada).”);
in response to receiving the first request, accessing, via an ingestion service electronically connected to one or more third party databases, third party user data corresponding to the first user, wherein the ingestion service includes data corresponding to online behavior of the first user (¶0031, “Content experience applications can create user profiles based on a customer/user dataset that may include basic information such as demographic and location data to establish account identities for the users (i.e., who they are). The user profile is then typically adapted to a user based on observations of user behaviors while using the content experience applications (i.e., what they are doing). Applications may also utilize data from external sources to supplement identity and behavior data when creating and adapting user profiles.”);
identifying and accessing, from one or more databases, a first domain persona corresponding to the first user, wherein the first domain persona includes an indication of a preference of the first user with respect to the first domain (¶0079, “Block 1805 comprises receiving a user selection of a persona, in which the persona provides an abstracted representation of the user to the plurality of online applications and to which the user experiences are responsively delivered for rendering on the computing device…”),
identifying and accessing, via the ingestion service and from one or more third party databases, a first subset of data that is determined to be relevant or indicative of the preference of the first user (¶0051, “…collecting context data may include using computing device sensors, monitoring user behaviors and interactions with the device and applications, accessing external data sources and systems, and the like.”);
generating an insight based at least in part on the first subset of data (¶0079, “… Block 1810 comprises storing data associated with the persona in a datastore. Block 1815 comprises determining a context pertaining to the delivery of user experiences by the online applications to the computing device responsively to the persona.”); and
electronically transmitting at least one portion of the insight to a data fusion system that is configured to:
generate an updated first domain persona based at least in part on the at least one portion of the insight (¶0080, “Block 1820 comprises revising the persona data in the datastore based on the context determination to update the persona. Block 1825 comprises sending the revised persona data for the updated persona to the plurality of online services for delivery of user experiences responsively to the updated persona.”).
However, KUMAR does not explicitly disclose a request comprises a first domain
wherein the insight comprises a conclusion regarding the preference of the first user with respect to the first domain;
access request to third party user data and a first domain
Abrahams discloses generate insights an insight based at least in part on the first subset of data, wherein the insight comprises a conclusion regarding the preference of the first user with respect to the first domain (Coln. 2, lines 5-28, “…the storage device containing program code configured to be run by the processor via the memory to implement a method for inferring insights from enhanced user input comprising:
the system accessing information that characterizes a user, wherein the information is selected from a group comprising: a unique identifier of the user, a domain of interest, and a user-defined personal preference… the system identifying, as a function of the enhanced scribble data, an insight related to the user.”), (Coln. 9, lines 28-35, “In some embodiments, a user may be associated with multiple domains. In the above case, for example, a second, distinct, domain “Vegetarian/Budget-priced” associated with the user, the scribble device, or the scribble itself might provide further context that allows the system to interpret the user's scribble as a request to retrieve a menu of a New York City Thai restaurant that includes low-priced vegetarian dishes”), (Claim 9, “… the non-transitory computer-readable storage medium containing program code configured to be run by the processor via the memory to implement a method for inferring insights from enhanced user input comprising: accessing, by the computerized communications system, information that characterizes a user, wherein the information that characterizes the user is selected from the group consisting of: a unique identifier of the user, a domain of interest, and a user-defined personal preference”);
access request to third party user data and a first domain (Coln. 9, lines 28-35, “In some embodiments, a user may be associated with multiple domains. In the above case, for example, a second, distinct, domain “Vegetarian/Budget-priced” associated with the user, the scribble device, or the scribble itself might provide further context that allows the system to interpret the user's scribble as a request to retrieve a menu of a New York City Thai restaurant that includes low-priced vegetarian dishes”), (Coln. 12, lines 51-67, “…The system might then store all or part of this data in an third-party airline-aggregating database, in a record format that is compatible with the database, and request that a flight-reservation system associated with the database recommend flights to the user that satisfy all the criteria described above”)
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant claimed invention to modify the system of KUMAR to include insight that comprises a conclusion regarding the preference of the first user with respect to the first domain as disclosed by Abraham and be motivated in doing so in order to eliminate a guesswork by translating raw data into actionable knowledge and aligning offerings with specific needs. It also enables the delivery of tailored content, recommendations, and services that directly appeal to the user.
