DETAILED ACTION
Introduction
This Non-Final Office Action is in response to the application with serial number 18/681,840, filed on February 6, 2024.
Claims 3, 4, 7, 8, 11, 12, and 15-17 are amended via preliminary amendment.
Claims 1-17 are pending.
Information Disclosure Statement
The information disclosure statement filed on February 6, 2024, has been considered.
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 1-17 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) 1-17 are all directed to one of the four statutory categories of invention, the claims are directed to optimizing brand-buyer relationships (as evidenced by the preamble of exemplary independent claim 1), 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 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;” and “cause the entity server 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 optimizing a brand-buyer relationship that, when considered alone and in combination, are part of the abstract idea of optimizing a brand-buyer relationship. The dependent claims further recite steps for managing personal behavior that are part of the abstract idea of optimizing a brand-buyer relationship. 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 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 server, processor, and memory in independent claim 1; a server 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 server, processor, and memory in independent claim 1; a server 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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 9 recites the limitation: “the entity server.” There is insufficient antecedent basis for this limitation in the claim. The dependent claims inherit the deficiency.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 2, 9, 10, 16, and 17 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US 20170277803 A1 to Zimmerman et al. (hereinafter ‘ZIMMERMAN’).
Claim 1 (Previously Presented)
ZIMMERMAN discloses a system for configuring an interactive digital representation of an entity (see ¶[0027]; digital signals) to optimise a brand-buyer relationship (see ¶[0005] and [0021]; maximize success of marketing and increase traffic. The improved user performance may result in increased frequency, duration, and/or quality of user interaction) 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 in association with at least one interaction metric 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 at least one interaction milestone, determine an interaction metric value for an interaction metric associated with said interaction milestone based on the interaction statistics to measure the brand-buyer relationship, wherein the 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) determine at least one candidate interaction metric of the interactive digital representation for reconfiguring by comparing each of the determined interaction metric values 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);
d) 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); and
e) cause the entity server to configure the interactive digital representation based on the determined configuration 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 and optimise the brand-buyer relationship (see again ¶[0005] and [0021]; maximize success of marketing and increase traffic. The improved user performance may result in increased frequency, duration, and/or quality of user interaction).
Claim 2 (Previously Presented)
ZIMMERMAN discloses the system according to claim 1.
ZIMMERMAN further discloses wherein the processor is further configured to adjust the metric thresholds 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 9 (Previously Presented)
ZIMMERMAN discloses a method of configuring an interactive digital representation of an entity (see ¶[0027]; digital signals) to optimise a brand-buyer relationship (see ¶[0005] and [0021]; maximize success of marketing and increase traffic. The improved user performance may result in increased frequency, duration, and/or quality of user interaction) 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 method comprising:
a) 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);
b) for at least one interaction milestone, determining an interaction metric value for an interaction metric associated with said interaction milestone based on the interaction statistics to measure the brand-buyer relationship, wherein the 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) determining at least one candidate interaction metric of the interactive digital representation for reconfiguring by comparing each of the determined interaction metric values with a corresponding metric threshold stored in a 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), wherein the database stores a plurality of interaction milestones in association with at least one interaction metric 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);
d) determining 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); and
e) causing the entity server to configure the interactive digital representation based on the determined configuration 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 and optimise the brand-buyer relationship (see again ¶[0005] and [0021]; maximize success of marketing and increase traffic. The improved user performance may result in increased frequency, duration, and/or quality of user interaction).
Claim 10 (Previously Presented)
ZIMMERMAN discloses the method according to claim 9.
ZIMMERMAN additionally discloses further comprising adjusting the metric thresholds 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 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 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 computer-readable storage medium storing instructions which, when executed by a processor, cause the processor to perform the method of any one 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 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) 3 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20170277803 A1 to ZIMMERMAN et al. in view of US 20150339759 A1 to Pope et al. (hereinafter ‘POPE’).
