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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Novel/Non-Obvious Subject Matter
Examiner has determined that claim 10 of Applicant’s claims has overcome having prior art rejections. The reason for this is that Examiner does not believe that, at the time of Applicant’s priority date, it would have been obvious for a person of ordinary skill in the art to combine prior art disclosures to result in the particular combinations of elements/limitations in the claim, including the particular configurations of the elements/limitations with respect to each other in the particular combinations, without the use of impermissible hindsight.
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.
Claim(s) 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As per Claim(s) 1 and 17, Claim(s) 1 and 17 recite(s):
- identifying content being output;
- identifying a plurality of reactions to the content from a plurality of users;
- inputting, to a first learning model, data indicating the plurality of reactions;
- receiving, as output from the first learning model, sentiment data for the plurality of reactions;
- determining, based on the sentiment data output from the first learning model, at least one reaction of the plurality of reactions having a negative sentiment;
- identifying, as at least one portion of the content that is to be modified, a portion of the content corresponding to a portion of the at least one reaction having the negative sentiment;
- inputting, to a second learning model, data indicating at least a portion of the content and data indicating the identified portion of the content;
- receiving, as output from the second learning model, a regenerated version of the content;
- causing the content to be modified based on, or supplemented with, the regenerated version of the content.
Each of the above limitations falls within the abstract-idea category of “Certain methods of organizing human activity.” Specifically, those limitations relate to the following subject matter that is grouped into the category of “Certain methods of organizing human activity”:
- managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions): manages communications among users and operators of a social media platform, each of which may be or involve humans.
To the extent that any of these limitations are recited alongside recitations of generic computer components, as described below in this rejection: If a claim limitation, under its broadest reasonable interpretation, covers subject matter recognized as certain methods of organizing human activity but for the recitation of generic computer components, then it falls within the “Certain method of organizing human activity” grouping of abstract ideas. Accordingly, the claim(s) recite an abstract idea.
This judicial exception is not integrated into a practical application because the additional elements when considered both individually and as an ordered combination do not integrate the abstract idea into a practical application. The claim(s) recite the following additional elements/limitations, each of which are addressed in the list below with the reason(s) why they do not integrate the abstract idea into a practical application:
- computer-implemented; outputting via displaying; a social media platform; machine learning; a system, comprising: control circuitry configured: These element(s)/limitation(s) amount to mere instructions to apply an exception. See MPEP 2106.05(f). In making this determination, examiners may consider whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Mere instructions to apply an exception is a consideration with respect to both integration of an abstract idea into a practical application and significantly more. MPEP 2106.05(f)(2) states: “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 provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit).” This is the case with these particular claim element(s)/limitation(s). Those elements/limitations do not meaningfully limit the claim because implementing an abstract idea on a generic computer does not integrate the abstract idea into a practical application, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer. Therefore, these particular claim element(s)/limitation(s) do not integrate the abstract idea into a practical application for at least this reason.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology.
Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim(s) are directed to an abstract idea.
The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception, either individually or as an ordered combination. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of computer-related components amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
The claim(s) are not patent eligible.
As per dependent claim(s) 2-16 and 18-20, these claim(s) incorporate the above abstract idea via their dependencies on the respective independent claim(s). The additional element(s)/limitation(s) of the respective independent claim(s) do not integrate the abstract idea into a practical application, nor do they add significantly more, with respect to those dependent claim(s), under the same reasoning as above with respect to the respective independent claim(s).
Those dependent claim(s) add the following generic computer components, which do not integrate the abstract idea into a practical application, nor add significantly more, under the same reasoning as given above with respect to generic computer components in the independent claim(s). Those additional generic computer components and their corresponding dependent claim(s) are as follows:
- posting (claims 4-5, 7, and 20);
- viewing (claims 9-10 and 13);
- transmitting (claim 11);
- computing devices (claim 13);
- multiple social media platforms (claim 14);
- display (claim 15).
The remaining added elements/limitations of those dependent claim(s) do not integrate the abstract idea into a practical application nor add significantly more because they all merely add further functional step(s) and/or detail to the abstract idea; as part of the abstract idea, they cannot integrate into a practical application or be significantly more than the abstract idea of which they are a part. For example, claim 2 merely provides more detail about the sentiment data.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application, nor add significantly more. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology.