Regarding claim 17, KUMAR discloses a non-transitory computer-readable medium storing instructions that, when executed, by a processor of a computing system cause the computing system to perform operations (¶0114, “…one or more non-transitory computer-readable memory devices storing instructions which, when executed by the one or more processors, cause the computing device to…”) comprising:
receiving, from a first user system corresponding to a first user, a first request (¶0114, “…receive user inputs at the UI to use the personalization application to control modifications to the persona based on collective learning implemented across the online applications (third party dada).”);
in response to receiving the first request, accessing, via an ingestion service electronically connected to one or more third party databases, third party user data corresponding to the first user, wherein the ingestion service includes data corresponding to online behavior of the first user (¶0031, “Content experience applications can create user profiles based on a customer/user dataset that may include basic information such as demographic and location data to establish account identities for the users (i.e., who they are). The user profile is then typically adapted to a user based on observations of user behaviors while using the content experience applications (i.e., what they are doing). Applications may also utilize data from external sources to supplement identity and behavior data when creating and adapting user profiles.”);
identifying and accessing, from one or more databases, a first domain persona corresponding to the first user, wherein the first domain persona includes an indication of a preference of the first user with respect to the first domain (¶0079, “Block 1805 comprises receiving a user selection of a persona, in which the persona provides an abstracted representation of the user to the plurality of online applications and to which the user experiences are responsively delivered for rendering on the computing device…”),
identifying and accessing, via the ingestion service and from one or more third party databases, a first subset of data that is determined to be relevant or indicative of the preference of the first user (¶0051, “…collecting context data may include using computing device sensors, monitoring user behaviors and interactions with the device and applications, accessing external data sources and systems, and the like.”);
generating an insight based at least in part on the first subset of data (¶0079, “… Block 1810 comprises storing data associated with the persona in a datastore. Block 1815 comprises determining a context pertaining to the delivery of user experiences by the online applications to the computing device responsively to the persona.”); and
electronically transmitting at least one portion of the insight to a data fusion system that is configured to:
generate an updated first domain persona based at least in part on the at least one portion of the insight (¶0080, “Block 1820 comprises revising the persona data in the datastore based on the context determination to update the persona. Block 1825 comprises sending the revised persona data for the updated persona to the plurality of online services for delivery of user experiences responsively to the updated persona.”).
However, KUMAR does not explicitly disclose a request comprises a first domain
wherein the insight comprises a conclusion regarding the preference of the first user with respect to the first domain;
access request to third party user data and a first domain
Abrahams discloses generate insights an insight based at least in part on the first subset of data, wherein the insight comprises a conclusion regarding the preference of the first user with respect to the first domain (Coln. 2, lines 5-28, “…the storage device containing program code configured to be run by the processor via the memory to implement a method for inferring insights from enhanced user input comprising:
the system accessing information that characterizes a user, wherein the information is selected from a group comprising: a unique identifier of the user, a domain of interest, and a user-defined personal preference… the system identifying, as a function of the enhanced scribble data, an insight related to the user.”), (Coln. 9, lines 28-35, “In some embodiments, a user may be associated with multiple domains. In the above case, for example, a second, distinct, domain “Vegetarian/Budget-priced” associated with the user, the scribble device, or the scribble itself might provide further context that allows the system to interpret the user's scribble as a request to retrieve a menu of a New York City Thai restaurant that includes low-priced vegetarian dishes”), (Claim 9, “… the non-transitory computer-readable storage medium containing program code configured to be run by the processor via the memory to implement a method for inferring insights from enhanced user input comprising: accessing, by the computerized communications system, information that characterizes a user, wherein the information that characterizes the user is selected from the group consisting of: a unique identifier of the user, a domain of interest, and a user-defined personal preference”);
access request to third party user data and a first domain (Coln. 9, lines 28-35, “In some embodiments, a user may be associated with multiple domains. In the above case, for example, a second, distinct, domain “Vegetarian/Budget-priced” associated with the user, the scribble device, or the scribble itself might provide further context that allows the system to interpret the user's scribble as a request to retrieve a menu of a New York City Thai restaurant that includes low-priced vegetarian dishes”), (Coln. 12, lines 51-67, “…The system might then store all or part of this data in an third-party airline-aggregating database, in a record format that is compatible with the database, and request that a flight-reservation system associated with the database recommend flights to the user that satisfy all the criteria described above”)
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant claimed invention to modify the system of KUMAR to include insight that comprises a conclusion regarding the preference of the first user with respect to the first domain as disclosed by Abraham and be motivated in doing so in order to eliminate a guesswork by translating raw data into actionable knowledge and aligning offerings with specific needs. It also enables the delivery of tailored content, recommendations, and services that directly appeal to the user.
Regarding claim 5, KUMAR in view of Abrahams discloses the system of Claim 1.
