DETAILED ACTION
This action is in response to the application filed 6/28/2024 and subsequent amendment filed 5/3/2025.
Claims 1-20 have been submitted for examination.
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 .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 3-6, 16-18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Piagentini et al. (US 2023/0065188), hereinafter Piagentini, in view of Ferrucci et al. (US 2022)/0261817), hereinafter Ferrucci.
As per claim 1, Piagentini teaches the following:
a computer-implemented method for providing a recommendation panel for a graphical user interface of an issue tracking platform, (see abstract), the method comprising:
causing display of an intake portal graphical user interface of a frontend application of the issue tracking platform on a client device, (see Fig. 7);
in response to a user selection of a query category of the intake portal graphical user interface, causing creation of a particular issue, the particular issue assigned a request type corresponding to the query category. As Piagentini teaches in paragraph [0043], and corresponding Figs. 7 and 8, in response to a user selecting “Yes” to file a support case (query category), a ticket creation shown in Fig. 8 is created;
causing display of an issue-view graphical user interface including issue data of the particular issue. As Piagentini teaches in paragraph [0044], and corresponding Fig. 8, a support ticket interface is displayed with pre-populated fields (issue data);
in response to user input provided to the issue-view graphical user interface, generating additional issue data including one or more transaction messages. As Piagentini further teaches in paragraph [0044], while most of the interface elements are pre-populated, “the user can review, correct, and add to the error information”. Therefore, the user may add “one or more transaction messages”; and
a first section including a set of one or more selectable link objects, each selectable link object associated with a respective content item identified for the request type. Piagentini shows in Fig. 5, and corresponding paragraph [0038], related articles to an issue are displayed within a pop out window (first section).
issue data. Piagentini shows in Fig. 6, and corresponding paragraph [0040], that in response to the user selecting that discovered articles not assisting in an issue, a support team is notified.
However, Piagentini does not explicitly teach of a third section of a link to a matter expert. In a similar field of endeavor, Ferrucci teaches of support system and interface (see abstract). Ferrucci shows in Fig. 6 of a recommendation panel 604.
As Ferrucci teaches in paragraph [0054], and corresponding Fig. 1, UI element 128 (second section including a link) allows a user to invite an agent for support from a human agent. Ferrucci further teaches the following:
a third section including suggested action narrative (see Fig. 6, 604), the suggested action narrative determined by:
generating a prompt including at least a portion of the one or more transaction messages and content extracted from a content item. As Ferrucci shows in Fig. 6, and corresponding paragraph [0133], the dialog engine has analyzed the transactional messages the user has entered under “issues” and determined the problem as “the speakers do not receive audio” (generated prompt);
providing the prompt to a generative output engine. As Ferrucci teaches in paragraph [0023], “the system may configure domain models to provide artificial intelligence (AI) expertise for corresponding specific domain knowledge”; and
generating the suggested action narrative using a generative response received from the generative output engine in response to the prompt. As Ferrucci further shows in Fig. 6, and corresponding paragraph [0133], the engine has generated at least two suggested remedies. Ferrucci further teaches in paragraph [0035], of utilizing AI to understand user input.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the interface of Piagentini with the third panel and invite agent control of Ferrucci. One of ordinary skill would have been motivated to have such modification because as Ferrucci teaches in paragraph [0006], such multiple panels and assistance methods benefit users in assisting with more complex issues.
Regarding claim 3, modified Piagentini teaches the method of claim 11 as described. However, Piagentini does not explicitly teach of generating the prompt using extract content. Ferrucci teaches the following:
messages of the one or more transaction messages comprise actions performed to resolve the particular issue; and the prompt comprises at least a portion of the one or more messages. As Ferrucci teaches paragraph [0090], “in response to the user answering a question or advice and/or changing a visual component, the multimodal dialog engine 216 may update the session model to reflect any changes. In response to changes with input scenario, the multimodal dialog engine 216 may update visual presentation of diagnostics data to align with the input scenario”. The Examiner interprets updating the recommendation in response to the user answering advice as encompassing “transaction messages comprise actions performed”.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the interface of Piagentini with the third panel and invite agent control of Ferrucci. One of ordinary skill would have been motivated to have such modification because as Ferrucci teaches in paragraph [0006], such multiple panels and assistance methods benefit users in assisting with more complex issues.
