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 .
Status of Claims
This is a final rejection in response to claims filed on 08/29/2025. Claims 1-3 and 5 are currently amended. Claims 1-5 remain pending and are examined herein.
Priority
The claims hold priority to US Provisional Application #63/400,042 filed on 08/22/2022.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
© the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
-“a profile ring feature module (102) configured to exhibit a profile ring on a profile of each user” in claim 1.
-“a user activity tracking module (103) configured to generate one or more signals derived from a plurality of actions executed by one or more users on the online social networking platform (101),” in claim 1
-“a notification module (104) configured to provide plurality of real time notifications to the user upon detecting variations in the color of the profile ring,” in claim 1
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. The corresponding structure is found in the provisional application #63/400,042 specification filed on 08/22/2022, specifically in paragraph, “[0014] Furthermore, the described features, structures, or characteristics of the invention may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided, such as examples of programming, software modules, user selections, network transactions, database queries, database structures, hardware modules, hardware circuits, hardware chips, etc., to provide a thorough understanding of embodiments of the invention.” Therefore, the modules are interpreted to be software or hardware modules.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claims 1-3 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because as set forth in the claim interpretation section, the recited “modules” encompass both software and hardware modules. Since the modules encompass software without specific structure (according to the provisional application #63/400,042 specification filed on 08/22/2022, specifically in paragraph [0014]), the claims are directed to a “computer program per se” or “software per se.” MPEP 2106.03 describes software per se as “Software expressed as code or a set of instructions detached from any medium is an idea without physical embodiment. See Microsoft Corp. v. AT&T Corp., 550 U.S. 437, 449, 82 USPQ2d 1400, 1407 (2007); see also Benson, 409 U.S. 67, 175 USPQ2d 675 (An "idea" is not patent eligible). Thus, a product claim to a software program that does not also contain at least one structural limitation (such as a "means plus function" limitation) has no physical or tangible form, and thus does not fall within any statutory category.” In order to overcome these rejections, the claims must provide structural recitations, when reciting a computer product, such as the computing infrastructure performing the software functions. Claim 2-3 are also rejected by virtue of their dependency to claim 1. For purposes of compact prosecution, the claims hereinafter are analyzed under the 2 step process as if they satisfied step 1.
Claims 1-5 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Is the claim to a Process, Machine, Manufacture, or Composition of Matter?
Claims 1-3: A system for evaluating a user demeanor and authenticity within an online social networking platform, the system (100) comprises
Claims 4-5: A method for evaluating a user demeanor and authenticity within an online social networking platform, the method
Claims 1-3 recite a system with modules which falls under “machine.” Claims 4-5 recite a method which falls under process, therefore both claims pass step 1 and are to be further analyzed under step 2.
Step 2a Prong 1: Is the claim directed to a Judicial Exception(A Law of Nature, a Natural Phenomenon (Product of Nature), or An Abstract Idea?)
The claims under the broadest reasonable interpretation in light of the specification are analyzed herein. Representative claims 1, and 4 are marked up, isolating the abstract idea from additional elements, wherein the abstract idea is in bold and the additional elements have been italicized as follows:
Claim 1: A system for evaluating a user demeanor and authenticity within an online social networking platform, the system (100) comprises:
a. a profile ring feature module (102) configured to exhibit a profile ring on a profile of each user, wherein the profile ring serves as an indicator within an online social networking platform (101), reflecting the user’s degrees of demeanor and authenticity in real time;
b. a user activity tracking module (103) configured to generate one or more signals derived from a plurality of actions executed by one or more users on the online social networking platform (101), wherein the signals are utilized for the computation of a user’s behavioral score for determining a color of the profile ring; and
c. a notification module (104) configured to provide plurality of real time notifications to the user upon detecting variations in the color of the profile ring, wherein the color variations of the profile ring indicate modifications in the user’s degrees of demeanor and authenticity.
Claim 4: A method for evaluating a user demeanor and authenticity within an online social networking platform, the method (200) comprising the steps of: a. generating one or more signals derived from a plurality of actions executed by the users on the online social networking platform (201); b. computing a user’s behavioral score based on the nature and extent of the user’s engagement activities utilizing the signals (202); c. determining a color of a profile ring through the utilization of the user’s behavioral score, wherein the color of the profile ring serves as an indicator within an online social networking platform, reflecting the user’s degrees of demeanor and authenticity (203); and d. providing real time notifications to the user upon detecting variations in the color of the profile ring, wherein the color variations indicate modifications in the user’s degrees of demeanor and authenticity (204).
When evaluating the bolded limitations of the claims under the broadest reasonable interpretation in light of the specification, it is clear that representative claims 1, and 4 recite an abstract idea within the category of “certain methods of organizing human activity.” More specifically, the present invention falls under the sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions as outlined in MPEP 2106.04(a)(2)(II)(C). In this case, the instant claims in bold recite steps of “evaluating a user demeanor and authenticity within a social networking platform, displaying a profile ring which serves as an indicator of the user’s degree of demeanor and authenticity, generate dataset based on user interactions to compute a behavioral score to determine the color of the profile ring, and provide notifications when the color ring changes.” These steps are merely data collection, data processing, and data display steps to perform the abstract idea of managing personal behavior or relationships or interactions between individuals. Analyzing a user’s behavior on a social networking platform and display an indication of their behavior to other user’s on the social networking platform falls within “social activities, teachings, and following rules or instructions.” Therefore, these claims recite an abstract idea and are to be further analyzed under Step 2A Prong 2.
Step 2A Prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application?
Claims 1 and 4 recite the following additional elements:
-a profile ring feature module in claim 1
-a user activity tracking module in claim 1
-a notification module in claim 1
-online social networking platform in claims 1 and 4
The additional elements listed above, when considered individually and in combination with the claim as a whole, no more than a recitation of the words “apply it” (or an equivalent) or mere instructions to implement an abstract idea or other exception on generic computing components as outlined in MPEP 2106.05(f). In this case, the abstract idea of “evaluating a user demeanor and authenticity within a social networking platform, displaying a profile ring which serves as an indicator of the user’s degree of demeanor and authenticity, generate dataset based on user interactions to compute a behavioral score to determine the color of the profile ring, and provide notifications when the color ring changes” is being performed on generic computing components such as modules. Furthermore, limiting the social networking platform to be “online” is merely an indication that the social networking platform exists on a computer, which does not amount to more than merely that the abstract idea should be applied on the internet. This could also be considered a general link to a field of us or technological environment as outlined in MPEP 2106.05(h), since it merely indicates applying the abstract idea on an online technological environment without meaningfully limiting its implementation. Therefore the additional elements do not integrate the claim into a practical application.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Claims 1 and 4 recite the following additional elements:
-a profile ring feature module in claim 1
-a user activity tracking module in claim 1
-a notification module in claim 1
-online social networking platform in claims 1 and 4
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using modules to perform the steps associated with the abstract idea, amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Similarly, generally linking the abstract idea to an online technological environment does not meaningfully limit the claim to provide an inventive concept according to MPEP 2106.05(h) Accordingly, even when viewed as a whole, nothing in the claim adds significantly more (i.e. an inventive concept) to the abstract idea. Thus claims 1 and 4 are not patent eligible because the claims are directed to an abstract without significantly more.
