DETAILED ACTION
Introduction
This Final Office Action is in response to amendments and remarks filed on January 22, 2026, for the application with serial number 18/681,840.
Claims 1, 2, and 4-17 are amended.
Claims 18-20 are added.
Claims 1-20 are pending.
Response to Remarks/Amendments
35 USC §101 Rejections
The Applicant traverses the rejection of the claims as being directed to an ineligible abstract idea, contending that the claims do not recite an abstract idea. See Remarks p. 10. In response, the Examiner points to the rejection, below, which concludes that the claims are directed to determining a configuration for a representation of entity. Essentially, the claims recited steps for determining the best content to display to a consumer or customer to induce the customer to interact with the content. The method could be implemented mentally or on paper by a human being, but a general purpose computer is recited for implementation.
The Applicant further contends that the claims are subject matter eligible because the claims contain technical subject matter. See Remarks p. 11. In response, the Examiner submits that the recitation of “interaction metrics” does not render the claims eligible. No apparent improvement to a technology or technical field is recited in the claims. The claims do not recite specific formatting or configuring steps for the digital representation that are rooted in computer technology. Merely stating that the digital configuration is based on interaction does not provide significantly more than the abstract idea – the recitation is part of the abstract idea of determining a configuration for a representation of an entity.
The rejection for lack of subject matter eligibility is updated and maintained.
35 USC §112 Rejections
In light of the Applicant’s amendments, the rejections under 35 USC §112 are withdrawn.
35 USC §103 Rejections
Amendments to the claims changed the scope of the claims, necessitating further search and consideration of the prior art. A new search returned the Khodorenko reference, which is cited in the rejection of the independent claims, below.
The Applicant contends that Zimmerman does not objectively measure a relationship. See Remarks p. 14. In response, the Examiner points to cited ¶[0020] and [0024] of Zimmerman, which teaches measuring interactions based on duration of time to conclude that an impression is positive. This is an objective measurement of a relationship. The Applicant’s remaining remarks are moot in light of the newly cited Khodorenko reference.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
The Manual of Patent Examining Procedure (MPEP) provides detailed rules for determining subject matter eligibility for claims in §2106. Those rules provide a basis for the analysis and finding of ineligibility that follows.
Claims 1-20 are rejected under 35 U.S.C. 101. The claimed invention is directed to non-statutory subject matter because the claimed invention recites a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Although claims(s) 1-20 are all directed to one of the four statutory categories of invention, the claims are directed to determining a configuration for a representation of an entity (as evidenced by the preamble of exemplary independent claim 1: “A system for configuring an interactive digital representation of an entity”), an abstract idea. Certain methods of organizing human activity are ineligible abstract ideas, including managing personal behavior or relationships or interactions between people. See MPEP §2106.04(a). The limitations of exemplary claim 1 include: “store a plurality of interaction milestones;” “receive a digital representation of an entity and interaction statistics for the [digital representation];” “determine . . . one or more interaction metrics;” “determine an interaction metric value;” “determine at least one candidate interaction metric of the interactive digital representation;” “determine a configuration for the interactive digital representation using [a] configuration stored in the database;” “generate at least one instruction . . . to configure the interactive digital representation based on the determined configuration.” The steps are all steps for managing personal behavior related to the abstract idea of determining a configuration for a representation of an entity that, when considered alone and in combination, are part of the abstract idea of determining a configuration for a representation of an entity. The dependent claims further recite steps for managing personal behavior that are part of the abstract idea of determining a configuration for a representation of an entity. These claim elements, when considered alone and in combination, are considered to be abstract ideas because they are directed to a method of organizing human activity which includes determining the best content and presentation of content to provide to a consumer based on objective metrics.