Regarding claim 4, modified Piagentini teaches the method of claim 1 as described. However, Piagentini does not explicitly teach of utilizing keywords. Ferrucci teaches the following:
wherein each respective content item is selected using the request type and keywords extracted from an issue description associated with the issue data. As Ferrucci teaches in paragraph [0049], the search may include keywords and for terms beyond explicit keywords (request type).
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the issue input of Piagentini with the key concept extraction of Ferrucci. One of ordinary skill would have been motivated to have such modification because the concept identification of Ferrucci benefits users in allowing a more natural language input.
Regarding claim 5, modified Piagentini teaches the method of claim 1 as described. However, Piagentini does not explicitly teach utilizing keywords. Ferrucci teaches the following:
further comprising determining the subject matter using the request type and a semantic analysis of an issue description associated with the issue data. As Ferrucci teaches in paragraph [0049], the search may include keywords and for terms beyond explicit keywords (issue type).
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the issue input of Piagentini with the key concept extraction of Ferrucci. One of ordinary skill would have been motivated to have such modification because the concept identification of Ferrucci benefits users in allowing a more natural language input.
Regarding claim 6, modified Piagentini teaches the method of claim 1 as described. However, Piagentini does not explicitly teach updating suggested actions based on second user input. Ferrucci teaches the following:
in response to a user modification of the issue data, the method further comprises: generating a second prompt comprising the user modification to the issue data; providing the second prompt to the generative output engine; and causing the suggested action narrative to be updated using a second generated response received from the generative output engine in response to the second prompt. As Ferrucci teaches in paragraph [0135], and corresponding Fig. 7, the user may be prompted 704 to input additional information. Ferrucci further teaches in paragraph [0138], and corresponding Fig. 8 that the suggestions 806 and system diagram 804 are updated to reflect additional user input.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the issue input of Piagentini with the additional input of Ferrucci. One of ordinary skill would have been motivated to have such modification because the additional input of Ferrucci because as Ferrucci teaches in paragraph [0137], more targeted and filtered suggestions may be generated as more information about the context of a system is gathered.
As per claim 16, Piagentini teaches the following:
a computer-implemented method for providing a recommendation panel for a graphical user interface of an issue tracking platform, (see abstract), the method comprising:
causing display of an intake portal graphical user interface of a frontend application of the issue tracking platform on a client device, (see Fig. 7);
in response to a user selection of a query category of the intake portal graphical user interface, causing creation of a particular issue, the particular issue assigned a request type corresponding to the query category. As Piagentini teaches in paragraph [0043], and corresponding Figs. 7 and 8, in response to a user selecting “Yes” to file a support case (query category), a ticket creation shown in Fig. 8 is created;
causing display of an issue-view graphical user interface including issue data of the particular issue and transaction messages. As Piagentini teaches in paragraph [0044], and corresponding Fig. 8, a support ticket interface is displayed with pre-populated fields (issue data). As Piagentini further teaches in paragraph [0044], while most of the interface elements are pre-populated, “the user can review, correct, and add to the error information”. Therefore, the user may add “one or more transaction messages;
in response to user input provided to the issue-view graphical user interface, generating additional issue data. As Piagentini further teaches in paragraph [0044], while most of the interface elements are pre-populated, “the user can review, correct, and add to the error information”; and
causing display of the recommendation panel in the issue-view graphical user interface, the recommendation panel comprising:
a first section including a set of one or more selectable link objects, each selectable link object selected using data extracted from the issue data and the transaction messages. Piagentini shows in Fig. 5, and corresponding paragraph [0038], related articles to an issue are displayed within a pop out window (first section).