Claim(s) 1-20 are therefore not drawn to eligible subject matter as they are directed to an abstract idea that is not integrated into a practical application and is without 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.
Claim(s) 1-3, 6, 12-13, 15, and 17-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duggin, US 20180082313 A1, in view of Coffing, US 20220303619 A1.
As per Claims 1 and 17, Duggin discloses:
- a computer-implemented method (Figure 1; paragraph [0002] (“The present disclosure relates generally to systems and methods for prioritizing user reactions to content for response on a social-media platform.”); paragraph [0020] (“As shown in FIG. 1, platform 107 may comprise one or more platform servers 108, a content management system 110 (“content manager 110”), archived content 109, and/or a multimodal analytics engine 200 (“analytics engine 200”). Platform servers 108 may comprise hardware architecture and a software framework to allow software applications to run, including, but not limited to, operating systems, programming languages, and user interfaces.”));
- identifying content being displayed on a social media platform (paragraph [0013] (“The multimodal social-media data analytics and engagement platform may be a web-based application that allows users to share information through a social-media network that uses video, audio, text, and other modes of communication to share content and reactions thereto with a social network.”); paragraph [0019] (“The content to be provided on the channel may be selected by the channel administrator. The channel administrator may collect data on users who view the content and may collect data pertaining to the viewing of the content. The channel administrator or another person or entity may receive reactions from users to the content that users view on the channel. The channel administrator or another person or entity may respond to the reactions. In certain embodiments, the channel administrator may be any person, people, entity, or entities that respond to or analyze the reactions.”); paragraph [0021] (“For example, reaction data to the content may contain metadata describing the content the reaction was generated to and the time within the content the reaction was generated (e.g., two minutes into a video file).”));
- identifying a plurality of reactions to the content from a plurality of users of the social media platform (paragraph [0019] (“The channel administrator or another person or entity may receive reactions from users to the content that users view on the channel. The channel administrator or another person or entity may respond to the reactions. In certain embodiments, the channel administrator may be any person, people, entity, or entities that respond to or analyze the reactions.”); paragraph [0021] (“Reactions may be analyzed by platform 107 using analytics engine 200.”; “The content archived may be associated with reactions to the content. For example, reaction data to the content may contain metadata describing the content the reaction was generated to and the time within the content the reaction was generated (e.g., two minutes into a video file). In some embodiments, the content and the corresponding reactions to the content may be archived.”); paragraph [0026] (“Platform 107 may display a report to the channel administrator comprising a list of user reactions the channel administrator should respond to in order to make the maximum impact on overall user sentiment associated with particular content or a particular section of content.”));
- inputting, to a first machine learning model, data indicating the plurality of reactions (paragraph [0025] (whole paragraph); paragraph [0026]; paragraph [0036] (“Analytics sub-engine 400 may receive user reactions or behavior as data in a variety of formats (as discussed with respect to FIG. 2), assign sentiment metrics or sentiment categories to reactions (e.g., negative sentiment, neutral sentiment, positive sentiment), and assign weights to reactions (i.e., “weight reactions”) according to predefined rules (e.g., weighting preferences 228) and the sentiment metrics and/or categories assigned to the reactions.”; “The rules and the method of assigning a sentiment category may change as machine-learning sub-engine 1000 receives feedback from response selections by the channel administrator and changes in overall user sentiment after the channel administrator posts responses.”));