KUMAR further discloses wherein the first domain persona includes at least one of: first information determined to be relevant to the preference of the first user or the insight that is generated based at least in part on the first information (¶0001, “…A user profile may be built and developed based on information explicitly provided by a user (e.g., user preferences) as well as information that may be obtained by observing interactions with the online services and applications (e.g., user behaviors)...”), (¶0069, “… For initial persona creation, the user may specify preferences 1615 using suitable UI elements and controls such as menu systems and forms…”), (¶0031, “… The user profile is then typically adapted to a user based on observations of user behaviors while using the content experience applications (i.e., what they are doing). Applications may also utilize data from external sources to supplement identity and behavior data when creating and adapting user profiles.”). See also ¶0051 and ¶0113.
Regarding claim 14, KUMAR in view of Abrahams discloses the computer-implemented method of Claim 10.
KUMAR further discloses wherein the first domain persona includes at least one of:
first information determined to be relevant to the preference of the first user or the insight that is generated based at least in part on the first information (¶0001, “…A user profile may be built and developed based on information explicitly provided by a user (e.g., user preferences) as well as information that may be obtained by observing interactions with the online services and applications (e.g., user behaviors)...”), (¶0069, “… For initial persona creation, the user may specify preferences 1615 using suitable UI elements and controls such as menu systems and forms…”), (¶0031, “… The user profile is then typically adapted to a user based on observations of user behaviors while using the content experience applications (i.e., what they are doing). Applications may also utilize data from external sources to supplement identity and behavior data when creating and adapting user profiles.”). See also ¶0051 and ¶0113.
Regarding claim 21, KUMAR in view of Abrahams discloses the non-transitory computer-readable medium of claim 17.
KUMAR further discloses wherein the first domain persona includes at least one of:
first information determined to be relevant to the preference of the first user or the insight that is generated based at least in part on the first information (¶0001, “…A user profile may be built and developed based on information explicitly provided by a user (e.g., user preferences) as well as information that may be obtained by observing interactions with the online services and applications (e.g., user behaviors)...”), (¶0069, “… For initial persona creation, the user may specify preferences 1615 using suitable UI elements and controls such as menu systems and forms…”), (¶0031, “… The user profile is then typically adapted to a user based on observations of user behaviors while using the content experience applications (i.e., what they are doing). Applications may also utilize data from external sources to supplement identity and behavior data when creating and adapting user profiles.”). See also ¶0051 and ¶0113.
Regarding claim 6, KUMAR in view of Abrahams discloses the system of Claim 1.
KUMAR further discloses wherein to identify and access, from the memory, the first domain persona corresponding to the first user, the processor executes further specific computer- executable instructions to at least:
determine that the first domain persona exists (¶0073, “… suitable controls can be exposed by the application to allow the user to impose variations on an existing persona or preset persona template and/or combine personas…”); and
access the first domain persona (¶0043, “The network 125 may utilize portions of the Internet 130 or include interfaces that support a connection to the Internet so that the computing devices 110 can access content and render user experiences provided by various remote or cloud-based applications 115 and websites 120. The applications and websites can support a diversity of features, services, and user experiences such as social networking, content experiences, mapping, news and information, entertainment, travel, productivity, finance, etc...”), (¶0083, “a request is received at the personalization service from the online application to access user-selected parameters for a persona associated with the user. At block 2020, in response to consent received from the user, access by the online application to at least a subset of user-selected parameters for the persona is provided from the personalization service.”).
Regarding claim 15, KUMAR in view of Abrahams discloses the computer-implemented method of Claim 10.
KUMAR further discloses wherein identifying and accessing, from the one or more databases, the first domain persona corresponding to the first user, further comprises:
determining that the first domain persona exists (¶0073, “… suitable controls can be exposed by the application to allow the user to impose variations on an existing persona or preset persona template and/or combine personas…”); and
accessing the first domain persona (¶0043, “The network 125 may utilize portions of the Internet 130 or include interfaces that support a connection to the Internet so that the computing devices 110 can access content and render user experiences provided by various remote or cloud-based applications 115 and websites 120. The applications and websites can support a diversity of features, services, and user experiences such as social networking, content experiences, mapping, news and information, entertainment, travel, productivity, finance, etc...”), (¶0083, “a request is received at the personalization service from the online application to access user-selected parameters for a persona associated with the user. At block 2020, in response to consent received from the user, access by the online application to at least a subset of user-selected parameters for the persona is provided from the personalization service.”).