Regarding dependent claims 2, 3, 5:
Claim 2 further defines the abstract idea by adding another step to the user activity tracking module which utilizes the behavioral score based on the nature and extend of the user’s engagement activities. Whether analyzed individually or combination, this is more of the same abstract idea because it merely analyzes user engagement activities(user interactions), when considering the behavioral score. The additional element “user activity tracking module” is still an indication of “apply it” or performing the abstract idea on generic computing components. Therefore the claims are still directed to an abstract idea without integration into a practical application or significantly more.
Claim 3 further defines the abstract idea by adding another step to the profile ring feature module which enables visibility of the profile ring to other users, the color of the profile ring indicating the computed behavioral score. Whether analyzed individually or combination, this is more of the same abstract idea because it merely facilitates the display of the profile data to other parties, which is a form of managing personal behavior or interactions between individuals. The additional element “profile ring feature module” is still an indication of “apply it” or performing the abstract idea on generic computing components. Therefore the claims are still directed to an abstract idea without integration into a practical application or significantly more.
Claim 5 further limits the abstract idea by defining what is included in “user’s engagement activities” to include “user’s historical behavior, quality of posts, content posted, analysis of affective state, instances of being blocked by other users, and positive ratings provided by other users for computing the behavioral score and determining the color of the profile ring.” This is more of the same abstract idea because even when substituting these elements into the representative claims, the claims still recite managing personal behavior or interactions between individuals. Furthermore, there are no further additional elements to consider therefore the claims are still directed to an abstract idea without integration into a practical application or significantly more.
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 1-4 are rejected under 35 U.S.C. 103 as being unpatentable over Highman et al. (US 20220237318 A1) hereinafter Highman in view of Dwyer et al. (US 20150195406 A1) hereinafter Dwyer.
Regarding Claim 1:
Highman discloses a method of creating a trust profile by gathering information about a user, assessing the collected information, providing a trust score, and displaying the profile with a color coded ring reflecting the trust. Highman teaches:
A system for evaluating a user authenticity within an online social networking platform, the system (100) comprises: (Highman [0003] A user can create a “trust” or “risk” profile that provides a trust score based on various factors that are included as part of an overall assessment. For example, user data may be based on public and private records, including civil, criminal and other legal proceedings, biographic information, financial records, academic records and other relevant data. [0010] The trust profile may include information regarding identity verification, criminal record status and civil record status and credential status information.) Authenticity is mapped to “trust” in Highman, and since Highman discloses sharing the trust profile with other users on a platform, the limitation has been taught.
-a. a profile ring feature module (102) configured to exhibit a profile ring on a profile of each user, (Highman [0009] The trust profile may be displayed with at least a portion of a circular ring that varies in length according to the trust score. A portion of the circular ring further may include a color code that varies according to the trust score. [0092] The evaluator enter a separately sent validation code to view the user’s profile. The profile is displayed with a picture of the user, the risk score and a color-coded ring.)
-wherein the profile ring serves as an indicator within an online social networking platform (101),
reflecting the user’s degrees of authenticity in real time; (Highman [0050] The user 28 may send their trust score or trust profile to an evaluator 30 or the user 28 may post the score on, for example, on a social media account, website or biographic profile. The data that is evaluated may be, for example, identity verification, criminal record, civil record, and credential verification. The evaluator 30 may be for various types of relationships, such as, for example, employer-employee, sports league-coaching position, potential intimate relationship, etc. [0084] Referring to FIGS. 15A-15C, once the user’s data and profile are complete, the user may share their trust information with another person or entity. The user is prompted to identify the reason for sharing. For example, the user may specify that sharing is for home and family services, professional services, a personal relationship or unspecified.) Highman’s trust score is mapped to “user’s degree of authenticity.” Since “real time” is not specifically defined in the specification, the ability to share trust information that reflects the trust profile satisfies the ”real time” limitation.
-b. a user activity tracking module (103) configured to generate one or more signals, (Highman [0047] The data source 24 may be a database, electronic documents, the internet, paper files, and the like. The trust assessment module may convert the personal information and risk information to an assessment to provide a trust or risk score. For example, if a job applicant has a criminal background, each criminal charge, disposition, and punishment may be quantified and included in the total score. Risk information may be converted from unstructured data sources 24 using a non-standard data vocabulary and complex data semantics to assessment information using standardized vocabulary and values. The memory may store the personal information, the risk information, and/or the assessment information on the computer.) Highman’s conversion of the unstructured data sources into assessment information is a generation of signals.
-wherein the signals are utilized for the computation of a user’s trust score for determining a color of the profile ring; and (Highman [0048] The personal and risk/trust information may be converted to a trust assessment or trust score using an algorithm by the trust assessment module 20. The algorithm may use logical expressions to automatically convert unstructured text into numeric values which are then used in an overall quantification. [0009] The trust profile may be displayed with at least a portion of a circular ring that varies in length according to the trust score. A portion of the circular ring further may include a color code that varies according to the trust score. [0071] The home page can be formatted for desktop 220, tablet 222, or mobile 224 layouts. Information included on the home page includes the user’s image surrounded by a color-coded circle and a numerical risk score. The home page communicates the risk score, shows the latest state of their profile and prompts the user to complete various data processing tasks.)
However, Highman fails to teach:
-Evaluating a user demeanor/degree of demeanor (Highman only discloses a trust score but not specifically evaluate the demeanor or behavioral characteristics)
-signals derived from a plurality of actions executed by one or more users on the social networking platform (Highman’s metrics for calculating the trust score do not involve social media engagements)
-the signals are utilized for computation of a user’s behavioral score for determing a color of the ring (Highman’s trust score determines the color of the ring.)
- c. a notification module (104) configured to provide plurality of real time notifications to the user upon detecting variations in the color of the profile ring,
-wherein the color variations of the profile ring indicate modifications in the user’s degrees of demeanor and authenticity.
Alternatively, Dwyer discloses a system for analyzing communications and dynamically providing a graphical representation of the scores based on the communications, which Dwyer primarily applies to live calls, but can also be applied to social media posts. Dwyer teaches:
-Evaluating a user demeanor/degree of demeanor (Dwyer [0155] In addition to the agent assistant providing behavioral feedback to the user, such as through color-ring indicators and textual messages, the agent assistant may provide for information in response to key words or phrases from the caller or the absence of key words/phrases, such as in information provided in `pop-ups` or `fly-outs`. [0099] One category may be behaviors, for example, how agents or customers are behaving. For example, are customers expressing dissatisfaction, and is there an empathetic response to that dissatisfaction. Various language patterns, keywords, phrases, or other characteristics associated with the overall feel of `dissatisfaction` may be included in a list for the category. When the listed item appears in the communication, the `dissatisfaction` tag may be applied. [0116] Various index scores, such as emotion score, agent quality score, agent quality—customer service, customer satisfaction, and compliance risk are shown. Various other index scores, individual behavior scores or other measures may be shown in this view.) The evaluation of behavior in Dwyer teaches the limitation above.
-signals derived from a plurality of actions executed by one or more users on the social networking platform (Dwyer [0095] With respect to data sources, the conversational analytics system may work with many data sources, regardless of the specific call recording system or combination of call recording systems, or sources of text contacts (e.g., voice, text, email, SMS, chat, blog, social network posts, and the like). [0096] In embodiments, a customer “call” center system may comprise a plurality of channels for receiving heterogeneous customer input to an enterprise, such as: phone calls to a call center; phone calls to an agent; voice mail; on-line chat; e-mail; blogs; surveys; Facebook; Twitter; Google+; other social channels; IVR; and the like. Customer input received as a vocal stream may be translated to text using a variety of speech analysis techniques such as phonetics, LVSCR, and the like. The translated text may be analyzed and the text categorized and scored. The customer input received as text may be analyzed and the text categorized and scored.)