Under step 2A of the subject matter eligibility analysis, a claim that recites a judicial exception must be evaluated to determine whether the claim provides a practical application of the judicial exception. Additional elements of the independent claims amount to generic computer hardware that does not provide a practical application (a processor and memory in independent claim 1; a computer with a processor in independent claim 9; an apparatus in dependent claim 16; and a computer readable medium in independent claim 17). See MPEP §2106.04(d)[I]. The claims do not recite an improvement to another technology or technical field, nor do they recite an improvement to the functioning of the computer itself. See MPEP §2106.05(a). The claims require no more than a generic computer (a processor and memory in independent claim 1; a computer with a processor in independent claim 9; an apparatus in dependent claim 16; and a computer readable medium in independent claim 17) to implement the abstract idea, which does not amount to significantly more than an abstract idea. See MPEP §2106.05(f). Because the claims only recite use of a generic computer, they do not apply the judicial exception with a particular machine. See MPEP §2106.05(b). For these reasons, the claims do not provide a practical application of the abstract idea, nor do they amount to significantly more than an abstract idea under step 2B of the subject matter eligibility analysis. Using a generic computer to implement an abstract idea does not provide an inventive concept. Therefore, the claims recite ineligible subject matter under 35 USC §101.
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.
Claim(s) 1, 2, 8-10, and 15-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20170277803 A1 to Zimmerman et al. (hereinafter ‘ZIMMERMAN’) in view of US 20140164502 A1 to Khodorenko et al. (hereinafter ‘KHODORENKO’).
Claim 1 (Currently Amended)
ZIMMERMAN discloses a system for configuring an interactive digital representation of an entity (see ¶[0027]; digital signals) based on interaction of at least one user with the interactive digital representation of the entity (see abstract; the method includes receiving data respective of interactions of a user with web content displayed on a user device during at least one electronic transaction, wherein the web content is associated with at least a product; determining, based on the received data, a user impression; generating a user profile including at least the determined user impression; determining at least one content modification parameter respective of the generated user profile), the system comprising:
a processor (see ¶[0009] and [0027]; the system includes a processing unit; and a memory, the memory containing instructions that, when executed by the processing unit. The processing unit 132 may comprise or be a component of a processor (not shown) or an array of processors coupled to the memory 134);
a database coupled with the processor (see ¶[0014] and [0027] & Fig. 1; a database on a network with a processing unit), the database being configured to store a plurality of interaction milestones (see ¶[0020] and [0024]; user viewing particular content for a duration of time that is above a predefined threshold may be determined as a positive user impression).
ZIMMERMAN does not specifically disclose, but KHODORENKO discloses, in association with a priority for each interaction milestone (see ¶[0088]; the interaction server 44 may, receive from the rules engine a higher priority value for interactions that carry a negative sentiment/tone than those that have a positive or neutral tone, recognizing that people are generally likely to remember and pass on bad news rather than good news).
ZIMMERMAN further discloses at least one interaction metric for each interaction milestone (see again ¶[0020] and [0024]; a duration of time), and a corresponding metric threshold, each interaction metric being associated with a configuration corresponding to the interaction metric (see ¶[0020] and [0024]; user viewing particular content for a duration of time that is above a predefined threshold may be determined as a positive user impression. A threshold may be (e.g., a time threshold, a performance threshold, and so on); and
memory coupled with the processor, memory being configured to store instructions (see ¶[0009]; the system includes a processing unit; and a memory, the memory containing instructions that, when executed by the processing unit, configure the system to: receive data respective of interactions of a user with web content displayed on a user device during at least one electronic transaction) which, when executed by the processor, cause the processor to:
a) receive a current interactive digital representation of an entity and interaction statistics for the current interactive digital representation (see abstract and ¶[0017]-[0018]; user interaction with web content. A display feature that may be any visual element presented to the user device 110 with respect to a particular display of content. For example, the feature may be an advertisement or banner displayed with respect to a transaction. The user impression may be a definitive value representing the user interactions respective of the data. The definitive value may be based on, but is not limited to, actions taken by the user respective of the displayed content, a duration of time spent viewing the content, a result of the user interactions (e.g., viewing additional content and/or leaving a web page), and so on);