Regarding claim 7, KUMAR in view of Abrahams discloses the system of Claim 1.
KUMAR further discloses wherein to identify and access, from the memory, the first domain persona corresponding to the first user, the processor executes further specific computer- executable instructions to at least:
determine that the first domain persona does not exist (¶0069, FIG. 16, “An illustrative persona creation function 1605 of the personalization application 1405 (FIG. 14) is shown in FIG. 16. The persona creation function may provide different options including selecting from among persona recommendations 1610. For initial persona creation, the user may specify preferences 1615 using suitable UI elements and controls such as menu systems and forms…”, wherein there will be no need to create initial persona if it exists);
generate the first domain persona including a specification of the first user and a specification of the first domain (¶0069-¶0070, “… For initial persona creation, the user may specify preferences 1615 using suitable UI elements and controls such as menu systems and forms. The personalization application can also be configured to offer a questionnaire 1620 to the user, such as a quiz or survey, to help identify appropriate personalization parameters…”); and
access the first domain persona (¶0043, “The network 125 may utilize portions of the Internet 130 or include interfaces that support a connection to the Internet so that the computing devices 110 can access content and render user experiences provided by various remote or cloud-based applications 115 and websites 120. The applications and websites can support a diversity of features, services, and user experiences such as social networking, content experiences, mapping, news and information, entertainment, travel, productivity, finance, etc...”), (¶0083, “a request is received at the personalization service from the online application to access user-selected parameters for a persona associated with the user. At block 2020, in response to consent received from the user, access by the online application to at least a subset of user-selected parameters for the persona is provided from the personalization service.”).
Regarding claim 16, KUMAR in view of Abrahams discloses the computer-implemented method of Claim 10.
KUMAR further discloses wherein identifying and accessing, from the one or more databases, the first domain persona corresponding to the first user, further comprises:
determining that the first domain persona does not exist (¶0069, FIG. 16, “An illustrative persona creation function 1605 of the personalization application 1405 (FIG. 14) is shown in FIG. 16. The persona creation function may provide different options including selecting from among persona recommendations 1610. For initial persona creation, the user may specify preferences 1615 using suitable UI elements and controls such as menu systems and forms…”, wherein there will be no need to create initial persona if it exists);
generating the first domain persona including a specification of the first user and a specification of the first domain (¶0069-¶0070, “… For initial persona creation, the user may specify preferences 1615 using suitable UI elements and controls such as menu systems and forms. The personalization application can also be configured to offer a questionnaire 1620 to the user, such as a quiz or survey, to help identify appropriate personalization parameters…”);; and
accessing the first domain persona (¶0043, “The network 125 may utilize portions of the Internet 130 or include interfaces that support a connection to the Internet so that the computing devices 110 can access content and render user experiences provided by various remote or cloud-based applications 115 and websites 120. The applications and websites can support a diversity of features, services, and user experiences such as social networking, content experiences, mapping, news and information, entertainment, travel, productivity, finance, etc...”), (¶0083, “a request is received at the personalization service from the online application to access user-selected parameters for a persona associated with the user. At block 2020, in response to consent received from the user, access by the online application to at least a subset of user-selected parameters for the persona is provided from the personalization service.”).
Regarding claim 8, KUMAR in view of Abrahams discloses the system of Claim 1.
KUMAR further discloses wherein the first domain is travel (¶0113, “… the method further comprises synchronizing the updated persona to each of a plurality of different computing devices associated with the user. In another example, the user experiences are associated with one or more of social networking, content experiences, mapping, news and information, entertainment, travel, productivity, or finance applications.”), see also ¶0043.
Claims 2 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over USPGPub. No. 20230409650 to KUMAR et al. (hereinafter KUMAR) in view of in view of US. Pat. No. 10108333 to Abrahams et al. (hereinafter Abrahams) and further in view of PGPub. No. 20130339186 to French et al. (hereinafter French).
Regarding claim 2, KUMAR in view of Abrahams discloses the system of Claim 1.
However, KUMAR in view of Abraham does not explicitly disclose wherein the processor executes further specific computer-executable instructions to at least implement a fraud detection service to determine that a likelihood of fraud with respect to the first request is below a specified threshold.
French discloses wherein the processor executes further specific computer- executable instructions to at least implement a fraud detection service to determine that a likelihood of fraud with respect to the first request is below a specified threshold (¶0074, “…if the fraud score for the bank account number of the event organizer is less than a threshold fraud score, then fraud detection system 160 may approve the request to pay out funds. Event management system 170 may then facilitate the transfer of the requested fund to the event organizer Although this disclosure describes fraud detection system 160 performing particular actions based on identifying an event parameter associated with fraud, this disclosure contemplates any suitable actions based on identifying an event parameter associated with fraud...”).