- receiving, as output from the first machine learning model, sentiment data for the plurality of reactions (paragraph [0025] (whole paragraph); paragraph [0026]; paragraph [0036] (“Analytics sub-engine 400 may receive user reactions or behavior as data in a variety of formats (as discussed with respect to FIG. 2), assign sentiment metrics or sentiment categories to reactions (e.g., negative sentiment, neutral sentiment, positive sentiment), and assign weights to reactions (i.e., “weight reactions”) according to predefined rules (e.g., weighting preferences 228) and the sentiment metrics and/or categories assigned to the reactions.”; “The rules and the method of assigning a sentiment category may change as machine-learning sub-engine 1000 receives feedback from response selections by the channel administrator and changes in overall user sentiment after the channel administrator posts responses.”; “The reactions analyzed may be reactions of an individual user or reactions of multiple users, such as users interacting with each other on platform 107.”));
- determining, based on the sentiment data output from the first machine learning model, at least one reaction of the plurality of reactions having a negative sentiment (paragraph [0025] (whole paragraph); paragraph [0026]; paragraph [0036] (“Analytics sub-engine 400 may receive user reactions or behavior as data in a variety of formats (as discussed with respect to FIG. 2), assign sentiment metrics or sentiment categories to reactions (e.g., negative sentiment, neutral sentiment, positive sentiment), and assign weights to reactions (i.e., “weight reactions”) according to predefined rules (e.g., weighting preferences 228) and the sentiment metrics and/or categories assigned to the reactions.”; “The rules and the method of assigning a sentiment category may change as machine-learning sub-engine 1000 receives feedback from response selections by the channel administrator and changes in overall user sentiment after the channel administrator posts responses.”; “The reactions analyzed may be reactions of an individual user or reactions of multiple users, such as users interacting with each other on platform 107.”));
- identifying a portion of the content corresponding to a portion of the at least one reaction having the negative sentiment (paragraph [0003] (“Content providers may want to know, for example, how users feel about the shared content, what portion of the content made users feel a particular way, or how to motivate users to view their content.”); paragraph [0021] (“For example, reaction data to the content may contain metadata describing the content the reaction was generated to and the time within the content the reaction was generated (e.g., two minutes into a video file).”); paragraph [0027] (quite a bit of paragraph); paragraph [0028] (“A “thumbs up” graphic, “clapping hands”, or smiley face graphic, for example, may be used to indicate the user likes the content or a positive emotion, while a “thumbs down” or “angry” graphic may be used to indicate displeasure or disagreement or a negative emotion. Other examples of emojis are neutral faces. Emoji 206 may be overlaid over the viewed content such that emoji 206 appears at the portion of the content viewed when emoji 206 was selected by the user. User selection of emoji 206 may be captured with a timecode of the content.”); paragraph [0037] (“Analytics sub-engine 400 may break down user reactions with their corresponding timestamp metadata into multiple components for categorizing the individual components into sentiment categories or assigning sentiment metrics and determining an overall sentiment metric or category for the entire reaction.”); paragraph [0042] (“When the viewer responds in real time while viewing content, the emoji data may be timestamped and attributed to a time relative to the content being viewed. The timestamped emoji data may be forwarded to emoji categorization module 415 to be assigned a sentiment metric and/or categorized by sentiment type.”));
- a system, comprising: control circuitry configured (Figure 1; paragraph [0002] (“The present disclosure relates generally to systems and methods for prioritizing user reactions to content for response on a social-media platform.”); paragraph [0020] (“As shown in FIG. 1, platform 107 may comprise one or more platform servers 108, a content management system 110 (“content manager 110”), archived content 109, and/or a multimodal analytics engine 200 (“analytics engine 200”). Platform servers 108 may comprise hardware architecture and a software framework to allow software applications to run, including, but not limited to, operating systems, programming languages, and user interfaces.”)).