b) for each interaction milestone, determine, using the database, one or more interaction metrics assigned to the interaction milestone, wherein each interaction milestone is associated with a milestone in a digital brand-buyer relationship, wherein at least one interaction milestone relates to a duration of interaction of the at least one user with the current interactive digital representation of the entity (see ¶[0019]; the user impression may represent an interest or other inclination of the user toward the content. In an embodiment, the user impression may further represent an interest in a product associated with the displayed content. The user interest may be, e.g., positive, negative, neutral, and so on. The user impression may further indicate a degree of inclination such as, for example, high, low, medium, and so on. The user impression may be represented as a numeric value, a Boolean value, a string, and the like);
c) for each of the determined one or more interaction metrics for the milestone, determine an interaction metric value based on the interaction statistics to measure the digital brand-buyer relationship (see again ¶[0019]; the user impression may represent an interest or other inclination of the user toward the content. In an embodiment, the user impression may further represent an interest in a product associated with the displayed content. The user interest may be, e.g., positive, negative, neutral, and so on. The user impression may further indicate a degree of inclination such as, for example, high, low, medium, and so on. The user impression may be represented as a numeric value, a Boolean value, a string, and the like);
d) determine at least one candidate interaction metric of the interactive digital representation for reconfiguring by comparing the interaction metric value for each of the one or more interaction metrics with a corresponding metric threshold stored in the database (see ¶[0020] and [0024]; a user impression related to a completion of a transaction to purchase a product (e.g., clicking a “Purchase” button displayed on the user device 110) may be determined as a highly positive user impression, while a user impression related to abandonment of an electronic shopping cart (e.g., by leaving the web page) may be determined as a negative user impression. As another example, a user viewing particular content for a duration of time that is above a predefined threshold may be determined as a positive user impression. As yet another example, if the user interacted with the content to view further content (e.g., clicking on an ad), the user impression may be determined as highly positive. The server 130 may be further configured to determine one or more criteria respective of each content modification parameter. The criteria may be dependent on the user and may be time-based, performance-based, and so on. The criteria may include a threshold (e.g., a time threshold, a performance threshold, and so on). Upon determination that the criteria for a particular content modification is met, the server 140 may be configured to modify the content displayed on the user device 110 accordingly);
e) determine a configuration for the interactive digital representation using the configuration stored in the database for the at least one candidate interaction metric and the current interactive digital representation (see again ¶[0024]; the server may be configured to modify the content displayed on the user device accordingly).
ZIMMERMAN does not specifically disclose, but KHODORENKO discloses, wherein the configuration is determined based on the priority of the interaction milestone corresponding to the at least one candidate interaction metric (see ¶[0003], [0048]-[0053], and [0167] & Figs. 6a-b; switch to a new interaction channel to have a more extensive conversation uninhibited by constraints such as character limitations. Switch based on an escalation).
ZIMMERMAN further discloses f) generate at least one instruction based on the configuration to configure the interactive digital representation to thereby update the current interactive digital representation of the entity (see again ¶[0024]; the server may be configured to modify the content displayed on the user device accordingly).
ZIMMERMAN discloses a method for inducing user activity with web content interactions that applies thresholds to interaction parameters with the content to determine to modify the content, where user interest is deemed to be positive or negative (see ¶[0019]). KHODORENKO discloses message classification based on influence that includes determining whether interactions are positive or negative, and assigning a priority for media escalation based on the polarity. It would have been obvious to include the priority as taught by KHODORENKO in the system executing the method of ZIMMERMAN with the motivation to prioritize negative interactions over positive interactions for the purposes of escalation and communication.
Claim 2 (Currently Amended)
The combination of ZIMMERMAN and KHODORENKO discloses the system according to claim 1.
ZIMMERMAN further discloses wherein the processor is further configured to adjust the corresponding metric threshold based on the entity (see ¶[0024]; the criteria may be dependent on the user and may be time-based, performance-based, and so on. The criteria may include a threshold (e.g., a time threshold, a performance threshold, and so on).
Claim 8 (Currently Amended)
The combination of ZIMMERMAN and KHODORENKO discloses the system according to claim 1.
ZIMMERMAN further discloses, wherein memory is further configured to store instructions which, when executed by the processor, cause the processor to: transmit the at least one instruction to an entity server to re-configure the current interactive digital representation of the entity (see ¶[0014]; the network includes a server).
