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 the Claims
Claims 1, 4-14, and 17-24 are all the claims pending in the application.
Claims 2, 3, 15, and 16 are cancelled.
Claims 21-24 are new.
Claims 1, 4, 5, 7, 9-14, 17, 18, and 20 are amended.
Claims 1, 4-14, and 17-24 are rejected.
The following is a Final Office Action in response to amendments and remarks filed July 24, 2026.
Response to Arguments
Regarding the claim objection, the objection is withdrawn in light of the amendments.
Regarding the 101 rejections, the rejections are maintained for the following reasons. First and second, Applicant asserts the rejections should be withdrawn because the predetermined image generation model is a specific technology and is obtained through iterative training. Examiner respectfully does not find this assertion persuasive because Examiner finds the use of the predetermined image generation model is recited too broadly and generally to be more than a general link to a field use.
Third, Applicant asserts the rejections should be withdrawn because the use of color as claimed embodies a concrete improvement. Examiner respectfully does not find this assertion persuasive because generating art for content is a part of the abstract idea (i.e., generating advertisements with relevant art).
Fourth and fifth, Applicant asserts the claims solve the problem of users manually writing text and editing images. Examiner respectfully does not find this assertion persuasive because claiming the improved speed or efficiency inherent with applying the abstract idea on a computer does not provide a practical application, see MPEP 2106.05(f)(2) (discussing Intellectual Ventures I LLC v. Capital One Bank (USA)).
Accordingly the 101 rejections are maintained, please see below for the complete rejections of the claims as amended.
Regarding the 112(b) rejections, the rejections are withdrawn in light of the amendments to the claims.
Regarding the 102 rejections, the rejections are withdrawn because the cited references do not teach all the newly amended limitations. Please see below for the new 103 rejections of the claims as amended.
Please note, Applicant asserts Conti does not teach some of the newly amended limitations. Examiner respectfully does not find this assertion persuasive because Applicant does not explain how or why the Conti does not teach these newly amended limitations.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Under Step 1 of the patent eligibility analysis, it must first be determined whether the claims are directed to one of the four statutory categories of invention. Applying Step 1 to the claims it is determined that: claims 1 and 4-13 are directed to a process; and claims 14 and 17-24 are directed to a machine.
Independent Claims
Under Step 2A Prong 1 of the patent eligibility analysis, it must be determined whether the claims recite an abstract idea that falls within one or more designated categories or “buckets” of patent ineligible subject matter that amount to a judicial exception to patentability.
The independent claims recite an abstract idea. Specifically, independent claim 1 recites an abstract idea in the limitations (emphasized):
…determining at least one piece of media content to be recommended;
obtaining, for each piece of media content, basic information corresponding to the piece of media content, and obtaining at least one type of interactive content generated based on the piece of media content, the interactive content comprising review information posted by historical users based on the piece of media content and content marked by the users in the piece of media content;
generating, based on the basic information corresponding to each piece of media content and the at least one type of interactive content, recommended content corresponding to the piece of media content, wherein the recommended content comprises a recommended image and a recommended text, and the recommended text comprises the basic information of the piece of media content and content generated based on the interactive content that highlights characteristics of the piece of media content;
generating target recommended content based on the recommended content corresponding to each piece of media content, and posting the target recommended content;
wherein generating, based on the basic information corresponding to each piece of media content and the at least one type of interactive content, the recommended content corresponding to the piece of media content comprises:
generating, for each piece of media content and based on the basic information corresponding to the piece of media content, the recommended image associated with the piece of media content,
generating, based on the basic information corresponding to the piece of media content and the at least one type of interactive content, the recommended text associated with the piece of media content, and
generating, based on the recommended image and the recommended text, the recommended content corresponding to the piece of media content;
wherein obtaining the basic information corresponding to the piece of media content comprises:
obtaining the basic information from preset parameters associated with the piece of media content, wherein the basic information comprises one or more of a content title, a content parameter, introduction information, and a cover image; and
wherein generating, based on the basic information corresponding to the piece of media content, the recommended image associated with the piece of media content comprises:
inputting the basic information into a predetermined image generation model to obtain the recommended image output by the image generation model, wherein the recommended image comprises one or more of the content title, the content parameter, the introduction information, and the cover image, and a color of the recommended image matches that of the cover image.
