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 .
Response to Amendment
The Amendment filed 5/22/2026 has been entered. Claims 1-4 and 7-19 remain pending in the application.
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 [previously cited].
Shivakumar (US Patent Application Publication 2015/0081611) – referred to as Shivakumar herein.
Lovitt et al. (US Patent Application Publication 2024/0297863) – referred to as Lovitt 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, 7, 9, 12-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hanes in view of Sachindran in further view of Shivakumar in further view of Lovitt.
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):
determining attribute features associated with a user by a computing device based on an interaction history between the user and the computing device, wherein the attribute features comprise a
receiving a query from the user (Hanes, Fig. 5 with ¶0035-¶0037 – user presents a query to an AI model);
determining first content 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 attribute features in response to detecting that the first content does not match at least a subset of attribute features, wherein the second content matches the attribute features; and presenting the second content (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. See also Figs. 5-6 with ¶0035-¶0036)
same query as the first, but with context that may cause iteration on the first content, resulting in the second content to be presented being different than the first).
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).
However, Hanes appears not to expressly disclose wherein the attribute features comprise a language the user desires and wherein formats of presenting content comprise a graphic-and-text format, an audio format, and a video format. However, in the same field of endeavor, Shivakumar discloses an AI learning system and NLP-based processing for customizing content summarization (Shivakumar, Abstract with ¶0030 and ¶0058), including
determining attribute features associated with a user by a computing device based on an interaction history between the user and the computing device, wherein the attribute features comprise a language the user desires, an inclination of the user for a summary of content, and a format of presenting content the user desires, and wherein formats of presenting content comprise a plain text format, a graphic-and-text format, an audio format (Shivakumar, ¶0024 – user preferences for content presentation type. ¶0040 – user preferences are determined from user activity data. ¶0041-¶0042 – user preferences include language, media type, content type. ¶0036, ¶0044-¶0047 – infographics (graphic and text format), news graph. ¶0044, ¶0048 and claim 7 as published – bulleted list text summary format. Audio format via text-to-speech, concept maps (graphics)).
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 user preferences for formatting based on the teachings of Shivakumar. The motivation for doing so would have been to enable the user to more effectively and easily understand the content being summarized, and understand the significance and relevance of the content (Shivakumar, ¶0002-¶0004).
However, Hanes as modified appears not to expressly disclose a video format. However, in the same field of endeavor, Lovitt discloses summary generation, including a level of detail for the summary (Lovitt, Abstract), including
an inclination of the user for a summary of content, and a format of presenting content the user desires, and wherein formats of presenting content comprise a plain text format and an audio format, and a video format (Lovitt, ¶0060 – summary format preference includes a preference for text, audio, video data).
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 user preferences for video formatting based on the teachings of Lovitt. The motivation for doing so would have been to enable the user to more easily and quickly understand the content being summarized, (Lovitt, ¶0058), especially for users who more easily comprehend and prefer video formats.
Regarding claim 2, Hanes as modified discloses the limitations of claim 1 above, and further discloses wherein the attribute features further comprise at least one of: an understanding degree of the user for a domain to which the first content belongs and a focus of the user on the first content (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 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 second content is presented at a designated area comprising at least a portion of a display area of an 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 7, Hanes as modified discloses the elements of claim 1 above. However, Hanes appears not to expressly disclose wherein the interaction history further 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 (Shivakumar, ¶0029, ¶0040, ¶0042, ¶0054 – user preferences are determined from user activity data. Activity data includes access interactions with presented content).
Regarding claim 9, Hanes as modified discloses the elements of claim 1 above, and further discloses wherein determining the 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 and a focus of the user on the first content (Hanes, ¶0017-¶0025 – user comprehension level is assessed. ¶0026-¶0030 – AI response is adjusted until it matches the user comprehension, and then is delivered to the user. Shivakumar, ¶0024 – user preferences for content presentation type. ¶0040 – user preferences are determined from user activity data. Lovitt, Abstract – user preference for level of detail).
Regarding claim 12, Hanes as modified discloses the elements of claim 1 above, and further discloses wherein updating the attribute features based on an update request in response to receiving the 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 a 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 14, Hanes as modified discloses the elements of claim 7 above, and further discloses 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 (Shivakumar, ¶0023, ¶0028, ¶0034, ¶0049, ¶0057 – user requested content includes online media files).
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: (Hanes, Fig. 5 with ¶0035-¶0037 – user presents a query to an AI model. ¶0056-¶0057 – processor executing instructions stored in memory);
determining attribute features associated with a user by a computing device based on an interaction history between the user and the computing device, wherein the attribute features comprise a inputs. In this case, the preference of the user can be user comprehension level of the response. Fig. 5 and ¶0021 – plain text output);
receiving a query from the user (Hanes, Fig. 5 with ¶0035-¶0037 – user presents a query to an AI model);
determining first content 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 attribute features in response to detecting that the first content does not match at least a subset of the attribute features, wherein the second content matches the attribute features; and presenting the second content (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. 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).
However, Hanes appears not to expressly disclose wherein the attribute features comprise a language the user desires and wherein formats of presenting content comprise a graphic-and-text format, an audio format, and a video format.