Claim 9 (Currently Amended)
ZIMMERMAN discloses a computer-implemented method (see abstract; a computer processor) of configuring an interactive digital representation of an entity (see ¶[0027]; digital signals) based on interaction of at least one user with the interactive digital representation of the entity (see abstract; the method includes receiving data respective of interactions of a user with web content displayed on a user device during at least one electronic transaction, wherein the web content is associated with at least a product; determining, based on the received data, a user impression; generating a user profile including at least the determined user impression; determining at least one content modification parameter respective of the generated user profile), the computer-implemented method comprising:
receiving a current interactive digital representation of an entity and interaction statistics for the current interactive digital representation (see abstract and ¶[0017]-[0018]; user interaction with web content. A display feature that may be any visual element presented to the user device 110 with respect to a particular display of content. For example, the feature may be an advertisement or banner displayed with respect to a transaction. The user impression may be a definitive value representing the user interactions respective of the data. The definitive value may be based on, but is not limited to, actions taken by the user respective of the displayed content, a duration of time spent viewing the content, a result of the user interactions (e.g., viewing additional content and/or leaving a web page), and so on);
storing, in a database, a plurality of interaction milestones (see ¶[0020] and [0024]; user viewing particular content for a duration of time that is above a predefined threshold may be determined as a positive user impression).
ZIMMERMAN does not specifically disclose, but KHODORENKO discloses, in association with a priority for each interaction milestone (see ¶[0088]; the interaction server 44 may, receive from the rules engine a higher priority value for interactions that carry a negative sentiment/tone than those that have a positive or neutral tone, recognizing that people are generally likely to remember and pass on bad news rather than good news).
ZIMMERMAN further discloses, at least one interaction metric for each interaction milestone (see again ¶[0020] and [0024]; a duration of time), and a corresponding metric threshold, each interaction metric being associated with a configuration corresponding to each interaction metric (see ¶[0020] and [0024]; user viewing particular content for a duration of time that is above a predefined threshold may be determined as a positive user impression. A threshold may be (e.g., a time threshold, a performance threshold, and so on);
for each interaction milestone, determining, using a processor and the database, one or more interaction metrics assigned to the interaction milestone, wherein each interaction milestone is associated with a milestone in a digital brand-buyer relationship, wherein at least one interaction milestone relates to a duration of interaction of the at least one user with the current interactive digital representation of the entity (see ¶[0019]; the user impression may represent an interest or other inclination of the user toward the content. In an embodiment, the user impression may further represent an interest in a product associated with the displayed content. The user interest may be, e.g., positive, negative, neutral, and so on. The user impression may further indicate a degree of inclination such as, for example, high, low, medium, and so on. The user impression may be represented as a numeric value, a Boolean value, a string, and the like);
for each of the determined one or more interaction metrics for the milestone, determining, using the processor, an interaction metric value based on the interaction statistics to measure the digital brand-buyer relationship (see ¶[0019]; the user impression may represent an interest or other inclination of the user toward the content. In an embodiment, the user impression may further represent an interest in a product associated with the displayed content. The user interest may be, e.g., positive, negative, neutral, and so on. The user impression may further indicate a degree of inclination such as, for example, high, low, medium, and so on. The user impression may be represented as a numeric value, a Boolean value, a string, and the like);
determining, using the processor, at least one candidate interaction metric of the interactive digital representation for reconfiguring by comparing the interaction metric value for each of the one or more interaction metrics with the corresponding metric threshold stored in the database (see ¶[0020] and [0024]; a user impression related to a completion of a transaction to purchase a product (e.g., clicking a “Purchase” button displayed on the user device 110) may be determined as a highly positive user impression, while a user impression related to abandonment of an electronic shopping cart (e.g., by leaving the web page) may be determined as a negative user impression. As another example, a user viewing particular content for a duration of time that is above a predefined threshold may be determined as a positive user impression. As yet another example, if the user interacted with the content to view further content (e.g., clicking on an ad), the user impression may be determined as highly positive. The server 130 may be further configured to determine one or more criteria respective of each content modification parameter. The criteria may be dependent on the user and may be time-based, performance-based, and so on. The criteria may include a threshold (e.g., a time threshold, a performance threshold, and so on). Upon determination that the criteria for a particular content modification is met, the server 140 may be configured to modify the content displayed on the user device 110 accordingly);
d) determining, using a processor, a configuration for the interactive digital representation using the configuration stored in the database for the at least one candidate interaction metric and the current interactive digital representation (see again ¶[0024]; the server may be configured to modify the content displayed on the user device accordingly).