-the signals are utilized for computation of a user’s behavioral score to determine a color of the ring (Dwyer [0018] Various other index scores, individual behavior scores or other measures may be shown in this view. [0118] For example, particular ranges of scores may be associated with a description. In the example of FIG. 16, a score through 79 indicates the suspected emotion, a score from 79 to 80 indicates normal emotion, and any score above 80 indicates calm. The user may define any number of ranges. Each score range may also be associated with a particular color when displayed to a user [0154] One example of the graphical indicator of the agent assistant is illustrated in FIG. 9, where color-coded rings surround an alert message area, where the alert message area displays messages to the agent, and the colored rings provide indicators of how the call is going. For instance, one colored ring may represent a `call temperature gauge`, showing through a color indicator of the emotional state of the caller as based on real-time language and/or acoustics analytics and scoring, such as green indicating a default condition where the caller is calm and the call is going well, orange indicating something has changed either in the acoustic characteristic of the caller’s voice or in the language they are using, and red indicating the caller is now taking actions or has a tone that may indicate they are agitated, upset, and the like, and where the agent needs to take counter-acting measures.) Dwyer also teaches a mood ring which displays different colors based on behavioral metrics.
- c. a notification module (104) configured to provide plurality of real time notifications to the user upon detecting variations in the color of the profile ring, (Dwyer [0124] Performance feedback is delivered as continuous, plain language alerts and notifications, [0154] The agent assistant may be provided on each agent’s desktop to provide real-time alerts, next-best-action guidance to the agent (e.g. links to relevant information or advice when certain items of interest occur on the call, for example: a technical issue with a product or a specific objection to an agent offer), and the like. One example of the graphical indicator of the agent assistant is illustrated in FIG. 9, where color-coded rings surround an alert message area, where the alert message area displays messages to the agent, and the colored rings provide indicators of how the call is going… Through the agent assistant, the agent may receive various textual and/or graphical feedback indicators to help them adjust to the changing behavior of the caller, thus improving the performance of the agent in handling the needs of the caller. In one embodiment, the outer ring changes color based on the tone of the call. If the color gets to “red”, it shakes itself to calm down the agent. Acoustically, volume, tone, and agitation (which itself is a measure of tempo, volume, and stress) may be visually displayed in one of the rings, such as the outer ring, of the assistant and optionally displayed as the actual score in the ring such as the center of the ring. Another ring, such as the inner ring, may change color based on violations and to provide an alert. A portion of the mood ring may present an alert message.) Dwyer’s provision of alerts when the mood ring changes color is mapped to the limitation.
-wherein the color variations of the profile ring indicate modifications in the user’s degrees of demeanor. (Dwyer [0154] For instance, one colored ring may represent a `call temperature gauge`, showing through a color indicator of the emotional state of the caller as based on real-time language and/or acoustics analytics and scoring, such as green indicating a default condition where the caller is calm and the call is going well, orange indicating something has changed either in the acoustic characteristic of the caller’s voice or in the language they are using, and red indicating the caller is now taking actions or has a tone that may indicate they are agitated, upset, and the like, and where the agent needs to take counter-acting measures. Another colored ring may represent an alert indicator that indicates the need to take actions by the agent, such as similarly indicated by different colors, augmented with alert messages, and the like. A ring may change color as the tone of the caller’s voice changes, such as from green when there was silence, to yellow as the caller spoke louder, and finally red when the caller became agitated. For example, after the caller had spoken loudly and quickly for several seconds, a high agitation warning may be shown, such as by color ring indication and/or a textual alert message. Not only can the agent’s assistant detect agitation/stress and other emotional states, but it can detect other acoustic events like silence or over-talk.) The changes in color is an indication of changes in the user’s demeanor.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Highman by adding the behavioral analysis of Dwyer, including changing the color of the ring based on a change in demeanor/behavior, and providing notifications when a change has occurred. This combination would yield the predictable result of providing a profile ring that is based both on behavior and trust scores, based on the actions of the user on a social media platform. One of ordinary skill would have been motivated to perform the combination as it has the benefit of accurately assessing a person’s behavior in real time. (Dwyer [0005])
Regarding Claim 2:
The combination of Highman and Dwyer teach or suggest the system as claimed in claim 1,
Highman teaches:
-utilizing the user’s trust score based on the trust information to determine the color of the profile ring. (Highman [0048] The personal and risk/trust information may be converted to a trust assessment or trust score using an algorithm by the trust assessment module 20. The algorithm may use logical expressions to automatically convert unstructured text into numeric values which are then used in an overall quantification. [0009] The trust profile may be displayed with at least a portion of a circular ring that varies in length according to the trust score. A portion of the circular ring further may include a color code that varies according to the trust score.)
However, Highman fails to disclose:
-wherein the user activity tracking module utilizes the user’s behavioral score based on the nature and extent of the user’s engagement activities for determining the color of the profile ring.
Alternatively, Dwyer discloses:
-wherein the user activity tracking module utilizes the user’s behavioral score based on the nature and extent of the user’s engagement activities to determine the color of the ring.(Dwyer [0082] The real-time (RT) conversational analytics facility enables automatically evaluating in real-time or near real-time every communication (of heterogeneous types (e.g., voice, phone call [either to the call center or direct dialed to an agent], voicemail, chat, e-mail, blog, survey, Facebook, Twitter, Google+, other social channels, IVR, etc.) related to an activity, such as an activity of an enterprise, including in-progress calls, for sentiment/acoustics, categorization, and performance scoring, including the presence or absence of specific language or acoustic characteristics, utilizing acoustic and conversational analysis to convert communications to a text format for inclusion in a single database repository that includes fields for data relating to, at least, speech analysis/audio mining of spoken communications. The communications may be routed to a centralized host or handled by distributed computing systems in various embodiments disclosed herein or via a cloud-based system. The raw, unstructured data of recorded or real-time conversations is converted into consumable, structured data. Audio conversations are ingested by the system along with call metadata and speech-to-text transcription is performed to generate a transcript that is analyzed using a set of linguistic and acoustic rules to look for certain key words, phrases, topics, and acoustic characteristics. [0082] The conversational analytics system allows for evaluation and comparison of performance and key metrics using data visualization. The conversational analytics system enables determining root cause through auto topic analysis and automatically identifying outliers. Output of text conversion/ sentiment/acoustics analysis of customer conversations and associated metadata from any source communication system (call recorders, chat systems, emails, social posts (e.g. twitter, Facebook), SMS, Blogs and Surveys, etc.) and across multiple contact center sites and locations are stored in a database for a three step process that can be a cloud-based or an on premise call center monitoring solution that is scalable: (i) categorization; (ii) scoring; (iii) auto-analytics. A plurality of category labels are assigned for topics throughout the communication (e.g. Greeting, ID+verification, Behavior/emotions, Procedure discussed, Competitor, Churn, Likelihood for upsell/cross-sell, Agent performance, Customer satisfaction, Credit card (mention CCV code), custom categories, custom sets of categories, search-based categories).) Dwyer’s sentiment analysis is an example of the nature of the user’s engagement activities, and the scoring of the interactions is an example of an “extent.”