Duggin fails to disclose determining to modify at least one portion of the content having negative sentiment; inputting, to a second machine learning model, data indicating at least a portion of the content and data indicating the identified portion of the content; receiving, as output from the second machine learning model, a regenerated version of the content; causing the content to be modified based on the regenerated version of the content. Coffing discloses determining to modify at least one portion of the content having negative sentiment (paragraph [0042] (“The customized media content constructor 140 can generate the customized media content by editing certain words, phrases, images, audio segments, or video segments within the selected media content segments based on the user information and/or the user insights. For example, if an insight from the user analysis engine 134 indicates that the user considers a certain word or phrase offensive, the customized media content constructor 140 can edit the customized media content to replace an instance of the offensive word or phrase with an inoffensive or less offensive word or phrase.”)); inputting, to a second machine learning model, data indicating at least a portion of the content and data indicating the identified portion of the content (paragraph [0033] (“Information about interactions may be useful for the customized media content constructor 140 to customize content based on what the user has shown to be effective for the user based on the interactions themselves (e.g., what the user has shown that they “like” based on the interactions themselves). Information about interactions may be useful for the customized media content constructor 140 to customize content based on media that historically appeals to users that perform similar interactions.”); paragraph [0034] (“Historical data about a user may be useful for the customized media content constructor 140 to customize content to be more similar to media that the user has historically consumed, enjoyed, and/or found persuasive. Historical data about a user may be useful for the customized media content constructor 140 to customize content based on media that historically appeals to users with similar histories.”); paragraph [0037] (“The customized media content constructor 140 to customize content for users in the high-reputation user's social network(s) based on content that the high-reputation user has historically consumed, enjoyed, and/or found persuasive. The customized media content constructor 140 to customize content for users in the high-reputation user's social network(s) based on content that historically appeals to the high-reputation user and/or similar users.”); paragraph [0042] (most of paragraph); paragraph [0043] (most of paragraph); paragraph [0047] (most of paragraph); paragraph [0087] (machine learning)); receiving, as output from the second machine learning model, a regenerated version of the content (paragraph [0033] (“Information about interactions may be useful for the customized media content constructor 140 to customize content based on what the user has shown to be effective for the user based on the interactions themselves (e.g., what the user has shown that they “like” based on the interactions themselves). Information about interactions may be useful for the customized media content constructor 140 to customize content based on media that historically appeals to users that perform similar interactions.”); paragraph [0034] (“Historical data about a user may be useful for the customized media content constructor 140 to customize content to be more similar to media that the user has historically consumed, enjoyed, and/or found persuasive. Historical data about a user may be useful for the customized media content constructor 140 to customize content based on media that historically appeals to users with similar histories.”); paragraph [0037] (“The customized media content constructor 140 to customize content for users in the high-reputation user's social network(s) based on content that the high-reputation user has historically consumed, enjoyed, and/or found persuasive. The customized media content constructor 140 to customize content for users in the high-reputation user's social network(s) based on content that historically appeals to the high-reputation user and/or similar users.”); paragraph [0042] (most of paragraph); paragraph [0043] (most of paragraph); paragraph [0047] (most of paragraph); paragraph [0087] (machine learning)); causing the content to be modified based on the regenerated version of the content (paragraph [0042] (most of paragraph); paragraph [0043] (most of paragraph)). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Duggin such that the invention determines to modify at least one portion of the content having negative sentiment; the invention inputs, to a second machine learning model, data indicating at least a portion of the content and data indicating the identified portion of the content; the invention receives, as output from the second machine learning model, a regenerated version of the content; and the invention causes the content to be modified based on the regenerated version of the content, as disclosed by Coffing, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per Claims 2 and 18, Duggin further discloses wherein the sentiment data classifies each reaction of the plurality of reactions as having a positive sentiment, a neutral sentiment, or a negative sentiment (paragraph [0036]; paragraph [0050]).
As per Claims 3 and 19, the modified Duggin fails to disclose identifying a replacement portion to be used in the regenerated version of the content instead of the identified portion of the content, the replacement portion having a positive or a neutral sentiment; wherein the replacement portion corresponds to the data indicating the identified portion of the content that is input to the second machine learning model. Coffing further discloses disclose identifying a replacement portion to be used in the regenerated version of the content instead of the identified portion of the content, the replacement portion having a positive or a neutral sentiment; wherein the replacement portion corresponds to the data indicating the identified portion of the content that is input to the second machine learning model (paragraph [0033]; paragraph [0034]; paragraph [0037]; paragraph [0042]; paragraph [0043]; paragraph [0047]; paragraph [0087]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the invention identifies a replacement portion to be used in the regenerated version of the content instead of the identified portion of the content, the replacement portion having a positive or a neutral sentiment; wherein the replacement portion corresponds to the data indicating the identified portion of the content that is input to the second machine learning model, as disclosed by Coffing, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per Claim 6, the modified Duggin fails to disclose wherein: the data indicating the identified portion of the content that is input to the second machine learning model comprises an indication to omit the identified portion of the content from the regenerated version of the content. Coffing further discloses wherein: the data indicating the identified portion of the content that is input to the second machine learning model comprises an indication to omit the identified portion of the content from the regenerated version of the content (paragraph [0033]; paragraph [0034]; paragraph [0037]; paragraph [0042]; paragraph [0043]; paragraph [0047]; paragraph [0087]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the data indicating the identified portion of the content that is input to the second machine learning model comprises an indication to omit the identified portion of the content from the regenerated version of the content, as disclosed by Coffing, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per Claim 12, Duggin further discloses wherein an impression about content is based on at least one of the plurality of reactions (paragraph [0025]; paragraph [0026]; paragraph [0036]).
