Prosecution Insights
Last updated: April 19, 2026
Application No. 19/071,105

METHOD, APPARATUS, DEVICE AND STORAGE MEDIUM FOR CONTENT MANAGEMENT

Non-Final OA §103
Filed
Mar 05, 2025
Examiner
PARCHER, DANIEL W
Art Unit
2174
Tech Center
2100 — Computer Architecture & Software
Assignee
BEIJING ZITIAO NETWORK TECHNOLOGY CO., LTD.
OA Round
3 (Non-Final)
61%
Grant Probability
Moderate
3-4
OA Rounds
3y 1m
To Grant
99%
With Interview

Examiner Intelligence

Grants 61% of resolved cases
61%
Career Allow Rate
160 granted / 264 resolved
+5.6% vs TC avg
Strong +59% interview lift
Without
With
+59.4%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
35 currently pending
Career history
299
Total Applications
across all art units

Statute-Specific Performance

§101
4.8%
-35.2% vs TC avg
§103
55.6%
+15.6% vs TC avg
§102
17.5%
-22.5% vs TC avg
§112
16.9%
-23.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 264 resolved cases

Office Action

§103
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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/12/2025 has been entered. Response to Amendment The Amendment filed 11/12/2025 has been entered. Claims 6 has been cancelled. Claims 1-4 and 7-19 remain pending in the application. Applicant’s amendments to the Specification have overcome the objection previously set forth. Response to Arguments Applicant’s arguments with respect to rejections under prior art have been fully considered and are moot upon a new ground(s) of rejection, as necessitated by amendment, as outlined below. Prior Art Listed herein below are the prior art references relied upon in this Office Action: Hanes et al. (US Patent Application Publication 2025/0036674), referred to as Hanes herein [previously cited]. Bruno et al. (US Patent Application Publication 2016/0048772), referred to as Bruno herein [previously cited]. Swift et al. (US Patent Application Publication 2022/0092272), referred to as Swift herein [previously cited]. Lyren (US Patent Application Publication 2014/0359439) – referred to as Lyren herein [previously cited]. Klein et al. (US Patent Application Publication 2023/0237091) – referred to as Klein herein [previously cited]. Sachindran et al. (US Patent Application Publication 2025/0094506) – referred to as Sachindran herein. Examiner’s Note Strikethrough notation in the pending claims has been added by the Examiner. 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) 1-4, 12-13 and 15-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hanes in view of Sachindran. Regarding claim 1, Hanes discloses a method for generating and presenting content based on determining attribute features, comprising (Hanes, Abstract – user attributes indicative of comprehension level. Responses are tailored to the user attributes): receiving a query from a user (Hanes, Fig. 5 with ¶0035-¶0037 – user presents a query to an AI model); determining one or more attribute features associated with the user by a computing device based on an interaction history between the user and the computing device, wherein the one or more attribute features indicate a preference of the user for a determining first content to be presented in response to the query (Hanes. Figs. 3 and 7 with ¶0018, ¶0026-¶0030, ¶0046 – AI response to the query (first content) is received. If the content matches the user comprehension level, the content can be provided); converting the first content to second content based on the one or more attribute features, wherein the second content is a assessed. ¶0026-¶0030 – AI response (first content) is adjusted (second content) based on user attributes until it matches the user comprehension, and then is delivered to the user. See also Figs. 5-6 with ¶0035-¶0036) However, Hanes appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor, Sachindran discloses an LLM interface for displaying responses to user input queries (Sachindran, Abstract, ¶0065), including knowledge-seeking queries (Sachindran, ¶0049-¶0054), including wherein the one or more attribute features indicate a preference of the user for a summary of content (Sachindran, ¶0021-0024, ¶0031-0032, ¶0034, ¶0059, ¶0092 – Summary of query results is generated based on user attributes and preferences including technical skill level). presenting the summary of the first content in a designated area of an interface while the first content is presented in a different designated area of the interface (Sachindran, Figs. 1-3, 8 with Abstract with ¶0020-¶0022, ¶0036-¶0037, ¶0075, and ¶0174 – the summary and at least one summarized query result are displayed simultaneously in different display areas). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the responses of Hanes to include displaying summaries together with query results based on the teachings of Sachindran. The motivation for doing so would have been to provide a quick resource for understanding query results (Sachindran, ¶0025, ¶0042), while providing detailed access to individual results and references, thereby enabling the user access to source material if desired for verification or additional detail (Sachindran, ¶0032). Regarding claim 2, Hanes as modified discloses the limitations of claim 1 above, and further discloses wherein the one or more attribute features comprise a plurality of attribute features, and the plurality of attribute features comprise at least one of: a language type that the user desires to use, an understanding degree of the user for a domain to which the first content belongs, a focus of the user on the first content, and a presentation format that the user desires to use (Hanes, ¶0017 -¶0025 – user comprehension level is assessed. ¶0026-¶0030 – AI response (first content) is adjusted (second content) based on user attributes until it matches the user comprehension, and then is delivered to the user). Regarding claim 3, Hanes as modified discloses the limitations of claim 2 above, and further discloses determining a set of target attribute features from the plurality of attribute features; and converting the first content to the second content based on the set of target attribute features (Hanes, ¶0017 -¶0025 – user comprehension level is assessed. ¶0026-¶0030 – AI response (first content) is adjusted (second content) based on user attributes until it matches the user comprehension, and then is delivered to the user). Regarding claim 4, Hanes as modified discloses the elements of claim 1 above, and further discloses wherein the designated area comprising at least a portion of a display area of the interface or a floating layer area superimposed over the display area of the interface (Hanes, Figs. 5-6 with ¶0035-¶0036 – response is displayed in the response area under the query. Sachindran, Figs. 1-3, 8 with Abstract with ¶0020-¶0022, ¶0075, and ¶0174 – the summary is displayed adjacent to at least one summarized query result). Regarding claim 12, Hanes as modified discloses the elements of claim 1 above, and further discloses wherein updating the one or more attribute features based on the update request in response to receiving an update request (Hanes, Figs. 5-6 with ¶0035-¶0036 – first and second prompts can generate first and second content. The second prompt is generated based on additional user context being injected into the query, resulting in the second content being presented in the designated area below the second query). Regarding claim 13, Hanes as modified discloses the elements of claim 1 above, and further discloses wherein presenting the