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Highman by evaluating a behavioral score based on a nature and extent of user’s engagement activities such as social media post as taught by Dwyer. One of ordinary skill in the art would have been motivated to make this combination as it would provide the benefit of accurately assessing one’s behavior. (Dwyer [0086])
Regarding Claim 3:
The combination of Highman and Dwyer teach or suggest the system as claimed in claim 1,
Furthermore, Highman teaches:
-wherein the profile ring feature module (102) facilitates visibility of the profile ring by other users, thereby enabling the other users to make one or more informed determinations based on the color of the profile ring associated with the user. (Highman [0004] The system allows a user to develop a “trust” profile that can be shared with others, such as, for example, potential employers. The user has complete control of their (used as singular or plural herein) data in terms of what is shared, the time period that it can be shared and with persons or entities that it can be shared with. [0045] The data aggregation module 18 may receive, at the computer, user account information and risk/authentication regarding the user 28 according to the personal information from the data sources 24. As used herein, the term “risk information” refers to any quantifiable information that may be considered as indicative of risk for a person or other entity. For example, risk information may include criminal history, civil history, terrorist watch lists, traffic violations, loan or debt delinquencies, outstanding wants or warrants, academic disciplinary history, and/or immigration status. Risk information may also include accusations relating to the previously mentioned types of risks. For example, a security company may want to know whether potential employees have a criminal record. In this example, risk information could include, among other things, any information that relates to the criminal history of a job applicant.)
-the color of the profile ring indicating the computed behavioral score, (Highman [0009] The trust profile may be displayed with at least a portion of a circular ring that varies in length according to the trust score. A portion of the circular ring further may include a color code that varies according to the trust score.) Since the trust score is now based on a combination of authenticity and behavioral measures from Dwyer, the color of the ring being based on the trust score, satisfies the limitation.
Regarding Claim 4:
Highman teaches:
-A method for evaluating a user authenticity within an online social networking platform, the method (200) comprising the steps of: (Highman [0003] A user can create a “trust” or “risk” profile that provides a trust score based on various factors that are included as part of an overall assessment. For example, user data may be based on public and private records, including civil, criminal and other legal proceedings, biographic information, financial records, academic records and other relevant data. [0010] The trust profile may include information regarding identity verification, criminal record status and civil record status and credential status information.) Authenticity is mapped to “trust” in Highman, and since Highman discloses sharing the trust profile with other users on a platform, the limitation has been taught.
-a. generating one or more signals; (Highman [0047] The data source 24 may be a database, electronic documents, the internet, paper files, and the like. The trust assessment module may convert the personal information and risk information to an assessment to provide a trust or risk score. For example, if a job applicant has a criminal background, each criminal charge, disposition, and punishment may be quantified and included in the total score. Risk information may be converted from unstructured data sources 24 using a non-standard data vocabulary and complex data semantics to assessment information using standardized vocabulary and values. The memory may store the personal information, the risk information, and/or the assessment information on the computer.) Highman’s conversion of the unstructured data sources into assessment information is a generation of signals.
-b. computing a user’s trust score based on the signals (202); (Highman [0048] The personal and risk/trust information may be converted to a trust assessment or trust score using an algorithm by the trust assessment module 20. The algorithm may use logical expressions to automatically convert unstructured text into numeric values which are then used in an overall quantification.)
-c. determining a color of a profile ring through the utilization of the user’s trust score, (Highman [0009] The trust profile may be displayed with at least a portion of a circular ring that varies in length according to the trust score. A portion of the circular ring further may include a color code that varies according to the trust score. [0071] The home page can be formatted for desktop 220, tablet 222, or mobile 224 layouts. Information included on the home page includes the user’s image surrounded by a color-coded circle and a numerical risk score. The home page communicates the risk score, shows the latest state of their profile and prompts the user to complete various ’ata processing tasks.)
-wherein the color of the profile ring serves as an indicator within an online social networking platform, reflecting the user’s degrees of authenticity (203); and (Highman [0050] The user 28 may send their trust score or trust profile to an evaluator 30 or the user 28 may post the score on, for example, on a social media account, website or biographic profile. The data that is evaluated may be, for example, identity verification, criminal record, civil record, and credential verification. The evaluator 30 may be for various types of relationships, such as, for example, employer-employee, sports league-coaching position, potential intimate relationship, etc. [0084] Referring to FIGS. 15A-15C, once the user’s data and profile are complete, the user may share their trust information with another person or entity. The user is prompted to identify the reason for sharing. For example, the user may specify that sharing is for home and family services, professional services, a personal relationship or unspecified.) Highman’s trust score is mapped to “user’s degree of authenticity.”
Highman fails to teach:
-Evaluating a user demeanor/degree of demeanor (Highman only discloses a trust score but not specifically evaluate the demeanor or behavioral characteristics)
-signals derived from a plurality of actions executed by one or more users on the social networking platform (Highman’s metrics for calculating the trust score do not involve social media engagements)
-b. computing a user’s behavioral score based on the nature and extent of the user’s engagement activities utilizing the signals (202);
-determining the color of the profile ring through the utilization of the user’s behavioral score.
- d. providing real time notifications to the user upon detecting variations in the color of the profile ring,
-wherein the color variations indicate modifications in the user’s degrees of demeanor and authenticity.
Alternatively, Dwyer teaches:
-Evaluating a user demeanor/degree of demeanor. (Dwyer [0155] In addition to the agent assistant providing behavioral feedback to the user, such as through color-ring indicators and textual messages, the agent assistant may provide for information in response to key words or phrases from the caller or the absence of key words/phrases, such as in information provided in `pop-ups` or `fly-outs`. [0099] One category may be behaviors, for example, how agents or customers are behaving. For example, are customers expressing dissatisfaction, and is there an empathetic response to that dissatisfaction. Various language patterns, keywords, phrases, or other characteristics associated with the overall feel of `dissatisfaction` may be included in a list for the category. When the listed item appears in the communication, the `dissatisfaction` tag may be applied. [0116] Various index scores, such as emotion score, agent quality score, agent quality—customer service, customer satisfaction, and compliance risk are shown. Various other index scores, individual behavior scores or other measures may be shown in this view.) The evaluation of behavior in Dwyer teaches the limitation above.
-signals derived from a plurality of actions executed by one or more users on the social networking platform (Dwyer [0095] With respect to data sources, the conversational analytics system may work with many data sources, regardless of the specific call recording system or combination of call recording systems, or sources of text contacts (e.g., voice, text, email, SMS, chat, blog, social network posts, and the like). [0096] In embodiments, a customer “call” center system may comprise a plurality of channels for receiving heterogeneous customer input to an enterprise, such as: phone calls to a call center; phone calls to an agent; voice mail; on-line chat; e-mail; blogs; surveys; Facebook; Twitter; Google+; other social channels; IVR; and the like. Customer input received as a vocal stream may be translated to text using a variety of speech analysis techniques such as phonetics, LVSCR, and the like. The translated text may be analyzed and the text categorized and scored. The customer input received as text may be analyzed and the text categorized and scored.)