These limitations recite an abstract idea because these limitations encompasses commercial or legal interactions (i.e., advertising, marketing or sales activities or behaviors). These limitations encompass commercial or legal interactions (i.e., advertising, marketing or sales activities or behaviors) because these limitations encompass generating advertising or marketing material for products. That is, these limitations encompass advertising, marketing or sales activities or behaviors because these limitations encompass generating art and text recommending a product based on existing reviews and its own content. Claims that encompass commercial or legal interactions fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Claims 1, 14, and 20 recite an abstract idea.
Under Step 2A Prong 2 of the patent eligibility analysis, it must be determined whether the identified, recited abstract idea includes additional elements that integrate the abstract idea into a practical application.
The additional elements of the independent claims do not integrate the abstract idea into a practical application. Claim 1 recites the additional elements (emphasized):
…determining at least one piece of media content to be recommended;
obtaining, for each piece of media content, basic information corresponding to the piece of media content, and obtaining at least one type of interactive content generated based on the piece of media content, the interactive content comprising review information posted by historical users based on the piece of media content and content marked by the users in the piece of media content;
generating, based on the basic information corresponding to each piece of media content and the at least one type of interactive content, recommended content corresponding to the piece of media content, wherein the recommended content comprises a recommended image and a recommended text, and the recommended text comprises the basic information of the piece of media content and content generated based on the interactive content that highlights characteristics of the piece of media content;
generating target recommended content based on the recommended content corresponding to each piece of media content, and posting the target recommended content;
wherein generating, based on the basic information corresponding to each piece of media content and the at least one type of interactive content, the recommended content corresponding to the piece of media content comprises:
generating, for each piece of media content and based on the basic information corresponding to the piece of media content, the recommended image associated with the piece of media content,
generating, based on the basic information corresponding to the piece of media content and the at least one type of interactive content, the recommended text associated with the piece of media content, and
generating, based on the recommended image and the recommended text, the recommended content corresponding to the piece of media content;
wherein obtaining the basic information corresponding to the piece of media content comprises:
obtaining the basic information from preset parameters associated with the piece of media content, wherein the basic information comprises one or more of a content title, a content parameter, introduction information, and a cover image; and
wherein generating, based on the basic information corresponding to the piece of media content, the recommended image associated with the piece of media content comprises:
inputting the basic information into a predetermined image generation model to obtain the recommended image output by the image generation model, wherein the recommended image comprises one or more of the content title, the content parameter, the introduction information, and the cover image, and a color of the recommended image matches that of the cover image.
These additional elements do not integrate the abstract idea into practical application for the following reasons. First, the additional elements of obtaining basic information and interactive content and posting the target recommended content, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements encompass generic computer functions of receiving data and sending data (e.g., receiving user input and transmitting data to a social network), see MPEP 2106.05(f)(2) (noting the use of computers in their ordinary capacity to receive, store, or transmit data does not integrate a judicial exception into a practical application).
Second, the additional elements of inputting the data into a predetermined image generation model, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are only a general link to a field of use or technological environment, see MPEP 2106.05(h) (discussing Affinity Labs). That is, although these additional elements do limit the use of the abstract idea, this type of limitation merely confines the use of the abstract idea to a particular technological environment (i.e., generative AI for creating text and images) and does not integrate the abstract idea into a practical application or add an inventive concept to the claims.
Claims 14 and 20 recite similar additional elements as claim 1 and further recite “a processor and a memory, wherein the memory stores computer-executable instructions; and the processor executes the computer-executable instructions stored in the memory” and a “non-transitory computer-readable storage medium having stored therein computer- executable instructions”, respectively. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, claims 1, 14 and 20 are directed to an abstract idea.
Under Step 2B of the patent eligibility analysis, the additional elements are evaluated to determine whether they amount to something “significantly more” than the recited abstract idea (i.e., an innovative concept).
The independent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception and a general link to a field of use. Mere instructions to apply an exception using generic computer components and a general link to a field of use cannot provide an inventive concept. Claims 1, 14 and 20 are not patent eligible.
Dependent Claims
The dependent claims are rejected under 35 USC 101 as directed to an abstract idea for the following reasons.