summary of the first content comprises presenting the second content in response to determining that the one or more attribute features are activated (Hanes, Figs. 5-6 with ¶0035-¶0036 – first and second prompts can generate first and second content. The second prompt is generated based on additional user context being injected into the query, resulting in the second content being presented in the designated area below the second query). Regarding claim 15, Hanes discloses an electronic device, comprising: at least one processor; and at least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor, the instructions, when executed by the at least one processor, causing the electronic device to perform acts comprising: receiving a query from a user (Hanes, Fig. 5 with ¶0035-¶0037 – user presents a query to an AI model. ¶0056-¶0057 – processor executing instructions stored in memory); determining one or more attribute features associated with the user by a computing device based on an interaction history between the user and the computing device, wherein the one or more attribute features indicate a preference of the user for a ¶0034 – user comprehension can be from user-specified declarations or through behavioral profiling based on inputs); determining first content to be presented in response to the query (Hanes. Figs. 3 and 7 with ¶0018, ¶0026-¶0030, ¶0046 – AI response to the query (first content) is received. If the content matches the user comprehension level, the content can be provided); converting the first content to second content based on the one or more attribute features, wherein the second content is a However, Hanes appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor, Sachindran discloses an LLM interface for displaying responses to user input queries (Sachindran, Abstract, ¶0065), including knowledge-seeking queries (Sachindran, ¶0049-¶0054), including wherein the one or more attribute features indicate a preference of the user for a summary of content (Sachindran, ¶0021-0024, ¶0031-0032, ¶0034, ¶0059, ¶0092 – Summary of query results is generated based on user attributes and preferences including technical skill level). presenting the summary of the first content in a designated area of an interface while the first content is presented in a different designated area of the interface (Sachindran, Figs. 1-3, 8 with Abstract with ¶0020-¶0022, ¶0036-¶0037, ¶0075, and ¶0174 – the summary and at least one summarized query result are displayed simultaneously in different display areas). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the responses of Hanes to include displaying summaries together with query results based on the teachings of Sachindran. The motivation for doing so would have been to provide a quick resource for understanding query results (Sachindran, ¶0025, ¶0042), while providing detailed access to individual results and references, thereby enabling the user access to source material if desired for verification or additional detail (Sachindran, ¶0032). Regarding claim 16, Hanes discloses a non-transitory computer-readable storage medium storing a computer program thereon, the computer program, when executed by a processor, causing the processor to perform acts comprising: receiving a query from a user (Hanes, Fig. 5 with ¶0035-¶0037 – user presents a query to an AI model. ¶0056-¶0057 – processor executing instructions stored in memory); determining one or more attribute features associated with the user by a computing device based on an interaction history between the user and the computing device, wherein the one or more attribute features indicate a preference of the user for a determining first content to be presented in response to the query (Hanes. Figs. 3 and 7 with ¶0018, ¶0026-¶0030, ¶0046 – AI response to the query (first content) is received. If the content matches the user comprehension level, the content can be provided); converting the first content to second content based on the one or more attribute features, wherein the second content is a However, Hanes appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor, Sachindran discloses an LLM interface for displaying responses to user input queries (Sachindran, Abstract, ¶0065), including knowledge-seeking queries (Sachindran, ¶0049-¶0054), including wherein the one or more attribute features indicate a preference of the user for a summary of content (Sachindran, ¶0021-0024, ¶0031-0032, ¶0034, ¶0059, ¶0092 – Summary of query results is generated based on user attributes and preferences including technical skill level). presenting the summary of the first content in a designated area of an interface while the first content is presented in a different designated area of the interface (Sachindran, Figs. 1-3, 8 with Abstract with ¶0020-¶0022, ¶0036-¶0037, ¶0075, and ¶0174 – the summary and at least one summarized query result are displayed simultaneously in different display areas). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the responses of Hanes to include displaying summaries together with query results based on the teachings of Sachindran. The motivation for doing so would have been to provide a quick resource for understanding query results (Sachindran, ¶0025, ¶0042), while providing detailed access to individual results and references, thereby enabling the user access to source material if desired for verification or additional detail (Sachindran, ¶0032). Regarding claim 17, Hanes as modified discloses the limitations of claim 15 above, and further discloses wherein the one or more attribute features comprise a plurality of attribute features, and the plurality of attribute features comprise at least one of: a language type that the user desires to use, an understanding degree of the user for a domain to which the first content belongs, a focus of the user on the first content, and a presentation format that the user desires to use (Hanes, ¶0017 -¶0025 – user comprehension level is assessed. ¶0026-¶0030 – AI response (first content) is adjusted (second content) based on user attributes until it matches the user comprehension, and then is delivered to the user). Regarding claim 18, Hanes as modified discloses the limitations of claim 17 above, and further discloses determining a set of target attribute features from the plurality of attribute features; and converting the first content to the second content based on the set of target attribute features (Hanes, ¶0017 -¶0025 – user comprehension level is assessed. ¶0026-¶0030 – AI response (first content) is adjusted (second content) based on user attributes until it matches the user comprehension, and then is delivered to the user). Regarding claim 19, Hanes as modified discloses the limitations of claim 15 above, and further discloses wherein, the designated area comprises at least a portion of a display area of the interface or a floating layer area superimposed over the display area of the interface (Hanes, Figs. 5-6 with ¶0035-¶0036 – response is displayed in the response area under the query. Sachindran, Figs. 1-3, 8 with Abstract with ¶0020-¶0022, ¶0075, and ¶0174 – the summary is displayed adjacent to at least one summarized query result). Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hanes in view of Sachindran in further view of Bruno. Regarding claim 7, Hanes as modified discloses the elements of claim 1 above. However, Hanes appears not to expressly disclose wherein the interaction history comprises at least one of: a historical processing request submitted by the user, and an access history of the user for a historical processing result of the historical processing request. However, in the same field of endeavor, Bruno discloses tailored response generation (Bruno, Abstract), including wherein the interaction history comprises at least one of: a historical processing request submitted by the user, and an access history of the user for a historical processing result of the historical processing request (Bruno, ¶0088-¶0092 – expertise level of the user is determined according to input history of the user, including previous questions). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the user comprehension of Hanes as modified to include determination based on input history based on the teachings of Bruno. The motivation for doing so would have been to improve user satisfaction, learning gains, task success, engagement, and overall benefit (Bruno, ¶0024). Claim(s) 8-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hanes in view of Sachindran in further view of Swift. Regarding claim 8, Hanes as modified discloses the elements of claim 1 above. However, Hanes appears not to expressly disclose wherein determining the one or more attribute features based on the interaction history comprises: determining a language type that the user desires to use based on a language used in the interaction history. However, in the same field of endeavor, Swift discloses a chatbot for assisting a user in response to queries (Swift, Abstract with ¶0008-¶0009) determining the one or more attribute features based on the interaction history comprises: determining a language type that the user desires to use based on a language used in the interaction history (Swift, Fig. 2 with Abstract and ¶0023-¶0026, ¶0032 – user/chatbot language is determined according to preferences, previous correspondence). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the response tailoring of Hanes as modified to include language determination based on input history based on the teachings of Swift. The motivation for doing so would have been to communication efficacy and support users the speak different languages are have widely different fluency levels in languages (Swift, ¶0003, ¶0008). Regarding claim 9, Hanes as modified discloses the elements of claim 1 above, and further discloses wherein determining the one or more attribute features based on the interaction history comprises: determining, based on the interaction history, an understanding degree of the user for a domain to which the first content belongs, a focus of the user on the first content, ¶0026-¶0030 – AI response is adjusted until it matches the user comprehension, and then is delivered to the user). However, Hanes appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor, Swift discloses a chatbot for assisting a user in response to queries (Swift, Abstract with ¶0008-¶0009) determining, based on the interaction history, a presentation format that the user desires to use (Swift, Fig. 2 with Abstract and ¶0023-¶0026, ¶0032 – user/chatbot language is determined according to preferences, previous correspondence). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the response tailoring of Hanes as modified to include language determination based on input history based on the teachings of Swift. The motivation for doing so would have been to communication efficacy and support users the speak different languages are have widely different fluency levels in languages (Swift, ¶0003, ¶0008). Claim(s) 10-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hanes in view of Sachindran in further view of Lyren. Regarding claim 10, Hanes as modified discloses the elements of claim 1 above, and further discloses wherein one or more attribute features comprise a plurality of attribute features for a instructions stored in memory. ¶0013 – AI model providing responses to user queries. ¶0045 – AI model generates responses according to training on the topic). However, Hanes appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor, Lyren discloses intelligent software agents responding to user queries (Lyren, Abstract with ¶0001), Including the processing system comprises a plurality of digital assistants, and the one or more attribute features comprise a plurality of attribute features for the plurality of digital assistants, respectively, and the method further comprises: selecting a first digital assistant from the plurality of digital assistants in response to receiving a processing request to obtain the first content; and obtaining the first content according to a first attribute feature of the first digital assistant (Lyren, Fig. 10 with ¶0160-¶0172 – selecting a particular use agent based on the task or action to be performed. Fig. 4 with ¶0095-¶0104 – actions are performed according to the personality of the agent. Fig. 15 with ¶0209-¶0212 – agents have particular specialties). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the chat bot of Hanes as modified to include a plurality of digital assistant based on the teachings of Lyren. The motivation for doing so would have been to improve user engagement (Lyren, ¶0242) and to more effectively adapt to user preferences and task parameters (Lyren, ¶0129). Regarding claim 11, Hanes as modified discloses the elements of claim 10 above, and further discloses wherein the first attribute feature of the first digital assistant is different from a second attribute feature of a second digital assistant of the plurality of digital assistants (Lyren, Fig. 10 with ¶0160-¶0172 – selecting a particular use agent based on the task or action to be performed. Fig. 4 with ¶0095-¶0104 – actions are performed according to the personality of the agent. Fig. 15 with ¶0209-¶0212 – agents have particular specialties). Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hanes in view of Sachindran in further view of Klein. Regarding claim 14, Hanes as modified discloses the elements of claim 7 above. However, Hanes appears not to expressly disclose wherein the historical processing comprises at least one of: a request to search for a media item; a request to process a remote media item; a request to process a local media item; and a request to generate a media item. However, in the same field of endeavor, Klein discloses a digital assistant (Klein, Abstract), including wherein the historical processing comprises at least one of: a request to search for a media item; a request to process a remote media item; a request to process a local media item; and a request to generate a media item (Klein, Abstract, ¶0011, ¶0015-¶0021, ¶0033, ¶0044, ¶0053, and Fig. 2C-2D with ¶0057-¶0061 – querying image contents. ¶0038-¶0039 – smartphone camera). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the queries of Hanes as modified to include media items based on the teachings of Klein. The motivation for doing so would have been to more effectively assist users by enabling users to present visual queries pertaining to visual features captured in media (Klein, ¶0031-¶0032). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL W PARCHER whose telephone number is (303)297-4281. The examiner can normally be reached Monday - Friday, 9:00am - 5:00pm, Mountain Time. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William Bashore can be reached at (571)272-4088 (Eastern Time). The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /DANIEL W PARCHER/Primary Examiner, Art Unit 2174
Read full office action