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant claimed invention to modify the system of KUMAR and Abrahams to include access request likelihood score below a threshold as disclosed by French and be motivated in doing so in order to approve and facilitate the transfer the requested fund to the event organizer-French ¶0074 in parts.
Regarding claim 11, KUMAR in view of Abrahams discloses the computer-implemented method of Claim 10.
However, KUMAR in view of Abrahams does not explicitly disclose further comprising implementing a fraud detection service to determine that a likelihood of fraud with respect to the first request is below a specified threshold.
French discloses further comprising implementing a fraud detection service to determine that a likelihood of fraud with respect to the first request is below a specified threshold (¶0074, “…if the fraud score for the bank account number of the event organizer is less than a threshold fraud score, then fraud detection system 160 may approve the request to pay out funds. Event management system 170 may then facilitate the transfer of the requested fund to the event organizer Although this disclosure describes fraud detection system 160 performing particular actions based on identifying an event parameter associated with fraud, this disclosure contemplates any suitable actions based on identifying an event parameter associated with fraud...”).
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant claimed invention to modify the system of KUMAR and Abrahams to include access request likelihood score below a threshold as disclosed by French and be motivated in doing so in order to approve and facilitate the transfer the requested fund to the event organizer-French ¶0074 in parts.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over USPGPub. No. 20230409650 to KUMAR et al. (hereinafter KUMAR) in view of in view of US. Pat. No. 10108333 to Abrahams et al. (hereinafter Abrahams) and further in view of PGPub. No. 20150012467 to Greystoke et al. (hereinafter Greystoke).
Regarding claim 9, KUMAR in view of Abrahams discloses the system of Claim 1.
However, KUMAR in view of Abrahams does not explicitly disclose wherein the first domain is business travel.
Greystoke discloses wherein the first domain is business travel (¶0065, “Various sub-personas, or alternate personas, can be implemented. For example, a travel sector or travel persona may include a business travel persona, a leisure-solo travel persona, a leisure-plus-spouse travel persona, a leisure-plus-family travel persona, a group travel persona, and so on…”).
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant claimed invention to modify the system of KUMAR and Abrahams to include travel persona as disclosed by Greystoke and be motivated in doing so in order to provide a decision-making tailored specifically to user preferences, behaviors, and locations and in multiple dimensions (reactively and proactively and across various sources of information or products)-Greystoke ¶0005 in parts.
Claims 3, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over USPGPub. No. 20230409650 to KUMAR et al. (hereinafter KUMAR in view of in view of US. Pat. No. 10108333 to Abrahams et al. (hereinafter Abrahams) and further in view of PGPub. No. 20130339186 to French et al. (hereinafter French) and further in view of PGPub. No. 20200322355 to Morgan et al. (hereinafter Morgan).
Regarding claim 3, KUMAR in view of Abrahams and further in view French discloses the system of Claim 2.
KUMAR further discloses wherein to determine that the likelihood of fraud with respect to the first request is below the specified threshold, fraud detection service is to at least:
determine a timestamp associated with each of one or more data items included in the first subset of data (¶0052, “…types and categories of context may include: service/application category or type 610 (e.g., content experience, social networking, shopping, etc.); data 615 that may be supplied by the service/application (e.g., content, metadata, etc.); user behaviors 620; date and/or time 625”);
determine an amount of the one or more data items included in the first subset of data indicating a user’s online behavior with respect to the first domain (¶0001, “Online services and applications may employ user profiles to facilitate user navigation to desired content and resources and delivery of appropriate user experiences. A user profile may be built and developed based on information explicitly provided by a user (e.g., user preferences) as well as information that may be obtained by observing interactions with the online services and applications (e.g., user behaviors). Typically, each online service and application will individually build, develop, and control the profiles of its users.”), (¶0032, “the content recommendation algorithms used by an application may need to be exposed to a relatively large amount of behavior data to function effectively and capture an accurate scope of a user's interests…”), (¶0052, “The amount and kind of contextual data utilized in a given implementation of the present principles can vary. FIG. 6 is an illustrative taxonomy 600 that lists some examples of context 605 that may be utilized by the personalization model and/or services/applications 205, 210, and 215. The examples are not exhaustive, may overlap, and not all the examples need to be utilized. As shown, types and categories of context may include: service/application category or type 610 (e.g., content experience, social networking, shopping, etc.); data 615 that may be supplied by the service/application (e.g., content, metadata, etc.); user behaviors 620; date and/or time 625…”), (¶0113, “… the user experiences are associated with one or more of social networking, content experiences, mapping, news and information, entertainment, travel, productivity, or finance applications.”); and
However, KUMAR in view of Abrahams and further in view French does not explicitly disclose the following limitation:
based at least in part on the timestamp associated with the one or more data items and the amount of the one or more data items, determine that the likelihood of fraud with respect to the first request is below the specified threshold.