Claim 3 (Currently Amended)
ZIMMERMAN discloses the system according to claim 1.
ZIMMERMAN 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)
ZIMMERMAN discloses the method according to claim 9.
ZIMMERMAN 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. in view US 9563900 B1 to Guo et al. (hereinafter ‘GUO’).
Claim 4 (Currently Amended)
ZIMMERMAN discloses the system according to claim 1.
ZIMMERMAN does not specifically disclose, but GUO discloses, wherein the database is further configured to store a weighting coefficient for 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)
ZIMMERMAN discloses the method according to claim 9.
ZIMMERMAN does not specifically disclose, but GUO discloses, wherein the database stores a weighting coefficient for 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) 8 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20170277803 A1 to ZIMMERMAN et al. in view of 0US 8321266 B2 to Cho (hereinafter ‘CHO’).
Claim 8 (Currently Amended)
ZIMMERMAN discloses the system according to claim 1.
ZIMMERMAN does not specifically disclose, but CHO discloses, wherein step e) comprises prioritising the determined configuration based on a priority of the configuration stored in the database (see col 2, ln 8-17; a user information analyzer for analyzing user preference information based on the browser reading history provided by the user information acquirer and updating the user information database based on the analyzed user preference information; and an advertisement information analyzer for acquiring the user's advertisement data with the highest priority stored in the user information analyzer from the advertisement information database, and updating the priority of the advertisement stored in the advertisement information database).
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. CHO discloses providing advertisements, where preference information of advertisements determines the priority of the advertisement displayed to users. It would have been obvious to include the preference information as taught by CHO in the system executing the method of ZIMMERMAN with the motivation to provide preferred advertising content to users.
Claim 15 (Currently Amended)
ZIMMERMAN discloses the method according to claim 9.
ZIMMERMAN does not specifically disclose, but CHO discloses, wherein step e) further comprises prioritising the determined configuration based on a priority of the configuration stored in the database (see col 2, ln 8-17; a user information analyzer for analyzing user preference information based on the browser reading history provided by the user information acquirer and updating the user information database based on the analyzed user preference information; and an advertisement information analyzer for acquiring the user's advertisement data with the highest priority stored in the user information analyzer from the advertisement information database, and updating the priority of the advertisement stored in the advertisement information database).
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. CHO discloses providing advertisements, where preference information of advertisements determines the priority of the advertisement displayed to users. It would have been obvious to include the preference information as taught by CHO in the system executing the method of ZIMMERMAN with the motivation to provide preferred advertising content to users.
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 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 (Previously Presented)
The combination of ZIMMERMAN and GUO discloses the system according to claim 4.
The combination of ZIMMERMAN 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); and
The combination of ZIMMERMAN and GUO does not specifically disclose, but PARK discloses, cause a display screen to display, on a user interface, the determined 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 (Previously Presented)
The combination of ZIMMERMAN, 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 determined entity score and the determined configuration and cause the display screen to display the generated 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 (Previously Presented)
The combination of ZIMMERMAN and GUO discloses the method according to claim 12.
The combination of ZIMMERMAN 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).
The combination of ZIMMERMAN and GUO does not specifically disclose, but PARK discloses, causing a display screen to display, on a user interface, the determined 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 determined entity score and the determined configuration and causing the display screen to display the generated 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 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. 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, GUO, CHAUDHURI, and PARK discloses the system according to claim 5.
The combination of ZIMMERMAN, 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 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.
Claim 14 (Previously Presented)
The combination of ZIMMERMAN, GUO, CHAUDHURI, and PARK discloses the method according to claim 13.
The combination of ZIMMERMAN, GUO, CHAUDHURI, and PARK does not specifically disclose but YAHIL discloses, further comprising repeating steps a) to e) 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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RICHARD N SCHEUNEMANN whose telephone number is (571)270-7947. The examiner can normally be reached M-F 9am-5pm EST.
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/RICHARD N SCHEUNEMANN/ Primary Examiner, Art Unit 3624
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