ZIMMERMAN does not specifically disclose, but KHODORENKO discloses, wherein the configuration is determined based on the priority of the interaction milestone corresponding to the at least one candidate interaction metric (see ¶[0003], [0048]-[0053], and [0167] & Figs. 6a-b; switch to a new interaction channel to have a more extensive conversation uninhibited by constraints such as character limitations. Switch based on an escalation).
ZIMMERMAN further discloses generating, using the processor, at least one instruction based on the configuration to configure the interactive digital representation to thereby update the current interactive digital representation of the entity (see again ¶[0024]; the server may be configured to modify the content displayed on the user device accordingly).
ZIMMERMAN discloses a method for inducing user activity with web content interactions that applies thresholds to interaction parameters with the content to determine to modify the content, where user interest is deemed to be positive or negative (see ¶[0019]). KHODORENKO discloses message classification based on influence that includes determining whether interactions are positive or negative, and assigning a priority for media escalation based on the polarity. It would have been obvious to include the priority as taught by KHODORENKO in the system executing the method of ZIMMERMAN with the motivation to prioritize negative interactions over positive interactions for the purposes of escalation and communication.
Claim 10 (Currently Amended)
The combination of ZIMMERMAN and KHODORENKO discloses the computer-implemented method according to claim 9.
ZIMMERMAN additionally discloses further comprising adjusting the corresponding metric threshold based on the entity (see ¶[0024]; the criteria may be dependent on the user and may be time-based, performance-based, and so on. The criteria may include a threshold (e.g., a time threshold, a performance threshold, and so on).
Claim 15 (Currently Amended)
ZIMMERMAN discloses the computer-implemented method according to claim 9.
ZIMMERMAN additionally discloses further comprising transmitting the at least one instruction to an entity server to re-configure the current interactive digital representation of the entity. (see ¶[0014]; the network includes a server).
Claim 16 (Currently Amended)
ZIMMERMAN discloses an apparatus for configuring an interactive digital representation of an entity, the apparatus comprising a processor configured to perform the computer-implemented method of claim 9 (see ¶[0009] and [0027]; the system includes a processing unit; and a memory, the memory containing instructions that, when executed by the processing unit. The processing unit 132 may comprise or be a component of a processor (not shown) or an array of processors coupled to the memory 134. See also claim 9 rejection, above).
Claim 17 (Currently Amended)
ZIMMERMAN discloses a non-transitory computer-readable storage medium for configuring an interactive digital representation of an entity, the non-transitory computer-readable storage medium for storing instructions which, when executed by a processor, cause the processor to perform the computer-implemented method of claim 9 (see ¶[0041]; the software is preferably implemented as an application program tangibly embodied on a program storage unit or computer readable medium consisting of parts, or of certain devices and/or a combination of devices. The application program may be uploaded to, and executed by, a machine comprising any suitable architecture. Preferably, the machine is implemented on a computer platform having hardware such as one or more central processing units (“CPUs”), a memory, and input/output interfaces. See also claim 9 rejection, above).
Claim 18 (New)
The combination of ZIMMERMAN and KHODORENKO discloses the computer-implemented method according to claim 9.
ZIMMERMAN additionally discloses further comprising: displaying a first user interface element configured to receive a user input to identify the current interactive digital representation of the entity (see abstract ¶[0022]; user interactions include clicking and scrolling. A user profile is generated).
Claim 19 (New)
The combination of ZIMMERMAN and KHODORENKO discloses the computer-implemented method according to claim 9.
ZIMMERMAN additionally discloses further comprising: displaying a second user interface element configured to receive a user input to fetch the interaction statistics for the current interactive digital representation of the entity from at least one usage data service provider (see ¶[0022]; determine and identify user performance parameters).
Claim 20 (New)
The combination of ZIMMERMAN and KHODORENKO discloses the computer-implemented method according to claim 9.