The modified Duggin fails to disclose wherein inputting, to the second machine learning model, the data indicating the at least a portion of the content and the data indicating the identified portion of the content is further performed based on determining the content comprises data that is false or offensive. Coffing further discloses wherein inputting, to the second machine learning model, the data indicating the at least a portion of the content and the data indicating the identified portion of the content is further performed based on determining the content comprises data that is false or offensive (paragraph [0033]; paragraph [0034]; paragraph [0037]; paragraph [0042]; paragraph [0043]; paragraph [0047]; paragraph [0087]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that inputting, to the second machine learning model, the data indicating the at least a portion of the content and the data indicating the identified portion of the content is further performed based on determining the content comprises data that is false or offensive, as disclosed by Coffing, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per Claim 13, Duggin further discloses wherein the content is viewed on a social media platform (paragraph [0013]).
The modified Duggin fails to disclose determining a first user is currently viewing the content via a first computing device, and that a second user is currently viewing the content via a second computing device; identifying first user preferences associated with the first user, and identifying second user preferences associated with the second user; and wherein the second machine learning model is configured to regenerate the content by: regenerating the content as first modified content, based at least in part on the first user preferences; regenerating the content as first modified content based at least in part on the second user preferences; and wherein causing the content to be modified based on, or supplemented with, the regenerated version of the content comprises: causing the content to be modified based on, or supplemented with, the first modified content at the first computing device of the first user; and causing the content to be modified based on, or supplemented with the second modified content at the second computing device of the second user. Coffing further discloses determining a first user is currently viewing the content via a first computing device, and that a second user is currently viewing the content via a second computing device; identifying first user preferences associated with the first user, and identifying second user preferences associated with the second user; and wherein the second machine learning model is configured to regenerate the content by: regenerating the content as first modified content, based at least in part on the first user preferences; regenerating the content as first modified content based at least in part on the second user preferences; and wherein causing the content to be modified based on, or supplemented with, the regenerated version of the content comprises: causing the content to be modified based on, or supplemented with, the first modified content at the first computing device of the first user; and causing the content to be modified based on, or supplemented with the second modified content at the second computing device of the second user (paragraph [0006]; paragraph [0032]; paragraph [0043]; paragraph [0056]; paragraph [0086]; paragraph [0087]; paragraph [0089]; paragraph [0090]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the invention determines a first user is currently viewing the content via a first computing device, and that a second user is currently viewing the content via a second computing device; the invention identifies first user preferences associated with the first user, and identifies second user preferences associated with the second user; and wherein the second machine learning model is configured to regenerate the content by: regenerating the content as first modified content, based at least in part on the first user preferences; regenerating the content as first modified content based at least in part on the second user preferences; and wherein causing the content to be modified based on, or supplemented with, the regenerated version of the content comprises: causing the content to be modified based on, or supplemented with, the first modified content at the first computing device of the first user; and causing the content to be modified based on, or supplemented with the second modified content at the second computing device of the second user, as disclosed by Coffing, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per Claim 15, Duggin further discloses providing for display the plurality of reactions; and based on the sentiment data for the plurality of reactions, modifying the display of the plurality of reactions to: group a first subset of the plurality of reactions having a positive sentiment together; group a second subset of the plurality of reactions having a negative sentiment together; and group a third subset of the plurality of reactions having a neutral sentiment together (paragraph [0013]; paragraph [0046]).
Claim(s) 4-5 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duggin in view of Coffing in further view of Krasadakis, US 20190179956 A1.