Prosecution Timeline

Mar 05, 2025
Application Filed
Apr 23, 2025
Non-Final Rejection — §103
Jul 28, 2025
Response Filed
Aug 08, 2025
Final Rejection — §103
Oct 07, 2025
Response after Non-Final Action
Nov 12, 2025
Request for Continued Examination
Nov 19, 2025
Response after Non-Final Action
Feb 23, 2026
Non-Final Rejection — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12596464
ELECTRONIC APPARATUS AND METHOD FOR PROVIDING USER INTERFACE THEREOF
2y 5m to grant Granted Apr 07, 2026
Patent 12591347
USER INTERFACES FOR INDICATING STATUS OF A TRACKED ENTITY
2y 5m to grant Granted Mar 31, 2026
Patent 12591607
AUTOMATED CONTENT CREATION AND CONTENT SERVICES FOR COLLABORATION PLATFORMS
2y 5m to grant Granted Mar 31, 2026
Patent 12578977
OMNI-CHANNEL MICRO FRONTEND CONTROL PLANE
2y 5m to grant Granted Mar 17, 2026
Patent 12541378
SYSTEMS AND METHODS FOR GENERATING AND PROVIDING A DYNAMIC USER INTERFACE
2y 5m to grant Granted Feb 03, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

3-4
Expected OA Rounds
61%
Grant Probability
99%
With Interview (+59.4%)
3y 1m
Median Time to Grant
High
PTA Risk
Based on 264 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month