However, in the same field of endeavor, Shivakumar discloses an AI learning system and NLP-based processing for customizing content summarization (Shivakumar, Abstract with ¶0030 and ¶0058), including
determining attribute features associated with a user by a computing device based on an interaction history between the user and the computing device, wherein the attribute features comprise a language the user desires, an inclination of the user for a summary of content, and a format of presenting content the user desires, and wherein formats of presenting content comprise a plain text format, a graphic-and-text format, an audio format (Shivakumar, ¶0024 – user preferences for content presentation type. ¶0040 – user preferences are determined from user activity data. ¶0041-¶0042 – user preferences include language, media type, content type. ¶0036, ¶0044-¶0047 – infographics (graphic and text format), news graph. ¶0044, ¶0048 and claim 7 as published – bulleted list text summary format. Audio format via text-to-speech, concept maps (graphics)).
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 user preferences for formatting based on the teachings of Shivakumar. The motivation for doing so would have been to enable the user to more effectively and easily understand the content being summarized, and understand the significance and relevance of the content (Shivakumar, ¶0002-¶0004).
However, Hanes as modified appears not to expressly disclose a video format. However, in the same field of endeavor, Lovitt discloses summary generation, including a level of detail for the summary (Lovitt, Abstract), including
an inclination of the user for a summary of content, and a format of presenting content the user desires, and wherein formats of presenting content comprise a plain text format and an audio format, and a video format (Lovitt, ¶0060 – summary format preference includes a preference for text, audio, video data).
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 user preferences for video formatting based on the teachings of Lovitt. The motivation for doing so would have been to enable the user to more easily and quickly understand the content being summarized, (Lovitt, ¶0058), especially for users who more easily comprehend and prefer video formats.
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: (Hanes, Fig. 5 with ¶0035-¶0037 – user presents a query to an AI model. ¶0056-¶0057 – processor executing instructions stored in memory);
determining attribute features associated with a user by a computing device based on an interaction history between the user and the computing device, wherein the attribute features comprise a
receiving a query from the user (Hanes, Fig. 5 with ¶0035-¶0037 – user presents a query to an AI model);
determining first content 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 attribute features in response to detecting that the first content does not match at least a subset of the attribute features, wherein the second content matches the attribute features; and presenting the second content (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. See also Figs. 5-6 with ¶0035-¶0036)
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. The second query is the same query as the first, but with context that may cause iteration on the first content, resulting in the second content to be presented being different than the first).
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).
However, Hanes appears not to expressly disclose wherein the attribute features comprise a language the user desires and wherein formats of presenting content comprise a graphic-and-text format, an audio format, and a video format. However, in the same field of endeavor, Shivakumar discloses an AI learning system and NLP-based processing for customizing content summarization (Shivakumar, Abstract with ¶0030 and ¶0058), including
determining attribute features associated with a user by a computing device based on an interaction history between the user and the computing device, wherein the attribute features comprise a language the user desires, an inclination of the user for a summary of content, and a format of presenting content the user desires, and wherein formats of presenting content comprise a plain text format, a graphic-and-text format, an audio format (Shivakumar, ¶0024 – user preferences for content presentation type. ¶0040 – user preferences are determined from user activity data. ¶0041-¶0042 – user preferences include language, media type, content type. ¶0036, ¶0044-¶0047 – infographics (graphic and text format), news graph. ¶0044, ¶0048 and claim 7 as published – bulleted list text summary format. Audio format via text-to-speech, concept maps (graphics)).
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 user preferences for formatting based on the teachings of Shivakumar. The motivation for doing so would have been to enable the user to more effectively and easily understand the content being summarized, and understand the significance and relevance of the content (Shivakumar, ¶0002-¶0004).
However, Hanes as modified appears not to expressly disclose a video format. However, in the same field of endeavor, Lovitt discloses summary generation, including a level of detail for the summary (Lovitt, Abstract), including
an inclination of the user for a summary of content, and a format of presenting content the user desires, and wherein formats of presenting content comprise a plain text format and an audio format, and a video format (Lovitt, ¶0060 – summary format preference includes a preference for text, audio, video data).
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 user preferences for video formatting based on the teachings of Lovitt. The motivation for doing so would have been to enable the user to more easily and quickly understand the content being summarized, (Lovitt, ¶0058), especially for users who more easily comprehend and prefer video formats.
Regarding claim 17, Hanes as modified discloses the limitations of claim 15 above, and further discloses wherein the attribute features further comprise at least one of: an understanding degree of the user for a domain to which the first content belongs, and 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 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 second content is presented at a designated area comprises at least a portion of a display area of an 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) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hanes in view of Sachindran in view of Sachindran in further view of Shivakumar in further view of Lovitt 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 attribute features based on the interaction history comprises: determining a language type that the user desires to use based on a
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).
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 Shivakumar in further view of Lovitt in further view of Lyren.
Regarding claim 10, Hanes as modified discloses the elements of claim 1 above, and further discloses wherein the attribute features comprise a plurality of attribute features for a
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).
Conclusion
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 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
Prosecution Insights