ZIMMERMAN additionally discloses further comprising displaying a plurality of interaction metrics used to measure the digital brand-buyer relationship (see ¶[0022]; determine and identify user performance parameters).
Claim(s) 3 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20170277803 A1 to ZIMMERMAN et al. and US 20140164502 A1 to KHODORENKO et al. as applied to claim 1 above, and further in view of US 20150339759 A1 to Pope et al. (hereinafter ‘POPE’).
Claim 3 (Previously Presented)
The combination of ZIMMERMAN and KHODORENKO discloses the system according to claim 1.
The combination of ZIMMERMAN and KHODORENKO does not specifically disclose, but POPE discloses, wherein the plurality of interaction milestones comprises a zero second interaction milestone, a ten seconds interaction milestone, a three minutes interaction milestone, a sign-up milestone, a first fourty eight hours after sign-up milestone, and an upgrade milestone (see ¶[0091]; the threshold period of time may be based on an upgrade purchase interval associated with the product. This upgrade purchase interval may be determined based on a statistical amount of time users wait to replace the product. For example, the threshold period of time may be based on the length of time that the average user waits to upgrade the product or an amount of time that a percentage of users (e.g., 35%, 50%, or 60%) wait to replace the product).
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content. POPE discloses providing a recommendation after a threshold period of time for upgrade or purchase. It would have been obvious to include the recommendation for repeat purchase or upgrade as taught by POPE in the system executing the method of ZIMMERMAN with the motivation to induce user activity with web content.
Claim 11 (Currently Amended)
The combination of ZIMMERMAN and KHODORENKO discloses the computer-implemented method according to claim 9.
The combination of ZIMMERMAN and KHODORENKO does not specifically disclose, but POPE discloses, wherein the plurality of interaction milestones comprises a zero second interaction milestone, a ten seconds interaction milestone, a three minutes interaction milestone, a sign-up milestone, a first fourty eight hours after sign-up milestone, and an upgrade milestone (see ¶[0091]; the threshold period of time may be based on an upgrade purchase interval associated with the product. This upgrade purchase interval may be determined based on a statistical amount of time users wait to replace the product. For example, the threshold period of time may be based on the length of time that the average user waits to upgrade the product or an amount of time that a percentage of users (e.g., 35%, 50%, or 60%) wait to replace the product).
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content. POPE discloses providing a recommendation after a threshold period of time for upgrade or purchase. It would have been obvious to include the recommendation for repeat purchase or upgrade as taught by POPE in the system executing the method of ZIMMERMAN with the motivation to induce user activity with web content.
Claim(s) 4 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20170277803 A1 to ZIMMERMAN et al. and US 20140164502 A1 to KHODORENKO et al. as applied to claim 1 above, and further in view of in view US 9563900 B1 to Guo et al. (hereinafter ‘GUO’).
Claim 4 (Currently Amended)
The combination of ZIMMERMAN and KHODORENKO discloses the system according to claim 1.
The combination of ZIMMERMAN and KHODORENKO does not specifically disclose, but GUO discloses, wherein the database is further configured to store a weighting coefficient for each interaction milestone, wherein the weighting coefficient indicates an impact of each interaction milestone (see col 2, ln 25-36; receiving a client device ID and client device profile data, determining consumer attached session data associated with the client device ID, receiving session data, determining a weighted correlation value by comparing the session data to the consumer attached session data, and updating consumer attached session data if the weighted correlation value satisfies a predetermined threshold. In some embodiments, the weighted correlation value is based on one or more page view indications, one or more page view duration indications, aggregate page view information and aggregate page view duration information).
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content. GUO discloses consumer tracking using session data with weights applied to correlation values determined from the session data. It would have been obvious to include the weights as taught by GUO in the system executing the method of ZIMMERMAN with the motivation to induce user activity with web content.
Claim 12 (Currently Amended)
The combination of ZIMMERMAN and KHODORENKO discloses the computer-implemented method according to claim 9.