As per Claims 4 and 20, Duggin further discloses wherein: the plurality of reactions comprise a plurality of comments posted to the social media platform in association with the content (paragraph [0019]; paragraph [0021]; paragraph [0026]); receiving, as the output from the first machine learning model, the sentiment data for the plurality of reactions (paragraph [0025]; paragraph [0026]; paragraph [0036]).
The modified Duggin fails to disclose identifying a replacement portion to be used in the regenerated version of the content instead of the portion of the content is performed in response to determining that the identified portion of the content is associated with a negative response. Coffing further discloses identifying a replacement portion to be used in the regenerated version of the content instead of the portion of the content is performed in response to determining that the identified portion of the content is associated with a negative response (paragraph [0042]; paragraph [0043]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the invention identifies a replacement portion to be used in the regenerated version of the content instead of the portion of the content is performed in response to determining that the identified portion of the content is associated with a negative response, as disclosed by Coffing, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
The modified Duggin fails to disclose wherein sentiment data comprises data indicating a number of the plurality of comments having a negative sentiment, and wherein determining a negative response comprises determining that a number of a plurality of comments exceeds a threshold. Krasadakis discloses wherein sentiment data comprises data indicating a number of the plurality of comments having a negative sentiment, and wherein determining a negative response comprises determining that a number of a plurality of comments exceeds a threshold (paragraph [0125]; paragraph [0126]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that sentiment data comprises data indicating a number of the plurality of comments having a negative sentiment, and determining a negative response comprises determining that a number of a plurality of comments exceeds a threshold, as disclosed by Krasadakis, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per Claim 5, Duggin further discloses wherein: the plurality of reactions comprise a plurality of comments posted to the social media platform in association with the content (paragraph [0019]; paragraph [0021]; paragraph [0026]); receiving, as the output from the first machine learning model, the sentiment data for the plurality of reactions (paragraph [0025]; paragraph [0026]; paragraph [0036]).
The modified Duggin fails to disclose inputting, to the second machine learning model, the data indicating at least a portion of the content and the data indicating the identified portion of the content is performed in response to determining that the identified portion of the content is associated with a negative response. Coffing further discloses inputting, to the second machine learning model, the data indicating at least a portion of the content and the data indicating the identified portion of the content is performed in response to determining that the identified portion of the content is associated with a negative response (paragraph [0033]; paragraph [0034]; paragraph [0037]; paragraph [0042]; paragraph [0043]; paragraph [0047]; paragraph [0087]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the invention inputs, to the second machine learning model, the data indicating at least a portion of the content and the data indicating the identified portion of the content is performed in response to determining that the identified portion of the content is associated with a negative response, as disclosed by Coffing, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
The modified Duggin fails to disclose wherein sentiment data comprises data indicating a number of the plurality of comments having a negative sentiment, and wherein determining a negative response comprises determining that a number of a plurality of comments having the negative sentiment exceeds a threshold. Krasadakis discloses wherein sentiment data comprises data indicating a number of the plurality of comments having a negative sentiment, and wherein determining a negative response comprises determining that a number of a plurality of comments having the negative sentiment exceeds a threshold (paragraph [0125]; paragraph [0126]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that sentiment data comprises data indicating a number of the plurality of comments having a negative sentiment, and determining a negative response comprises determining that a number of a plurality of comments having the negative sentiment exceeds a threshold, as disclosed by Krasadakis, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duggin in view of Coffing in further view of Li, US 20250373901 A1.