Claims 4 and 17 recite the additional elements of inputting the claimed information into a text generation model. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are only a general link to a field of use or technological environment, see MPEP 2106.05(h) (discussing Affinity Labs). That is, although these additional elements do limit the use of the abstract idea, this type of limitation merely confines the use of the abstract idea to a particular technological environment (i.e., generative AI for creating text and images) and does not integrate the abstract idea into a practical application or add an inventive concept to the claims.
Claims 5-8 and 18, 19, 21, and 22 recite the additional elements of filtering based on various types of data. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are only using software to tailor information and provide it to a user, which is not more than mere instructions to apply the exception, see MPEP 2106.05(f) (discussing Intellectual Ventures I LLC v. Capital One Bank (USA)).
Claims 7 and 21 further recites the additional elements of using a text recognition model. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are only a general link to a field of use or technological environment, see MPEP 2106.05(h) (discussing Affinity Labs). That is, although these additional elements do limit the use of the abstract idea, this type of limitation merely confines the use of the abstract idea to a particular technological environment (e.g., sentiment analysis techniques) and does not integrate the abstract idea into a practical application or add an inventive concept to the claims.
Claims 9-12, 23 and 24 recite the additional elements of displaying sorted images, spliced text, a trigger control and media content. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are recited at a high-level of generality (i.e., as generic graphical user interface elements) such that it amounts to no more than mere instructions to apply the exception using generic computer components.
Claim 13 recites the additional elements of generating a recommend image and text using image and text generation models based on obtaining user generated editing. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are only a general link to a field of use or technological environment, see MPEP 2106.05(h) (discussing Affinity Labs). That is, although these additional elements do limit the use of the abstract idea, this type of limitation merely confines the use of the abstract idea to a particular technological environment (i.e., generative AI for creating text and images based on user inputs) and does not integrate the abstract idea into a practical application or add an inventive concept to the claims.
Claim Rejections - 35 USC § 103
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.
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, 4-8, 13, 14 and 17-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cokely et al., US Pub. No. 2025/0245872, herein referred to as “Cokely”; in view of Conti et al, US Pub. No. 2015/0112981, herein referred to as “Conti”.
Regarding claim 1, Cokely teaches:
determining at least one piece of media content to be recommended (identifies music segments for sharing, ¶[0019]; see also ¶[0020] defining “music segment” and noting the segment can be an entire song);
obtaining, for each piece of media content, basic information corresponding to the piece of media content, and obtaining at least one type of interactive content generated based on the piece of media content (receives basic metadata and lyrics for song, e.g., ¶¶[0060], [0091] and Figs. 2 and 6, and data from messaging apps like sentiment, e.g., ¶¶[0055], [0094]),
generating, based on the basic information corresponding to each piece of media content and the at least one type of interactive content, recommended content corresponding to the piece of media content, wherein the recommended content comprises a recommended image (generates image based on music segment data and sentiment data, e.g., ¶¶[0042], [0047])
and a recommended text (generates natural language outputs like tags based on music segment data, ¶¶[0040]-[0041], and user request, ¶¶[0050]-[0051] and Fig. 5);
and the recommended text comprises the basic information of the piece of media content (generates tags based on basic metadata, ¶0061])
and content generated based on the interactive content that highlights characteristics of the piece of media content (generates images based on sentiment information, ¶¶[0047], [0094]);
and generating target recommended content based on the recommended content corresponding to each piece of media content, and posting the target recommended content (provides music segment with generated image in shareable formant other users can access, ¶[0124] and Fig. 9; see also ¶[0069] noting music segment is stored with the tags);
wherein generating, based on the basic information corresponding to each piece of media content and the at least one type of interactive content, the recommended content corresponding to the piece of media content comprises (provides music segment with generated image in shareable formant other users can access, ¶[0124] and Fig. 9):
generating, for each piece of media content and based on the basic information corresponding to the piece of media content, the recommended image associated with the piece of media content (generates image based on music segment data and sentiment data, e.g., ¶¶[0042], [0047]),
generating, based on the basic information corresponding to the piece of media content and the at least one type of interactive content, the recommended text associated with the piece of media content (generates natural language outputs like tags based on music segment data, ¶¶[0040]-[0041], and user requests, ¶¶[0050]-[0051] and Fig. 5),
and generating, based on the recommended image and the recommended text, the recommended content corresponding to the piece of media content (provides music segment with generated image in shareable formant other users can access, ¶[0124] and Fig. 9; see also ¶[0069] noting music segment is stored with the tags);
wherein obtaining the basic information corresponding to the piece of media content comprises (receives basic metadata and lyrics for song, e.g., ¶¶[0060], [0091] and Figs. 2 and 6, and data from messaging apps like sentiment, e.g., ¶¶[0055], [0094]):
obtaining the basic information from preset parameters associated with the piece of media content, wherein the basic information comprises one or more of a content title, a content parameter, introduction information, and a cover image (receives basic metadata and lyrics for song, e.g., ¶¶[0060], [0091]);
and wherein generating, based on the basic information corresponding to the piece of media content, the recommended image associated with the piece of media content comprises (generates image based on music segment data and sentiment data, e.g., ¶¶[0042], [0047], and receives lyrics for song, e.g., ¶¶[0060], [0091] and Figs. 2 and 6; see also ¶[0050] discussing receiving song title, etc.);
inputting the basic information into a predetermined image generation model to obtain the recommended image output by the image generation model (uses machine-learning image generation model to generate image, ¶[0042]; see also ¶¶[0091], [0100] and Fig. 6 discussing generating image based on lyrics),
wherein the recommended image comprises one or more of the content title, the content parameter, the introduction information, and the cover image, and a color of the recommended image matches that of the cover image (generates image with song title, artist, etc., ¶[0044]).