The combination of ZIMMERMAN and KHODORENKO does not specifically disclose, but GUO discloses, wherein the database stores a weighting coefficient for each interaction milestone), wherein the weighting coefficient indicates an impact or each interaction milestone (see col 2, ln 25-36; receiving a client device ID and client device profile data, determining consumer attached session data associated with the client device ID, receiving session data, determining a weighted correlation value by comparing the session data to the consumer attached session data, and updating consumer attached session data if the weighted correlation value satisfies a predetermined threshold. In some embodiments, the weighted correlation value is based on one or more page view indications, one or more page view duration indications, aggregate page view information and aggregate page view duration information).
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content. GUO discloses consumer tracking using session data with weights applied to correlation values determined from the session data. It would have been obvious to include the weights as taught by GUO in the system executing the method of ZIMMERMAN with the motivation to induce user activity with web content.
Claim(s) 5, 6, and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20170277803 A1 to ZIMMERMAN et al. in view of US 20140164502 A1 to KHODORENKO et al. and US 9563900 B1 to GUO et al. as applied to claims 1 and 4 above, and further in view of US 20170206549 A1 to CHAUDHURI et al. (hereinafter ‘CHAUDHURI’) and US 8972275 B2 to Park et al. (hereinafter ‘PARK’).
Claim 5 (Currently Amended)
The combination of ZIMMERMAN, KHODORENKO, and GUO discloses the system according to claim 4.
The combination of ZIMMERMAN, KHODORENKO, and GUO does not specifically disclose, but CHAUDHURI discloses, wherein memory is further configured to store instructions which, when executed by the processor, cause the processor to: determine an entity score by combining interaction metric values for the plurality of interaction milestones weighted based on a weighting coefficient associated with a corresponding interaction milestone (see abstract and ¶[0022]; rank advertisements based on functions and provide an advertisement with a highest score to a user. A threshold is used to normalize a score) wherein the entity score indicates the digital brand-buyer relationship; and
The combination of ZIMMERMAN, KHODORENKO, and GUO does not specifically disclose, but PARK discloses, cause a display screen to display, on a user interface, the entity score to a user (see col 6, ln 62-col 7, ln 21; the data may be filtered based on any relevant criteria, such as, a number of webpages or a period of time. See also see col 10, ln 47-53; the reporting module 126 can compile information from the analytic module 122, determination module 124, or both to generate various types of reports and make recommendations to improve social media optimization.).
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content. CHAUDHURI discloses recommending advertisements using ranking functions that includes scoring advertisements and providing the highest scoring advertisement to a user. It would have been obvious for one of ordinary skill in the art at the time of invention to include the scoring of advertisements using weighted vectors as taught by CHAUDHURI in the system executing the method of ZIMMERMAN with the motivation to induce user activity with web content.
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content. PARK discloses optimization of social media engagement that includes a report with recommendations to improve media optimization. It would have been obvious to include the report as taught by PARK in the system executing the method of ZIMMERMAN with the motivation to induce user activity with web content.
Claim 6 (Currently Amended)
The combination of ZIMMERMAN, KHODORENKO, GUO, CHAUDHURI, and PARK discloses the system according to claim 5.
ZIMMERMAN does not specifically disclose, but PARK discloses wherein memory is further configured to store instructions which, when executed by the processor, cause the processor to: in response to receiving, via the user interface, an indication from the user to improve the entity score, generate a configuration report using the entity score and the configuration and cause the display screen to display the configuration report on the user interface (see col 10, ln 47-53; the reporting module 126 can compile information from the analytic module 122, determination module 124, or both to generate various types of reports and make recommendations to improve social media optimization. The reporting module 126 can include one or more algorithms that can generate one or more reports and provide one or more recommendations for improved social media optimization. See also col 2, ln 9-28; generate a report to display to a user).
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content. PARK discloses optimization of social media engagement that includes a report with recommendations to improve media optimization. It would have been obvious to include the recommendations as taught by PARK in the system executing the method of ZIMMERMAN with the motivation to induce user activity with web content.
Claim 13 (Currently Amended)
The combination of ZIMMERMAN, KHODORENKO, and GUO discloses the computer-implemented method according to claim 12.