As per Claim 7, Duggin further discloses wherein: the plurality of reactions comprise a plurality of comments posted to the social media platform in association with the content; and the method further comprises: determining an amount of attention-drawing of a comment; and addressing issues with content based at least in part on the amount of attention-drawing of a comment (paragraph [0019]; paragraph [0021]; paragraph [0026]; paragraph [0035]; paragraph [0036]; paragraph [0037])
The modified Duggin fails to disclose wherein addressing issues with content comprises using the second machine learning model to regenerate the content as modified content. Coffing further discloses wherein addressing issues with content comprises using the second machine learning model to regenerate the content as modified content (paragraph [0033]; paragraph [0034]; paragraph [0037]; paragraph [0042]; paragraph [0043]; paragraph [0047]; paragraph [0087]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that addressing issues with content comprises using the second machine learning model to regenerate the content as modified content, as disclosed by Coffing, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
The modified Duggin fails to disclose wherein amount of attention-drawing of a comment is determined by determining that a number of interactions with at least one comment of the plurality of comments exceeds a threshold. Li discloses wherein amount of attention-drawing of a comment is determined by determining that a number of interactions with at least one comment of the plurality of comments exceeds a threshold (paragraphs [0020]-[0023]; paragraph [0108]; paragraph [0110]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that amount of attention-drawing of a comment is determined by determining that a number of interactions with at least one comment of the plurality of comments exceeds a threshold, as disclosed by Li, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duggin in view of Coffing in further view of Ur, US 20130290084 A1.
As per Claim 8, the modified Duggin fails to disclose wherein the plurality of reactions comprise a plurality of comments related to the content, and identifying the plurality of reactions to the content from the plurality of users of the social media platform comprises: for each respective user of the plurality of users, analyzing profile data of the user to determine whether a user profile of the user is a valid user profile; for each respective comment of the plurality of comments, analyzing text of the comment to determine whether the comment is relevant to the content; and identifying the plurality of reactions to the content from the plurality of users of the social media platform based on determining that: each of the plurality of users is associated with a valid user profile; and each of the plurality of comments is relevant to the content. Ur discloses wherein the plurality of reactions comprise a plurality of comments related to the content, and identifying the plurality of reactions to the content from the plurality of users of the social media platform comprises: for each respective user of the plurality of users, analyzing profile data of the user to determine whether a user profile of the user is a valid user profile; for each respective comment of the plurality of comments, analyzing text of the comment to determine whether the comment is relevant to the content; and identifying the plurality of reactions to the content from the plurality of users of the social media platform based on determining that: each of the plurality of users is associated with a valid user profile; and each of the plurality of comments is relevant to the content (paragraph [0021]; paragraph [0050]; paragraph [0081]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the plurality of reactions comprise a plurality of comments related to the content, and identifying the plurality of reactions to the content from the plurality of users of the social media platform comprises: for each respective user of the plurality of users, analyzing profile data of the user to determine whether a user profile of the user is a valid user profile; for each respective comment of the plurality of comments, analyzing text of the comment to determine whether the comment is relevant to the content; and identifying the plurality of reactions to the content from the plurality of users of the social media platform based on determining that: each of the plurality of users is associated with a valid user profile; and each of the plurality of comments is relevant to the content, as disclosed by Ur, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duggin in view of Coffing in further view of Israel, WO 2017/149540 A1, in further view of Biswas, US 20250068699 A1.
As per Claim 9, Duggin further discloses wherein sentiment analysis is performed by the first machine learning model (paragraph [0025]; paragraph [0026]; paragraph [0036]).
The modified Duggin fails to disclose in response to determining that reactions are of interest, inputting, to the sentiment analysis, the data indicating the plurality of reactions. Israel discloses in response to determining that reactions are of interest, inputting, to the sentiment analysis, the data indicating the plurality of reactions (p. 5, lines 7-21; p. 24, lines 11-27). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that, in response to determining that reactions are of interest, the invention inputs, to the sentiment analysis, the data indicating the plurality of reactions, as disclosed by Israel, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
The modified Duggin fails to disclose determining that reactions are of interest by identifying a number of users that have reacted to the content or viewed the content; and determining that the number of users is above a threshold number. Biswas discloses determining that reactions are of interest by identifying a number of users that have reacted to the content or viewed the content; and determining that the number of users is above a threshold number (paragraph [0018]; claim 10). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the invention determines that reactions are of interest by identifying a number of users that have reacted to the content or viewed the content; and determining that the number of users is above a threshold number, as disclosed by Biswas, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duggin in view of Coffing in further view of Sneyers, US 20210183105 A1.