-b. computing a user’s behavioral score based on the nature and extent of the user’s engagement activities utilizing the signals (202); (Dwyer [0082] The real-time (RT) conversational analytics facility enables automatically evaluating in real-time or near real-time every communication (of heterogeneous types (e.g., voice, phone call [either to the call center or direct dialed to an agent], voicemail, chat, e-mail, blog, survey, Facebook, Twitter, Google+, other social channels, IVR, etc.) related to an activity, such as an activity of an enterprise, including in-progress calls, for sentiment/acoustics, categorization, and performance scoring, including the presence or absence of specific language or acoustic characteristics, utilizing acoustic and conversational analysis to convert communications to a text format for inclusion in a single database repository that includes fields for data relating to, at least, speech analysis/audio mining of spoken communications. The communications may be routed to a centralized host or handled by distributed computing systems in various embodiments disclosed herein or via a cloud-based system. The raw, unstructured data of recorded or real-time conversations is converted into consumable, structured data. Audio conversations are ingested by the system along with call metadata and speech-to-text transcription is performed to generate a transcript that is analyzed using a set of linguistic and acoustic rules to look for certain key words, phrases, topics, and acoustic characteristics. [0082] The conversational analytics system allows for evaluation and comparison of performance and key metrics using data visualization. The conversational analytics system enables determining root cause through auto topic analysis and automatically identifying outliers. Output of text conversion/ sentiment/acoustics analysis of customer conversations and associated metadata from any source communication system (call recorders, chat systems, emails, social posts (e.g. twitter, Facebook), SMS, Blogs and Surveys, etc.) and across multiple contact center sites and locations are stored in a database for a three step process that can be a cloud-based or an on premise call center monitoring solution that is scalable: (i) categorization; (ii) scoring; (iii) auto-analytics. A plurality of category labels are assigned for topics throughout the communication (e.g. Greeting, ID+verification, Behavior/emotions, Procedure discussed, Competitor, Churn, Likelihood for upsell/cross-sell, Agent performance, Customer satisfaction, Credit card (mention CCV code), custom categories, custom sets of categories, search-based categories).) Dwyer’s sentiment analysis is an example of the nature of the user’s engagement activities, and the scoring of the interactions is an example of an “extent.”
-determining the color of the profile ring through the utilization of the user’s behavioral score. (Dwyer [0018] Various other index scores, individual behavior scores or other measures may be shown in this view. [0118] For example, particular ranges of scores may be associated with a description. In the example of FIG. 16, a score through 79 indicates the suspected emotion, a score from 79 to 80 indicates normal emotion, and any score above 80 indicates calm. The user may define any number of ranges. Each score range may also be associated with a particular color when displayed to a user [0154] One example of the graphical indicator of the agent assistant is illustrated in FIG. 9, where color-coded rings surround an alert message area, where the alert message area displays messages to the agent, and the colored rings provide indicators of how the call is going. For instance, one colored ring may represent a `call temperature gauge`, showing through a color indicator of the emotional state of the caller as based on real-time language and/or acoustics analytics and scoring, such as green indicating a default condition where the caller is calm and the call is going well, orange indicating something has changed either in the acoustic characteristic of the caller’s voice or in the language they are using, and red indicating the caller is now taking actions or has a tone that may indicate they are agitated, upset, and the like, and where the agent needs to take counter-acting measures.) Dwyer also teaches a mood ring which displays different colors based on behavioral metrics.
- d. providing real time notifications to the user upon detecting variations in the color of the profile ring, (Dwyer [0124] Performance feedback is delivered as continuous, plain language alerts and notifications, [0154] The agent assistant may be provided on each agent’s desktop to provide real-time alerts, next-best-action guidance to the agent (e.g. links to relevant information or advice when certain items of interest occur on the call, for example: a technical issue with a product or a specific objection to an agent offer), and the like. One example of the graphical indicator of the agent assistant is illustrated in FIG. 9, where color-coded rings surround an alert message area, where the alert message area displays messages to the agent, and the colored rings provide indicators of how the call is going… Through the agent assistant, the agent may receive various textual and/or graphical feedback indicators to help them adjust to the changing behavior of the caller, thus improving the performance of the agent in handling the needs of the caller. In one embodiment, the outer ring changes color based on the tone of the call. If the color gets to “red”, it shakes itself to calm down the agent. Acoustically, volume, tone, and agitation (which itself is a measure of tempo, volume, and stress) may be visually displayed in one of the rings, such as the outer ring, of the assistant and optionally displayed as the actual score in the ring such as the center of the ring. Another ring, such as the inner ring, may change color based on violations and to provide an alert. A portion of the mood ring may present an alert message.) Dwyer’s provision of alerts when the mood ring changes color is mapped to the limitation.
-wherein the color variations indicate modifications in the user’s degrees of demeanor and authenticity. (Dwyer [0154] For instance, one colored ring may represent a `call temperature gauge`, showing through a color indicator of the emotional state of the caller as based on real-time language and/or acoustics analytics and scoring, such as green indicating a default condition where the caller is calm and the call is going well, orange indicating something has changed either in the acoustic characteristic of the caller’s voice or in the language they are using, and red indicating the caller is now taking actions or has a tone that may indicate they are agitated, upset, and the like, and where the agent needs to take counter-acting measures. Another colored ring may represent an alert indicator that indicates the need to take actions by the agent, such as similarly indicated by different colors, augmented with alert messages, and the like. A ring may change color as the tone of the caller’s voice changes, such as from green when there was silence, to yellow as the caller spoke louder, and finally red when the caller became agitated. For example, after the caller had spoken loudly and quickly for several seconds, a high agitation warning may be shown, such as by color ring indication and/or a textual alert message. Not only can the agent’s assistant detect agitation/stress and other emotional states, but it can detect other acoustic events like silence or over-talk.) The changes in color is an indication of changes in the user’s demeanor.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Highman by adding the behavioral analysis of Dwyer, including changing the color of the ring based on a change in demeanor/behavior, and providing notifications when a change has occurred. This combination would yield the predictable result of providing a profile ring that is based both on behavior and trust scores, based on the actions of the user on a social media platform. One of ordinary skill would have been motivated to perform the combination as it has the benefit of accurately assessing a person’s behavior in real time. (Dwyer [0005])
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Highman (US 20220237318 A1) in view of Dwyer (US 20150195406 A1) further in view of Rohrweck et al. (US 9824145 B1) hereinafter Rohrweck
The combination of Highman and Dwyer teach or suggest The method as claimed in claim 4:
Furthermore, Highman teaches:
- determining the color of the profile ring. (Highman [0009] The trust profile may be displayed with at least a portion of a circular ring that varies in length according to the trust score. A portion of the circular ring further may include a color code that varies according to the trust score.)
However, Highman fails to disclose:
- wherein the user’s engagement activities include the user’s historical behavior, quality of posts, content posted, analysis of affective state, instances of being blocked by other users, and positive ratings provided by other users for determining the color of the profile ring.
Alternatively, Dwyer teaches: - wherein the user’s engagement activities include the user’s historical behavior, (Dwyer [0027] In an aspect, a method of call classification capable of automated AB testing utilizing historical data may include creating two or more categories of calls, which differ in value for an identified piece of metadata, identifying similarities between calls within each group, and identifying differences between groups. The input may be one of phone call, voice mail, VOIP, Chat, Email, SMS, Twitter, Facebook, Blogs and Surveys. Displaying all inputs may include displaying a chart of metadata over time.)
-quality of posts, (Dwyer [0098] With respect to accuracy, simple transcription accuracy may be a variable based on a number of influencing factors such as quality of the recording, mono versus stereo recording mode, voice transmission type (i.e. SIP or TDM), headset quality, accents, and the like.)