However, Piagentini does not explicitly teach of a second section comprising an action narrative. In a similar field of endeavor, Ferrucci teaches of support system and interface (see abstract). Ferrucci further teaches the following:
a second section including suggested action narrative, (see Fig. 6, 604), the suggested action narrative determined by:
generating a prompt including at least a portion of the issue data and the transaction messages. As Ferrucci teaches in paragraph [0132], and corresponding Fig. 6, in response to user input of an issue, a “Diagnosis” panel 604 is presented with a “Problem” identified (first prompt including a portion of different identified issues, i.e. user text input and diagram);
providing the prompt to a generative output engine. As Ferrucci teaches in paragraph [0023], the system configures domain models to provide AI expertise, thus the issue data is submitted to an AI (prompt to generative output engine); and
generating the suggested action narrative using a generative response received from the generative output engine in response to the prompt. See Fig. 6, “Causes & Remedies”.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the interface of Piagentini with the remedies panel of Ferrucci. One of ordinary skill would have been motivated to have such modification because as Ferrucci teaches in paragraph [0006], such multiple panels and assistance methods benefit users in assisting with more complex issues.
Regarding claim 17, modified Piagentini teaches the method of claim 16 as described. However, Piagentini does not explicitly teach of generating the prompt using extract content. Ferrucci teaches the following:
generating the prompt using extracted content from a content item identified using the issue data. As Ferrucci teaches in paragraph [0120], a semantic parser may indicate key concepts from user entered issue data.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the issue input of Piagentini with the key concept extraction of Ferrucci. One of ordinary skill would have been motivated to have such modification because the concept identification of Ferrucci benefits users in allowing a more natural language input.
Regarding claim 18, modified Piagentini teaches the method of claim 16 as described above. However, Piagentini does not explicitly teach of transaction messages comprising actions performed to resolve an issue. Ferrucci further teaches the following:
wherein the transaction messages comprise actions performed to resolve the particular issue. As Ferrucci teaches in paragraph [0135], and corresponding Fig. 7, a user may enter additional information to update recommendations. As Ferrucci teaches in paragraph [0090], “in response to answering questions or advice, and/or changing a visual component, the multimodal dialog engine 216 may update the session”, which is interpreted as at least suggesting actions taken to reach a resolution.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the transaction messages of Piagentini with the additional user input of Ferrucci. One of ordinary skill would have been motivated to have such modification because as Ferrucci teaches in paragraph [0006], such multiple panels and assistance methods benefit users in assisting with more complex issues.
Regarding claim 20, modified Piagentini teaches the method of claim 17 as described. However, Piagentini does not explicitly teach of a link to a subject matter expert. Ferrucci teaches the following:
the recommendation panel comprises a third section including a link to a user profile of a subject matter expert user, the subject matter expert user selected using the issue data. See Fig. 6, “Invite Agent”.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the interface of Piagentini with the third panel and invite agent control of Ferrucci. One of ordinary skill would have been motivated to have such modification because as Ferrucci teaches in paragraph [0006], such multiple panels and assistance methods benefit users in assisting with more complex issues.
Claim(s) 2 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Piagentini in view of Ferrucci as applied to claims 1 and 16, and further in view of Kim (US 2015/0271316).
Regarding claim 2, modified Piagentini teaches the method of claim 1 as described above. However, Piagentini does not explicitly teach of the first transaction message being a first message comprising user generated content. Ferrucci teaches the following:
the one or more transaction messages comprise: a first message comprising user generated content, the first message received at the intake portal graphical user interface. As Ferrucci teaches in paragraph [0056], and corresponding Fig. 1, the user inputs a scenario regarding an issue in box 130.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the interface of Piagentini with the user input scenarios of Ferrucci. One of ordinary skill would have been motivated to have such modification because as Ferrucci teaches in paragraph [0006], such multiple panels and assistance methods benefit users in assisting with more complex issues.
Furthermore, Piagentini in view of Ferrucci does not explicitly teach of a transaction message comprising agent generated content. In a similar field of endeavor, Kim teaches of recommending/generating content based upon user input (see abstract). Kim further teaches the following:
and a second message comprising agent generated content, the second message received at the issue-view graphical user interface. As Kim teaches in paragraphs [0023] and [0024], the system may generate content based upon a first message received from a first terminal and a second message received from a second terminal.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the recommendations based on input of Piagentini with the recommendations based on input from different users of Kim. One of ordinary skill would have been motivated to have such modification because utilizing the input of both the issue user and the expert would benefit users in providing further context to the AI system of Piagentini, thus improving output quality.