However Cokely does not teach but Conti does teach:
the interactive content comprising review information posted by historical users based on the piece of media content and content marked by the users in the piece of media content (extracts reviews for products, e.g., ¶¶[0013]-[0014]; see also ¶¶[0003], [0020] noting reviews are contained in documents).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the music sharing of Cokely with the search engine using sentiment analysis of Conti because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, Cokely searches the internet, e.g., ¶[0065]. One of ordinary skill would have recognized the search would likely be improved by incorporating the click through information of Conti.
Regarding claim 4, the combination of Cokely and Conti teaches all the limitations of claim 1 and Cokely further teaches:
wherein generating, based on the basic information corresponding to the piece of media content and the at least one type of interactive content, the recommended text associated with the piece of media content comprises: inputting, for each piece of media content, the basic information associated with the piece of media content and the at least one type of interactive content into a predetermined text generation model, to obtain the recommended text generated by the text generation model (generates natural language outputs like tags based on music segment data, ¶¶[0040]-[0041], and user requests, ¶¶[0050]-[0051] and Fig. 5).
Regarding claim 5, the combination of Cokely and Conti teaches all the limitations of claim 1 and Cokely further teaches:
wherein obtaining the basic information corresponding to the piece of media content, and obtaining the at least one type of interactive content generated based on the piece of media content comprises: obtaining, from the preset parameters associated with the piece of media content, introduction information and/or classification label information associated with the piece of media content (receives basic metadata for song, e.g., ¶¶[0060], [0091] and Figs. 2 and 6; see also ¶[0050] discussing receiving song title, etc.);
and determining the introduction information and/or classification label information as the basic information (generates tags based on music segment data, ¶¶[0040]-[0041]; see also ¶[0069] noting music segment is stored with the tags);
and performing, based on a preset filtering condition, a filter operation on at least one type of interactive data associated with the piece of media content to obtain the at least one type of interactive information (searches for and receives music segments using tags, ¶[0049]. Examiner notes the present Specification discusses types of interactive information and content in ¶[0053] of the Specification as filed).
Regarding claim 6, the combination of Cokely and Conti teaches all the limitations of claim 5 and Conti further teaches:
wherein the interactive data comprises at least one piece of content marking data generated by a user for at least part of the piece of media content (extracts reviews for products, e.g., ¶¶[0013]-[0014]);
and performing, based on the preset filtering condition, the filter operation on the at least one type of interactive data associated with the piece of media content to obtain the at least one type of interactive information comprises: determining a number of historical views corresponding to each piece of content marking data (determines click information for documents, ¶[0015]);
and determining, as the interactive information, a piece of content marking data having a number of historical views greater than a preset number threshold from the at least one piece of content marking data (searches based on number of clicks being high enough, ¶[0015]).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the music sharing of Cokely with the search engine using sentiment analysis of Conti because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, Cokely searches the internet, e.g., ¶[0065]. One of ordinary skill would have recognized the search would likely be improved by incorporating the click through information of Conti.