Morgan discloses based at least in part on the timestamp associated with the one or more data items and the amount of the one or more data items, determine that the likelihood of fraud with respect to the first request is below the specified threshold (¶0061-¶0071, FIG. 2, “…if the control system determines that one or more timestamps are included in the connection data, the control system can generate a score indicating a fraudulent level of the account based on the one or more timestamps (operation 212)… if the control system determines that the score is less the fraud threshold, the control system can allow the connection at operation 216. As such, the technician computing device can use the connection to access the cloud service to continue or start with communicating with the receiver computing device to modify, update, or manage its configuration”).
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant claimed invention to modify the system of KUMAR, Abrahams, and French to include using timestamps to detect Fraud as disclosed by Morgan and be motivated in doing so in order to generate a score indicating a fraudulent level of the account based on the one or more timestamps and access the cloud service if the score is lower that a predetermined threshold-Morgan ¶0066 in parts.
Regarding claim 12, KUMAR in view of Abrahams and further in view French discloses the computer-implemented method of Claim 11.
KUMAR further discloses wherein to determine that the likelihood of fraud with respect to the first request is below the specified threshold, fraud detection service is to at least:
determine a timestamp associated with each of one or more data items included in the first subset of data (¶0052, “…types and categories of context may include: service/application category or type 610 (e.g., content experience, social networking, shopping, etc.); data 615 that may be supplied by the service/application (e.g., content, metadata, etc.); user behaviors 620; date and/or time 625”);
determine an amount of the one or more data items included in the first subset of data indicating a user’s online behavior with respect to the first domain (¶0001, “Online services and applications may employ user profiles to facilitate user navigation to desired content and resources and delivery of appropriate user experiences. A user profile may be built and developed based on information explicitly provided by a user (e.g., user preferences) as well as information that may be obtained by observing interactions with the online services and applications (e.g., user behaviors). Typically, each online service and application will individually build, develop, and control the profiles of its users.”), (¶0032, “the content recommendation algorithms used by an application may need to be exposed to a relatively large amount of behavior data to function effectively and capture an accurate scope of a user's interests…”), (¶0052, “The amount and kind of contextual data utilized in a given implementation of the present principles can vary. FIG. 6 is an illustrative taxonomy 600 that lists some examples of context 605 that may be utilized by the personalization model and/or services/applications 205, 210, and 215. The examples are not exhaustive, may overlap, and not all the examples need to be utilized. As shown, types and categories of context may include: service/application category or type 610 (e.g., content experience, social networking, shopping, etc.); data 615 that may be supplied by the service/application (e.g., content, metadata, etc.); user behaviors 620; date and/or time 625…”), (¶0113, “… the user experiences are associated with one or more of social networking, content experiences, mapping, news and information, entertainment, travel, productivity, or finance applications.”); and
However, KUMAR in view of Abrahams and further in view French does not explicitly disclose the following limitation:
based at least in part on the timestamp associated with the one or more data items and the amount of the one or more data items, determine that the likelihood of fraud with respect to the first request is below the specified threshold.
Morgan discloses based at least in part on the timestamp associated with the one or more data items and the amount of the one or more data items, determine that the likelihood of fraud with respect to the first request is below the specified threshold (¶0061-¶0071, FIG. 2, “…if the control system determines that one or more timestamps are included in the connection data, the control system can generate a score indicating a fraudulent level of the account based on the one or more timestamps (operation 212)… if the control system determines that the score is less the fraud threshold, the control system can allow the connection at operation 216. As such, the technician computing device can use the connection to access the cloud service to continue or start with communicating with the receiver computing device to modify, update, or manage its configuration”).
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant claimed invention to modify the system of KUMAR, Abrahams, and French to include using timestamps to detect Fraud as disclosed by Morgan and be motivated in doing so in order to generate a score indicating a fraudulent level of the account based on the one or more timestamps and access the cloud service if the score is lower that a predetermined threshold-Morgan ¶0066 in parts.