-content posted, (Dwyer [0082] The present disclosure describes a real-time (RT) conversational analytics facility that provides conversational analytics and real-time, or near real-time monitoring of communications from multiple channels, such as phone calls, chats, text messaging, blog posts, social media posts,)
-analysis of affective state for determining the color of the ring. (Dwyer [0012] In an aspect, a non-transitory computer readable medium may include an executable program for emotional analysis of text communications, wherein the program instructs a microprocessor to perform the following steps: receiving a text communication, analyzing the text communication in real time for non-word symbols within the text that mimic verbal elements, and determining at least one emotional state indicator of the sender from the analysis. The steps may further include providing a dynamic graphical representation of the at least one emotional state indicator through a graphical user interface. Analysis of incoming text may include analysis of non-word symbols such as emoticons, capitalization, punctuation, ellipses, and spacing. The steps may further include storing the incoming text and the one or more emotional states in a searchable database. [0118] Each score range may also be associated with a particular color when displayed to a user. At least one score range made be identified as the target range outside of which an alert may possibly be generated. The user may indicate if the emotion score should be displayed as a numerical score, as the text description, as a color, some combination of any of the above, or the like.) Dwyer’s emotional analysis is an example of an analysis of an affective state.
- computing the behavioral score and (Dwyer [0018] Various other index scores, individual behavior scores or other measures may be shown in this view. [0118] For example, particular ranges of scores may be associated with a description. In the example of FIG. 16, a score through 79 indicates the suspected emotion, a score from 79 to 80 indicates normal emotion, and any score above 80 indicates calm. The user may define any number of ranges. Each score range may also be associated with a particular color when displayed to a user [0154] One example of the graphical indicator of the agent assistant is illustrated in FIG. 9, where color-coded rings surround an alert message area, where the alert message area displays messages to the agent, and the colored rings provide indicators of how the call is going. For instance, one colored ring may represent a `call temperature gauge`, showing through a color indicator of the emotional state of the caller as based on real-time language and/or acoustics analytics and scoring, such as green indicating a default condition where the caller is calm and the call is going well, orange indicating something has changed either in the acoustic characteristic of the caller’s voice or in the language they are using, and red indicating the caller is now taking actions or has a tone that may indicate they are agitated, upset, and the like, and where the agent needs to take counter-acting measures.) Dwyer also teaches a mood ring which displays different colors based on behavioral metrics.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Highman by adding user’s historical behavior, quality of posts, content posted, and analysis of effective state as metrics for determining the color of the ring. One of ordinary skill in the art would have been motivated to perform this combination as it would provide the benefit of tracking a wide variety of metrics to produce a behavioral score. (Dwyer [0083])
However, neither Highman nor Dwyer teach:
-instances of being blocked by other users, and positive ratings provided by other users.
Alternatively, Rohrweck discloses a method for generating a user score based on feedback from other users to indicate the reputation of the users. Rohrweck teaches:
-instances of being blocked by other users, and (Rohrweck [Col. 10 Lines 34-49] For example, the analysis may determine reputation of a reporting user as a malicious user or a reputable user by determining characteristics of the interaction limitations generated by other users as it relates to the interactions feedback of the reporting user. Some example characteristics include the number of times the feedback from the reporting user was muted by other users, the number of times the reporting user’s feedback comment was removed by other users, the number of times a post/comment/message of the reporting user was flagged by other users, the number of times the reporting user’s profile was reported by other users as well as such reports per user ratio, the number of times the reporting user’s comments, posts, messages were deleted or redacted by the social service provider, the number of times the reporting user was blocked by other users, etc.)
-positive ratings provided by other users. (Rohrweck [Col.13 Lines 10-24] The user score and ranking identify which ones of the users in the user base are malicious or abusive users and which ones are reputable users. For example, in some implementations illustrated in box 317 of FIG. 3, users with a lower user score, for e.g., a user score less than 4.0, are indicated to have higher ranking and considered to be reputable and users with higher user score, for e.g., a user score that is greater than 4.0, are indicated to have lower ranking and considered to be malicious, abusive or otherwise less reputable. In alternative implementations, the higher user score (for e.g., greater than 4.0) may be associated with reputable users and the lower user score may be associated with less reputable users. The aforementioned forms of determining the ranking is an example and other forms of determining the ranking of users may be employed. [Col. 14 Lines 15-18]The signal to noise ratio essentially determines the ratio of number of good reporting versus number of bad reporting in the signals generated by the particular user.) The users are rated based on the amount of good reports they receive versus bad reports from other users.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to further modify Highman by adding instance of being blocked by other users, and positive ratings from other users as engagement metrics to analyze a user’s reputation as taught by Rohrweck. One of ordinary skill would have been motivated to make this combination as it would provide the benefit of improving the user experience of reputable users of the platform. (Rohrweck [Col. 4 Line 50- Col. 5 Line 16])
Response to Arguments
The applicant’s remarks filed on 08/29/2025 have been fully considered.
Regarding applicant’s arguments over claim interpretation under 112(f), spanning pages 4-5 of the applicant’s remarks, the examiner acknowledges that the applicant’s responses consist of providing support from the specification for the profile ring feature module as recited in claim 1, user activity tracking module as recited in claim 1, and notification module recited in claim 1. The examiner respectfully agrees that support in the specification does exist for these claims interpreted under 112(f), however, the examiner notes that 112(f) is not a rejection. The claim interpretation under 112(f) merely sets the record that the claims, which lack supporting structure in the claims, are interpreted to cover the corresponding structure in the specification. Since adequate support has been found in the specification, this interpretation does not result in a 112(a) or 112(b) rejection. However, the claim interpretation under 112(f) stands because the claims have not been amended to include adequate corresponding structure in the claims. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Regarding applicant’s remarks over claim rejections under 112(b) on page 6 of the applicant’s remarks, the examiner acknowledges that the amendments overcome the rejection and withdraws the 112(b) rejection.
Regarding applicant’s arguments over claim rejections under 35 U.S.C. 101 from pages 7-16, the examiner has acknowledged all of the applicant’s arguments but does find them persuasive for the following reasons.
Regarding the rejection of claims 1-3 for being directed to non-statutory subject matter, the rejection stands because the applicant has only provided examples from the specification [0022-0024] that provide the corresponding structure, however, these sections do not specifically limit the scope of “modules” from mere software per se embodiments. In regards to the applicant’s arguments in page 8, the applicant’s arguments regarding improving the functioning of the social networking platform are not relevant to the discussion of non-statutory subject matter. Therefore, none of the applicant’s arguments regarding the rejection of claims 1-3 over being directed to non-statutory subject matter are persuasive and thus the rejection stands. Please see MPEP 2106.03(I) for more information on statutory subject matter, particularly “software per se.”