Regarding claim 7, the combination of Cokely and Conti teaches all the limitations of claim 5 and Cokely further teaches:
wherein the interactive data comprises a plurality of pieces of image and text review data posted the historical users for the piece of media content (review information includes images and text, e.g., ¶¶[0016], [0021]);
and performing, based on the preset filtering condition, the filter operation on the at least one type of interactive data associated with the piece of media content to obtain the at least one type of interactive information comprises: performing, by using a predetermined text recognition model (uses optical character recognition, ¶[0021] and sentiment analysis process, ¶¶[0028], [0034]),
a filter operation on a plurality of pieces of image and text review data satisfying a first preset condition in the interactive data to obtain a plurality of pieces of first interactive data, wherein the first preset condition comprises an amount of data comprised in a piece of image and text review data satisfying a preset data amount condition, and the piece of image and text review data not comprising negative emotional content (filters out reviews whose sentiment magnitude is lower than a given empirically-obtained threshold, ¶[0028]);
determining an association parameter corresponding to each piece of first interactive data, and performing a filter operation on the plurality of pieces of first interactive data based on a preset interaction condition and the association parameter to obtain a plurality of pieces of second interactive data, wherein the association parameter comprises data amount information, an interaction parameter, and a browsing parameter of the piece of first interactive data (determines review information, e.g., ¶[0018], determines click information for documents, ¶[0015], and review source information, ¶[0016]);
and performing a filter operation on the plurality of pieces of second interactive data by a preset filtering word set to obtain the interactive information (filters out reviews whose sentiment magnitude is lower than a given empirically-obtained threshold, ¶[0028]; see also ¶¶[0029], [0033] discussing negative words).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the music sharing of Cokely with the search engine using sentiment analysis of Conti because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, Cokely searches the internet, e.g., ¶[0065]. One of ordinary skill would have recognized the search would likely be improved by incorporating the sentiment information of Conti.
Regarding claim 8, the combination of Cokely and Conti teaches all the limitations of claim 7 and Conti further teaches:
wherein the filtering word set comprises a positive word subset and a negative word subset (uses negative and positive words, ¶[0029]);
and performing the filter operation on the plurality of pieces of second interactive data by the preset filtering word set to obtain the interactive information comprises: performing a filtering-out operation on pieces of second interactive data comprising a word in the negative word subset in the plurality of pieces of second interactive data, to obtain a plurality of pieces of filtered second interactive data (filters out reviews whose sentiment magnitude is lower than a given empirically-obtained threshold, ¶[0028]; see also ¶¶[0029], [0033] discussing negative words);
and determining, as the interactive information, a piece of second interactive data comprising a word in the positive word subset in the plurality of pieces of filtered second interactive data (identifies candidate reviews having a sentiment magnitude above a threshold, e.g., ¶[0033]).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the music sharing of Cokely with the search engine using sentiment analysis of Conti because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, Cokely searches the internet, e.g., ¶[0065]. One of ordinary skill would have recognized the search would likely be improved by incorporating the sentiment information of Conti.
Regarding claim 13, the combination of Cokely and Conti teaches all the limitations of claim 1 and Cokely further teaches:
wherein after generating, based on the basic information corresponding to each piece of media content and the at least one type of interactive content, the recommended content corresponding to the piece of media content, the method further comprises: obtaining content of editing determined by a user based on the recommended content (user indicates user would prefer a custom and/or personalized image, ¶[0122]; see also Fig. 9 showing personalization process);
and performing an editing operation on the recommended content based on the content of editing, to obtain edited recommended content (iteratively generates image based on user’s personalization request until user indicates satisfaction with the generated image, ¶[0122] and Fig. 9);
and wherein generating the target recommended content based on the recommended content corresponding to each piece of media content comprises: generating the target recommended content based on each piece of edited recommended content (provides music segment with generated image in shareable formant other users can access, ¶[0124] and Fig. 9; see also ¶[0069] noting music segment is stored with the tags).
Regarding claims 14 and 20, claims 14 and 20 recite similar limitations as claim 1 and further recite “a processor and a memory, wherein the memory stores computer-executable instructions” and a “non-transitory computer-readable storage medium having stored therein computer- executable instructions”, respectively. These limitations are taught by Cokely in e.g., ¶¶[0006], [0021] and Fig. 1. Accordingly claims 14 and 20 are rejected for similar reasons as claim 1.