The combination of ZIMMERMAN, KHODORENKO, and GUO does not specifically disclose, but CHAUDHURI discloses, further comprising: determining an entity score by combining interaction metric values for the plurality of interaction milestones weighted based on a weighting coefficient associated with a corresponding interaction milestone (see abstract and ¶[0022]; rank advertisements based on functions and provide an advertisement with a highest score to a user. A threshold is used to normalize a score), wherein the entity score indicates the digital brand-buyer relationship
The combination of ZIMMERMAN, KHODORENKO, and GUO does not specifically disclose, but PARK discloses, causing a display screen to display, on a user interface, the entity score to a user (see col 6, ln 62-col 7, ln 21; the data may be filtered based on any relevant criteria, such as, a number of webpages or a period of time. See also see col 10, ln 47-53; the reporting module 126 can compile information from the analytic module 122, determination module 124, or both to generate various types of reports and make recommendations to improve social media optimization.); and
in response to receiving, via the user interface, an indication from the user to improve the entity score, generating a configuration report using the entity score and the configuration and causing the display screen to display the configuration report on the user interface (see col 10, ln 47-53; the reporting module 126 can compile information from the analytic module 122, determination module 124, or both to generate various types of reports and make recommendations to improve social media optimization. The reporting module 126 can include one or more algorithms that can generate one or more reports and provide one or more recommendations for improved social media optimization. See also col 2, ln 9-28; generate a report to display to a user).
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content. CHAUDHURI discloses recommending advertisements using ranking functions that includes scoring advertisements and providing the highest scoring advertisement to a user. It would have been obvious for one of ordinary skill in the art at the time of invention to include the scoring of advertisements using weighted vectors as taught by CHAUDHURI in the system executing the method of ZIMMERMAN with the motivation to induce user activity with web content.
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content. PARK discloses optimization of social media engagement that includes a report with recommendations to improve media optimization. It would have been obvious to include the report as taught by PARK in the system executing the method of ZIMMERMAN with the motivation to induce user activity with web content.
Claim(s) 7 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20170277803 A1 to ZIMMERMAN et al. in view of US 20140164502 A1 to KHODORENKO et al., US 9563900 B1 to GUO et al., US 20170206549 A1 to CHAUDHURI et al., and US 8972275 B2 to Park et al. as applied to claims 1, 4, and 5 above, and further in view of US 10068327 B2 to Yahil (hereinafter ‘YAHIL’).
Claim 7 (Currently Amended)
The combination of ZIMMERMAN, KHODORENKO, GUO, CHAUDHURI, and PARK discloses the system according to claim 5.
The combination of ZIMMERMAN, KHODORENKO, GUO, CHAUDHURI, and PARK does not specifically disclose but YAHIL discloses, wherein memory is further configured to store instructions which, when executed by the processor, cause the processor to repeat steps a) to e) if the entity score is below an entity score threshold (see claim 1; if fit is below a threshold, iteratively optimize parameters and determine a fit of the subset of new parameters until the threshold is satisfied).
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content and maximize performance. YAHIL discloses modeling that includes iteratively optimizing parameters when performance is below a threshold. It would have been obvious to include iterative optimization as taught by YAHIL in the system executing the method of ZIMMERMAN with the motivation to maximize performance of interaction parameters and induce user activity with content.
Claim 14 (Currently Amended)
The combination of ZIMMERMAN, KHODORENKO, GUO, CHAUDHURI, and PARK discloses the computer-implemented method according to claim 13.
The combination of ZIMMERMAN, KHODORENKO, GUO, CHAUDHURI, and PARK does not specifically disclose but YAHIL discloses, further comprising repeating steps of claim 9 if the determined entity score is below an entity score threshold (see claim 1; if fit is below a threshold, iteratively optimize parameters and determine a fit of the subset of new parameters until the threshold is satisfied).
ZIMMERMAN discloses a method for inducing user activity with web content that applies thresholds to interaction parameters with the content to determine to modify the content and maximize performance. YAHIL discloses modeling that includes iteratively optimizing parameters when performance is below a threshold. It would have been obvious to include iterative optimization as taught by YAHIL in the system executing the method of ZIMMERMAN with the motivation to maximize performance of interaction parameters and induce user activity with content.
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.
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/RICHARD N SCHEUNEMANN/Primary Examiner, Art Unit 3624
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