Regarding the rejection of claims 1-5 under 35 U.S.C. 101 for being directed to an abstract idea without significantly more, the examiner has considered all of arguments over Step 1 and Step 2A Prong 1 from pages 9-12, however none of them are persuasive. In response to arguments that the steps are performed by the computing infrastructure, not by the human mind, the examiner notes that these arguments are not persuasive because the claims are not categorized in the rejections as a mental process (please see MPEP 2106.04(a)(2)(III) for more information). Secondly, the steps being performed on a computing infrastructure does not automatically integrate them into a practical application, especially when the steps are merely “apply it” level elements, or mere instructions to perform the abstract idea on a generic computer. (See MPEP 2106.05(f)). The applicant’s arguments that steps such as “proactively alerting users to high-risk situations, enabling preventative action before harm occurs,” and “reducing reliance on resource-intensive retroactive moderation” together provide a technical solution to misrepresentation and low-quality engagement on online social networking platforms. However, the examiner respectfully disagrees. These alleged improvements are not technological improvements (improvements to the functioning of a computer) because they are merely abstract idea improvements being instructed to be performed on a generic computing device. MPEP 2106.05(a) states, “However, it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology.” Because the modules are interpreted as mere software implementations performed on the generic computing infrastructures in the specification, the modules are not improvements to technology (see MPEP 2106.05(a) and MPEP 2106.05(f)). These arguments by the examiner also apply to applicant’s remarks in pages 10 and 11 asserting more of the same. Furthermore in page 12, the applicant asserts that “generating signals requires technical collection of digital activity data...,” “computing a behavioral score involves processing the generating signals into numerical metrics through algorithms,” and “providing real-time notifications depends on technical messaging.” However, the examiner respectfully disagrees. None of these features provide an improvement to the functioning of a computer. According to MPEP 2106.05(f), “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” Therefore, the collection of data, computation of data, and outputting of data, as stated by the applicant is merely invoking the use of computers or other machinery as a tool to perform an existing process. Therefore, none of the applicant’s arguments in pages 9-12 are persuasive, and the examiner’s stance on Step 1 and Step 2a Prong 1 is unchanged, the claims are reciting an abstract idea.
Regarding arguments over Step 2a Prong 2 in pages 13-14, the examiner has fully considered the applicant’s arguments but does not find them persuasive. The applicant argues in page 13, that the modules recite more than generic computing, but a “specific integration of data collection, processing, and display into the technical functioning of a social networking platform.” However, the examiner respectfully disagrees, as stated above, the claims are no more than mere instructions to perform the abstract idea on a generic computing device, because “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data)” merely invokes the use of computers as a tool to perform an existing process. The applicant alleges that the integrated technical solution improves system efficiency by reducing redundant server queries, minimizes latency in status updates through push-based notifications, ensures synchronized user state across devices, and provides an always-visible UI element that encodes complex behavioral telemetry in a compact low bandwidth signal. However, this argument is not persuasive for the following reasons. These arguments set forth the improvement in a conclusory manner, a bare assertion without the detail necessary to be apparent to one of ordinary skill in the art that an improvement is claimed. MPEP 2106.05(a) states,
“If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. An indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art.”
The improvement is not apparent to one of ordinary skill in the art because the claims do not reflect the alleged improvement in their present claim scope, nor does the specification provide sufficient detail. These arguments also apply to the first paragraph of page 14 of the remarks, which further asserts that the claims improves the underlying operation of an online social networking platform, however, such improvements are not apparent to one of ordinary skill in the art. Therefore, none of the applicant’s arguments regarding step 2A prong 2 are persuasive and the examiner’s position remains unchanged, specifically that the claims are directed to an abstract idea without integration into a practical application.
Regarding applicant’s arguments over step 2B in pages 14 and 15, the examiner has fully considered the applicant’s arguments but does not find them persuasive. The applicant argues more of the same arguments as in previous sections, specifically that when “considered as a combination, the elements yield a technical improvement in online social networking platforms: behavioral signals are collected, processed into objective scores, the scores are mapped to a dynamics visual indicator (profile ring) visible to all users and real-time notifications ensure that changes in authenticity are instantly reflected across the platform” However, the examiner respectfully disagrees for the same reasons stated previously, specifically that this is no more than a recitation of the abstract idea of “managing personal behavior” but merely implemented to be performed as software tasks on generic computing devices, wherein the computer is merely invoked as a tool to perform economic tasks such as collecting, processing and outputting data. Therefore, none of the applicant’s arguments regarding step 2B are persuasive and the examiner’s position remains unchanged, specifically that the claims are directed to an abstract idea without significantly more.
Regarding arguments over dependent claims 2, 3 and 5, in page 16, the examiner has fully considered the applicant’s arguments but does not find them persuasive. Specifically, the applicant’s assertions that claim 2 provides a “technical improvement by creating a quantifiable behavioral score that a generic computer would not produce with the claimed structure” merely falls within invoking computers as a tool to perform economic tasks such as data processing. The applicant also asserts that claim 3 improves the user interface, however it is no more than displaying the results of a calculation, on a display in its ordinary capacity. The applicant asserts that claim 5 improves the platform’s ability to detect misrepresentation and strengthens the technical operation of the system, however, improving the detection of misrepresentation is an improvement to the abstract idea not a technical improvement. Therefore, even when considering the dependent claims in combination, the examiner’s position remains unchanged because none of the applicant’s arguments are persuasive.
Regarding applicant’s arguments over rejections under 35 U.S.C. 103 in pages 17-29, the examiner has fully considered the applicant’s arguments but does not find any of them persuasive for the following reasons.
In page 17, the applicant’s asserts that primary art, Highman does not rely on static background data external to the platform, and thus does not teach “behavioral signals.” However, the examiner notes that the claims are given the broadest reasonable interpretation(BRI) in view of the specification. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., real-time behavioral signals, such as historical engagement, quality of posts, affective state, peer blocking instances and positive peer ratings) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). The BRI of behavioral signals, in view of the specification but also by its plain meaning is any data signal that indicates any behavior by an individual. Therefore, external information such as “public and private records, legal proceedings, financial data, and credential status” fall within the scope of the BRI of “behavioral signals.” Furthermore, nothing in the claims requires that the behavioral signals are “real-time” behavioral signals, and even if that were the case, “real-time” does not have a definitive definition in the specification, and would therefore be broadly interpreted. Therefore, Highman [0073], which states, “[0073] A variety of computations and analyses are performed in the background and the user may be updated with a message depending on the background task as shown in steps 230-246. For example, if an alias/address has been attested to, but background checks are not complete, the system displays a calculation in process message (calculating score) 230” satisfies both the “real time” and the ”dynamic” limitation. Therefore, the applicant’s arguments are unpersuasive.
In page 18, the applicant rehashes the argument of Highman’s static external signals rather than “real-time behavioral signals” which is still unpersuasive for the same reasons as stated above. Furthermore, the applicant asserts that Highman fails to teach the claimed “profile ring feature module” because Highman does not disclose a module that dynamically updates the ring color based on user demeanor and authenticity as reflected by ongoing engagement. However, this argument is not persuasive. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Because the combination of Highman and Dwyer does arrive at the predictable outcome of teaching the profile ring feature module based on ongoing engagement, the applicant’s arguments are not persuasive.
In page 19, the applicant argues that the claimed invention explicitly requires signals derived from multiple actions executed by users. This is not persuasive because it is also a piecemeal analysis of the claim. The claim does not solely rely on Highman to teach the limitation therefore, the argument that Highman fails to teach evaluating user demeanor or deriving signals from social networking engagement activities is not persuasive because Dwyer is cited to remedy these deficiencies.
In page 20, the applicant argues that the Dwyer does not teach persistent, real-time notifications to end-users when their behavioral score changes, because Dwyer teaches ring-color changes based on agent quality, compliance and caller agitation. However, this is not persuasive because the broadest reasonable interpretation of “a notification module configured to provide plurality of real-time notifications to the user upon detecting variations in the color of the profile” does not necessarily exclude the changing of the profile ring in response to call interactions. Secondly, by attacking Dwyer individually without considering the combination, the applicant is performing a piecemeal analysis. Therefore, the arguments are unpersuasive.