Regarding claim 19, KUMAR in view of Abrahams and further in view French discloses the non-transitory computer-readable medium of Claim 17, wherein the instructions, when executed by the processor, further cause the computing system to perform the operations comprising:
determining that a likelihood of fraud with respect to the first request is below a specified threshold, wherein determining that the likelihood of fraud with respect to the first request is below the specified threshold comprises:
KUMAR further discloses determine a timestamp associated with each of one or more data items included in the first subset of data (¶0052, “types and categories of context may include: service/application category or type 610 (e.g., content experience, social networking, shopping, etc.); data 615 that may be supplied by the service/application (e.g., content, metadata, etc.); user behaviors 620; date and/or time 625”);
determine an amount of the one or more data items included in the first subset of data indicating a user’s online behavior with respect to the first domain (¶0001, “Online services and applications may employ user profiles to facilitate user navigation to desired content and resources and delivery of appropriate user experiences. A user profile may be built and developed based on information explicitly provided by a user (e.g., user preferences) as well as information that may be obtained by observing interactions with the online services and applications (e.g., user behaviors). Typically, each online service and application will individually build, develop, and control the profiles of its users.”), (¶0032, “the content recommendation algorithms used by an application may need to be exposed to a relatively large amount of behavior data to function effectively and capture an accurate scope of a user's interests…”), (¶0052, “The amount and kind of contextual data utilized in a given implementation of the present principles can vary. FIG. 6 is an illustrative taxonomy 600 that lists some examples of context 605 that may be utilized by the personalization model and/or services/applications 205, 210, and 215. The examples are not exhaustive, may overlap, and not all the examples need to be utilized. As shown, types and categories of context may include: service/application category or type 610 (e.g., content experience, social networking, shopping, etc.); data 615 that may be supplied by the service/application (e.g., content, metadata, etc.); user behaviors 620; date and/or time 625…”), (¶0113, “… the user experiences are associated with one or more of social networking, content experiences, mapping, news and information, entertainment, travel, productivity, or finance applications.”); and
However, KUMAR in view of Abrahams and further in view French does not explicitly disclose the following limitation:
based at least in part on the timestamp associated with the one or more data items determining that the likelihood of fraud with respect to the first request is below a specified threshold.
Morgan discloses based at least in part on the timestamp associated with the one or more data items determining that the likelihood of fraud with respect to the first request is below the specified threshold (¶0061-¶0071, FIG. 2, “…if the control system determines that one or more timestamps are included in the connection data, the control system can generate a score indicating a fraudulent level of the account based on the one or more timestamps (operation 212)… if the control system determines that the score is less the fraud threshold, the control system can allow the connection at operation 216. As such, the technician computing device can use the connection to access the cloud service to continue or start with communicating with the receiver computing device to modify, update, or manage its configuration”).
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant claimed invention to modify the computer-implemented method of KUMAR, Ruxton, and Morgan to include using timestamps to detect Fraud as disclosed by Morgan and be motivated in doing so in order to generate a score indicating a fraudulent level of the account based on the one or more timestamps and access the cloud service if the score is lower that a predetermined threshold-Morgan ¶0066 in parts.
Claims 4, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over USPGPub. No. 20230409650 to KUMAR et al. (hereinafter KUMAR) in view of in view of US. Pat. No. 10108333 to Abrahams et al. (hereinafter Abrahams) and further in view of PGPub. No. 20190362317 to Rogynskyy et al. (hereinafter Rogynskyy).
Regarding claim 4, KUMAR in view of Abrahams discloses the system of Claim 1.
KUMAR further discloses wherein the processor executes further specific computer- executable instructions to at least implement a relevancy service to determine that the first subset of data is relevant (¶0034, “The sharable personas operate as a single source of user identity and preferences across online ecosystems and various computing devices associated with a user to expose sufficient data to enable effective engagement with content experience applications without oversharing unnecessary information. Personas can be flexibly deployed based on applicable context with a particular application or ecosystem so that only relevant data in the persona is shared as needed to support that application's offering while data that is irrelevant to the application is suppressed.”),
However, KUMAR in view of Abrahams does not explicitly disclose
indicative of the preference of the first user, wherein to determine that the first subset of data is relevant or indicative of the preference of the first user, the relevancy service determines that a relevancy score for each of one or more data items within the first subset of data is above a specified threshold.