Regarding claims 17-19, 21 and 22, claims 17-19, 21 and 22 recite similar limitations as claims 4-8 and accordingly are rejected for similar reasons as claims 4-8.
Claim(s) 9-12, 23, and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cokely and Conti further in view of Confrey et al, US Pub. No. 2010/0128042, herein referred to as “Confrey”.
Regarding claim 9, the combination of Cokely and Conti teaches all the limitations of claim 1 and Cokely further teaches:
performing, based on the determination order, a sorting operation on recommended images associated with the at least one piece of media content to obtain sorted recommended images (iteratively generates image based on user’s personalization request until user indicates satisfaction with the generated image, ¶[0122] and Fig. 9);
displaying the sorted recommended images in a predetermined first display area (provides images to user, e.g., ¶[0122]).
However the combination of Cokely and Conti does not teach but Confrey does teach:
wherein generating the target recommended content based on the recommended content corresponding to each piece of media content comprises: determining a determination order corresponding to the at least one piece of media content (divides the text into a series of sequential display targets, ¶¶[0110], [0127] and Figs.2 and 3)
performing, based on the determination order, a splicing operation on the recommended text corresponding to the at least one piece of media content to obtain spliced recommended texts (divides the text into a series of sequential display targets, ¶¶[0110], [0127] and Figs.2 and 3);
and displaying the spliced recommended texts in a predetermined second display area to obtain the target recommended content (displays text, e.g., ¶¶[0128]-[0129], [0152]).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the music sharing of Cokely and Conti with the flow of text and media of Confrey because Confrey explicitly suggests doing so to make the text more engaging, perceptually focusing, and cognitively immersive, e.g., Abstract of Confrey; see also MPEP 2143.I.G.
Regarding claim 10, the combination of Cokely, Conti and Confrey teaches all the limitations of claim 9 and Cokely further teaches:
wherein after generating the target recommended content based on the recommended content corresponding to each piece of media content, the method further comprises: displaying, in a display area associated with each recommended image, a trigger control corresponding to the piece of media content associated with the recommended image, wherein the trigger control is configured to display the piece of media content in response to a trigger operation of a user after the target recommended content is posted (sharable format includes link that another user can use to access the music segment, ¶[0124])
Regarding claim 11, the combination of Cokely, Conti and Confrey teaches all the limitations of claim 9 and Cokely further teaches:
a trigger control corresponding to the piece of media content in a display area associated with the recommended text, wherein the trigger control is configured to display the piece of media content in response to a trigger operation of a user after the target recommended content is posted (sharable format includes link that another user can use to access the music segment, ¶[0124]).
However the combination of Cokely and Conti does not teach but Confrey does teach
wherein after performing, based on the determination order, the splicing operation on the recommended text corresponding to the at least one piece of media content to obtain the spliced recommended texts, the method further comprises: displaying, for a recommended text corresponding to each piece of media content in the spliced recommended texts (divides the text into a series of sequential display targets, ¶¶[0110], [0127] and Figs.2 and 3, and displays text, e.g., ¶¶[0128]-[0129], [0152]; see also ¶¶[0109], [0118] discussing composer tool allowing the visual, aural, or semantic enhancement of a Text Flow through the insertion of Other Media).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the music sharing of Cokely and Conti with the flow of text and media of Confrey because Confrey explicitly suggests doing so to make the text more engaging, perceptually focusing, and cognitively immersive, e.g., Abstract of Confrey; see also MPEP 2143.I.G.
Regarding claim 12, the combination of Cokely, Conti and Confrey teaches all the limitations of claim 9 and Cokely further teaches:
obtaining a target image determined by a user; and displaying the target image before the sorted recommended images (iteratively generates image based on user’s personalization request until user indicates satisfaction with the generated image, ¶[0122] and Fig. 9).
Regarding claims 23 and 24, claims 23 and 24 recite similar limitations as claims 9 and 10 and accordingly are rejected for similar reasons as claims 9 and 10.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Tsui et al., US Pub No. 2025/0278874 teaches a similar text and image generative process
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRENDAN S O'SHEA whose telephone number is (571) 270-1064. The examiner can normally be reached Monday to Friday 11-7.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nathan Uber can be reached at (571) 270-3923. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BRENDAN S O'SHEA/Examiner, Art Unit 3626