In page 21, regarding arguments over claim 2, the applicant argues more of the same argument that Highman and Dwyer fail to teach “generating behavioral scores based on the nature and extent of engagement activities occurring within the online social networking platform, including “posting content, receiving ratings...” However, in response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., real-time behavioral signals, such as historical engagement, quality of posts, affective state, peer blocking instances and positive peer ratings, and “in platform user behavior”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). The BRI of behavioral signals, in view of the specification but also by its plain meaning is any data signal that indicates any behavior by an individual. Therefore, external information such as “public and private records, legal proceedings, financial data, and credential status” fall within the scope of the BRI of “behavioral signals.” Furthermore, nothing in the claims requires that the behavioral signals are “real-time” behavioral signals, and even if that were the case, “real-time” does not have a definitive definition in the specification, and would therefore be broadly interpreted. If the applicant wishes the distinguish the claim language from the prior art, the applicant is free to bring in limitations from the specification into the amended claim language to create such a distinction. However, given the BRI of the present claim language, Highman and Dwyer do teach the limitations and therefore, the arguments are not persuasive.
In page 22, the applicant asserts that Highman fails to teach that the profile ring feature module is displaying within the social networking platform itself, and that the ring reflects a user’s behavioral and behavioral scores. Firstly, the examiner notes again that the limitations from the specification are not read into the claims. Secondly, the BRI of “social networking platform” covers a broad scope and is not specifically defined in the disclosure, therefore it covers the scope of any platform enabling social interaction. Therefore Highman teaching a model “based on static, user-controlled sharing of trust data with limited evaluators (employers, service providers)” still falls within the scope of “facilitates visibility of the profile ring by other users, thereby enabling the other uses to make one or more informed determinations based on the color of the profile ring associated with the user.” Furthermore, this is also a piecewise analysis as it merely involves analyzing Highman whilst ignoring the combination of references. Therefore, the applicant’s arguments are unpersuasive.
In page 23, the applicant argues that neither Highman nor Dwyer discloses the profile ring feature module that “enables real-time, non-intrusive transparency of user demeanor and authenticity...” However, this is merely an assertion without evidence, and does not focus on the actual scope of the claim language. In view of the actual claim language, the combination of Highman and Dwyer has been shown to teach all of the limitations of the claims. Therefore, the applicant’s arguments are not persuasive.
In page 24, regarding arguments over claim 4, the applicant asserts more of the same arguments that Highman describes converting personal information from external data sources, which is allegedly in contrast with “generating signals specifically from multiple actions executed by the users within the online social networking platform.” However, this is a piecemeal analysis of the references. The rejection statement does not rely upon Highman alone to teach “generating signals specifically from multiple actions executed by the users within the online social networking platform.” Since Dwyer teaches signals such as “(e.g., voice, text, email, SMS, chat, blog, social network posts, and the like),” and because the scope of “social networking platform” is broad enough to include the customer call center system of Dwyer, than the limitations have been taught by the combination of Highman and Dwyer. Therefore, the applicant’s arguments are not persuasive.
In page 25, the applicant argues more of the same that “Highman’s trust score is a static evaluation of background records (criminal, financial, or credential data) and does not rely user engagement or behavioral characteristics. These arguments are not persuasive for the same reasons asserted above, specifically that it is a piecemeal analysis. The examiner has explicitly shown why Dwyer remedies the alleged deficiencies of Highman by teaching user engagement or behavioral characteristics. Therefore, the applicant’s arguments are unpersuasive.
In page 26, the applicant argues more of the same that “Highman’s trust score is a static evaluation of background records (criminal, financial, or credential data) and does not rely user engagement or behavioral characteristics. These arguments are not persuasive for the same reasons asserted above, specifically that it is a piecemeal analysis, and reads limitations into the claims that are not explicitly stated in the claim language (engagement activities, post quality, peer interactions, “dynamic”). Furthermore, the applicant’s arguments that Highman discloses sharing a static trust profile without any mechanism for dynamic alerts is not persuasive because, even if the claim language explicitly required “dynamic”, the BRI of “dynamic” does not necessarily exclude Highman’s profile rings because dynamic does not have specific limiting definition in the specification, and can include any feature that allows such profile/score to be updated at any interval. Therefore, Highman [0073], which states, “[0073] A variety of computations and analyses are performed in the background and the user may be updated with a message depending on the background task as shown in steps 230-246. For example, if an alias/address has been attested to, but background checks are not complete, the system displays a calculation in process message (calculating score) 230” would satisfy the ”dynamic” limitation. Therefore, the applicant’s arguments are unpersuasive.
Furthermore in pages 27 and 28, the applicant argues more of the same that Dwyer does not satisfy the “behavioral score to a persistent social networking profile,” however, this is not persuasive because it is further a piecemeal analysis of the references (ignoring the combination of Highman and Dwyer), and it is reading limitations from the specifications into the claims that are not explicitly stated in the claim language. As stated above, because of the breadth of “social networking profile,” is broad enough such that both Highman and Dwyer satisfy it because they mention posting these scores on social media platforms (see Dwyer [0083] and Highman [0050]). Furthermore, the arguments suffer from reading limitations from the specification into the claims that are not specifically required in the language such as “persistent social networking profile,” the claims do not mention “persistent.” Furthermore, the applicant mischaracterizes Dwyer by stating that Dwyer does not specifically disclose “computing a behavioral score from in-platform engagement activities such as likes, comments, posts, or blocking within a social network,” which is both not required by the claim language, but also untrue because Dwyer teaches “comments” in at least [0151]. Therefore, the applicant’s arguments are not persuasive.
In page 28, the applicant states that even when considering the combination of Highman and Dwyer, Dwyer does not teach “computing a behavioral score from social networking engagement activities, determining the profile ring color from that score, and providing real-time notifications to the user reflecting both demeanor and authenticity changes.” However, even thought the applicant acknowledges the combination, the applicant still states that Dwyer alone does not teach the required steps, ultimately ignoring the combination of Highman and Dwyer, which has been shown to teach all of the required claim limitations.
Regarding arguments over the rejection of claim 5 in pages 28-29, the applicant finally explicitly limits the user’s engagement activities to include “historical behavior, quality of posts, content posted, analysis of affective state, instances of being blocked by other users, and positive ratings.” However, the applicant continues to make piecemeal analyses of Highman and Dwyer whilst ignoring that the rejection is now based on the obvious combination of Highman, Dwyer, and Rohrweck. In view of the rejection above, the combination has been shown to teach all of the required claim limitations, including obviousness statements providing rationale for the combination of references. Therefore, applicant’s assertion that “while Highman, Dwyer, and Rohrweck collectively disclose aspects of trust scoring, behavioral analysis, and reputation feedback, none of these references explicitly teach aggregating these diverse engagement metrics into a unified color-coded profile ring that persistently reflects both authenticity and demeanor of the user on a social networking platform” is not a persuasive argument because there is no requirement that one of the references explicitly teaches aggregating the metrics into a unified color-coded profile ring. The combination of references satisfies the claim limitations and the rationale provided shows that one of ordinary skill in the art would have been motivated to perform such a combination by the benefit of accurate measuring trust/authenticity/reputation. Therefore, the applicant’s arguments are not persuasive in view of the prior art.
Therefore, the claim rejections under 103 stand, and the rejection is not withdrawn.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
-Madhu et al. (US 20200374311 A1) discloses risk assessment in a social network. ([0032] In various embodiments, the Socure system can display each friend profile with a visual color-coded representation. For example, the color red may represent profiles that are likely to be inauthentic or that may pose a threat. In another example, green may represents profiles that are likely to be authentic.)
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/NICO L PADUA/Junior Patent Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626
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