Rogynskyy discloses indicative of the preference of the first user, wherein to determine that the first subset of data is relevant or indicative of the preference of the first user, the relevancy service determines that a relevancy score for each of one or more data items within the first subset of data is above a specified threshold (¶0710, “… the electronic activity parser 210 can assign a relevancy score to each of the set of electronic activities based on the respective feature set. The electronic activity parser 210 may compare the relevancy scores with a first threshold value. If the relevance score satisfies the first threshold value (e.g., greater than the first threshold value), the electronic activity parser 210 may select the corresponding electronic activity to be included in the subset…”).
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant’s claimed invention to modify system of KUMAR and Abrahams in claim 1 to include relevancy score greater than a threshold as disclosed by Rogynskyy and be motivated in doing so in order to select the corresponding electronic activity to be included in the subset-Rogynskyy ¶0710 in parts.
Regarding claim 13, KUMAR in view of Abrahams discloses the computer-implemented method of Claim 10.
KUMAR further discloses further comprising: implementing a relevancy service to determine that the first subset of data is relevant (¶0034, “The sharable personas operate as a single source of user identity and preferences across online ecosystems and various computing devices associated with a user to expose sufficient data to enable effective engagement with content experience applications without oversharing unnecessary information. Personas can be flexibly deployed based on applicable context with a particular application or ecosystem so that only relevant data in the persona is shared as needed to support that application's offering while data that is irrelevant to the application is suppressed.”),
However, KUMAR in view of Abrahams does not explicitly disclose
indicative of the preference of the first user, wherein to determine that the first subset of data is relevant or indicative of the preference of the first user, the relevancy service determines that a relevancy score for each of one or more data items within the first subset of data is above a specified threshold.
Rogynskyy discloses indicative of the preference of the first user, wherein to determine that the first subset of data is relevant or indicative of the preference of the first user, the relevancy service determines that a relevancy score for each of one or more data items within the first subset of data is above a specified threshold (¶0710, “… the electronic activity parser 210 can assign a relevancy score to each of the set of electronic activities based on the respective feature set. The electronic activity parser 210 may compare the relevancy scores with a first threshold value. If the relevance score satisfies the first threshold value (e.g., greater than the first threshold value), the electronic activity parser 210 may select the corresponding electronic activity to be included in the subset…”).
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant’s claimed invention to modify system of KUMAR and Abrahams in claim 1 to include relevancy score greater than a threshold as disclosed by Rogynskyy and be motivated in doing so in order to select the corresponding electronic activity to be included in the subset-Rogynskyy ¶0710 in parts.
Regarding claim 20, KUMAR in view of Abrahams discloses the non-transitory computer-readable medium of Claim 17.
KUMAR further discloses wherein the instructions, when executed by the processor, further cause the computing system to perform operations comprising:
determining that the first subset of data is relevant (¶0034, “The sharable personas operate as a single source of user identity and preferences across online ecosystems and various computing devices associated with a user to expose sufficient data to enable effective engagement with content experience applications without oversharing unnecessary information. Personas can be flexibly deployed based on applicable context with a particular application or ecosystem so that only relevant data in the persona is shared as needed to support that application's offering while data that is irrelevant to the application is suppressed.”),
However, KUMAR in view of Abrahams does not explicitly disclose
indicative of the preference of the first user, wherein determining that the first subset of data is relevant or indicative of the preference of the first user comprises determining that a relevancy score for each of the one or more data items within the first subset of data is above a specified threshold.
Rogynskyy discloses indicative of the preference of the first user comprises determining that a relevancy score for each of the one or more data items within the first subset of data is above a specified threshold (¶0710, “… the electronic activity parser 210 can assign a relevancy score to each of the set of electronic activities based on the respective feature set. The electronic activity parser 210 may compare the relevancy scores with a first threshold value. If the relevance score satisfies the first threshold value (e.g., greater than the first threshold value), the electronic activity parser 210 may select the corresponding electronic activity to be included in the subset…”).
Thus, one of ordinary skill in the art would have found it obvious before the effective filing date of applicant’s claimed invention to modify system of KUMAR and Abrahams in claim 1 to include relevancy score greater than a threshold as disclosed by Rogynskyy and be motivated in doing so in order to select the corresponding electronic activity to be included in the subset-Rogynskyy ¶0710 in parts.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MUDASIRU K OLAEGBE whose telephone number is (571)272-2082. The examiner can normally be reached MON-FRI. 7.30AM-5.30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Farid Homayounmehr can be reached at 5712723739. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MUDASIRU K OLAEGBE/ Examiner, Art Unit 2495
/FARID HOMAYOUNMEHR/ Supervisory Patent Examiner, Art Unit 2495
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