As per Claim 11, the modified Duggin fails to disclose transmitting a recommendation, to a content provider associated with the content, to replace the content with the regenerated version of the content, wherein causing the content on the social media platform to be modified based on, or supplemented with, the regenerated version of the content is performed in response to receiving an indication from the content provider approving of the recommendation. Sneyers discloses transmitting a recommendation, to a content provider associated with the content, to replace the content with the regenerated version of the content, wherein causing the content on the social media platform to be modified based on, or supplemented with, the regenerated version of the content is performed in response to receiving an indication from the content provider approving of the recommendation (paragraph [0017]; paragraph [0035]; paragraph [0038]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the invention transmits a recommendation, to a content provider associated with the content, to replace the content with the regenerated version of the content, wherein causing the content on the social media platform to be modified based on, or supplemented with, the regenerated version of the content is performed in response to receiving an indication from the content provider approving of the recommendation, as disclosed by Sneyers, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duggin in view of Coffing in further view of Ramakrishnan, US 20200334639 A1, in further view of Krasadakis.
As per Claim 14, Duggin further discloses wherein the social media platform is a first social media platform, the plurality of reactions is a first plurality of reactions, and the plurality of users is a first plurality of users, and the method further comprises: determining the content is being displayed on a second social media platform; identifying a second plurality of reactions to the content from a second plurality of users of the second social media platform; inputting, to the first machine learning model, data indicating the second plurality of reactions; receiving, as output from the first machine learning model, sentiment data for the second plurality of reactions (paragraph [0019]; paragraph [0025]; paragraph [0026]; paragraph [0036]).
The modified Duggin fails to disclose in response to determining, based on the sentiment data, that negative sentiment is less than a threshold, maintaining the content. Ramakrishnan discloses in response to determining, based on the sentiment data, that negative sentiment is less than a threshold, maintaining the content (Figure 3; paragraph [0032]; paragraph [0048]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that, in response to determining, based on the sentiment data, that negative sentiment is less than a threshold, the invention maintains the content, as disclosed by Ramakrishnan, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
The modified Duggin fails to disclose wherein the metric for negative sentiment is the number of reactions having a negative sentiment. Krasadakis discloses wherein the metric for negative sentiment is the number of reactions having a negative sentiment (paragraph [0125]; paragraph [0126]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the metric for negative sentiment is the number of reactions having a negative sentiment, as disclosed by Krasadakis, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duggin in view of Coffing in further view of Marom, US 20250209257 A1.
As per Claim 16, Duggin further discloses wherein: the content comprises text data (paragraph [0013]; paragraph [0020]; paragraph [0021]).
The modified Duggin fails to disclose the data indicating at least a portion of the content, input to the second machine learning model, comprises at least a portion of the text data; and the data indicating the identified portion of the content, input to the second machine learning model, comprises an indication of an identified portion of the text that is determined, based on the sentiment data, to be modified or omitted in the regenerated version of the content. Coffing further discloses the data indicating at least a portion of the content, input to the second machine learning model, comprises at least a portion of the text data; and the data indicating the identified portion of the content, input to the second machine learning model, comprises an indication of an identified portion of the text that is determined, based on the sentiment data, to be modified or omitted in the regenerated version of the content (paragraph [0033]; paragraph [0034]; paragraph [0037]; paragraph [0042]; paragraph [0043]; paragraph [0044]; paragraph [0047]; paragraph [0087]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the data indicating at least a portion of the content, input to the second machine learning model, comprises at least a portion of the text data; and the data indicating the identified portion of the content, input to the second machine learning model, comprises an indication of an identified portion of the text that is determined, based on the sentiment data, to be modified or omitted in the regenerated version of the content, as disclosed by Coffing, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
The modified Duggin fails to disclose the second machine learning model is a large language model; and a command requesting the text data to be regenerated is input to the machine learning model. Marom discloses the second machine learning model is a large language model; and a command requesting the text data to be regenerated is input to the machine learning model (paragraph [0041]; paragraph [0046]; paragraph [0060]; paragraph [0064]; paragraph [0108]; paragraph [0189]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of the modified Duggin such that the second machine learning model is a large language model; and a command requesting the text data to be regenerated is input to the machine learning model, as disclosed by Marom, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Yarnall, US 20220182346 A1 (systems and methods for review and response to social media postings).
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/NATHAN ERB/Primary Examiner, Art Unit 3628