Regarding claim 19, modified Piagentini teaches the method of claim 16 as described above. However, Piagentini does not explicitly teach of the first transaction message being a first message comprising user generated content. Ferrucci teaches the following:
the transaction messages comprise: a first message comprising user generated content, the first message received at the intake portal. As Ferrucci teaches in paragraph [0056], and corresponding Fig. 1, the user inputs a scenario regarding an issue in box 130.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the interface of Piagentini with the user input scenarios of Ferrucci. One of ordinary skill would have been motivated to have such modification because as Ferrucci teaches in paragraph [0006], such multiple panels and assistance methods benefit users in assisting with more complex issues.
Furthermore, Piagentini in view of Ferrucci does not explicitly teach of a transaction message comprising agent generated content. In a similar field of endeavor, Kim teaches of recommending/generating content based upon user input (see abstract). Kim further teaches the following:
a second message comprising agent generated content, the second message received at the issue-view graphical user interface. As Kim teaches in paragraphs [0023] and [0024], the system may generate content based upon a first message received from a first terminal and a second message received from a second terminal.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the recommendations based on input of Piagentini with the recommendations based on input from different users of Kim. One of ordinary skill would have been motivated to have such modification because utilizing the input of both the issue user and the expert would benefit users in providing further context to the AI system of Piagentini, thus improving output quality.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Piagentini in view of Ferrucci as applied to claim 1, and further in view of Jaroker (US 2015/0067399).
Regarding claim 7, modified Piagentini teaches the method of claim 1 as described above. However, Piagentini does not explicitly teach of authenticating the user and agent. In a similar field of endeavor, Jaroker is directed to a method for providing remote support. Piagentini in view of Jaroker further teaches the following:
causing the portal intake graphical user interface to be displayed on the client device in response to a successful authentication of a user of the client device; and causing the issue-view graphical user interface to be displayed on a second client device in response to a successful authentication of an agent of the second client device. As Jaroker teaches in paragraph [0089], and corresponding Fig. 1, and intermediary system authenticates a user and expert through a login system. Upon the modification of Piagentini in view of Jaroker, the user and invited agent would first be required to pass authentication.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the user/agent interaction of Piagentini with the authentications of Jaroker. One of ordinary skill would have been motivated to have such modification because requiring any user to first be authenticated before allowing access to a system provided the well established benefit of increased security.
Claim(s) 8, 9, 11, and 13-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ferrucci in view of Piagentini.
As per claim 8, Ferrucci teaches the following:
a computer-implemented method for providing a recommendation panel for a graphical user interface of an issue tracking platform, (see abstract), the method comprising:
causing display of an intake portal graphical user interface of a frontend application of the issue tracking platform on a client device. As Ferrucci teaches in paragraph [0115], and corresponding Fig. 4, an interface 400 for initiating a support request is presented;
in response to a user selection of a query category of the intake portal graphical user interface, causing creation of a particular issue, the particular issue comprising first issue data that includes one or more transaction messages input by a user to the intake portal graphical user interface. As Ferrucci teaches in paragraph [0116], and corresponding Fig. 4, a “manage session” element allows a user to modify current configurations including starting a new session (selection of query category);
causing display of an issue-view graphical user interface including issue data of the particular issue. As Ferrucci shows in Fig. 4, a user may enter issue data in section 410;
in response to user input provided to the issue-view graphical user interface, (see Fig. 4), generating a knowledge base query, the generating the knowledge base query comprising:
identifying a set of issues using the issue data from the particular issue;
generating a first prompt including at least a portion of the first issue data and second issue data extracted from the set of issues. As Ferrucci teaches in paragraph [0132], and corresponding Fig. 6, in response to user input of an issue, a “Diagnosis” panel 604 is presented with a “Problem” identified (first prompt including a portion of different identified issues, i.e. user text input and diagram);
providing the first prompt to a generative output engine. As Ferrucci teaches in paragraph [0023], the system configures domain models to provide AI expertise, thus the issue data is submitted to an AI (prompt to generative output engine); and
receiving a first generative response from the generative output engine. See Fig. 6, 604, identified “Problem”;
submitting the knowledge base query to a knowledge base system. As Ferrucci teaches in paragraph [0023], the system configures domain models to provide AI expertise, thus the issue data is submitted to an AI; and
in response to receiving a response to the knowledge base query, causing display of the recommendation panel in the issue-view graphical user interface, (see Fig. 6, 604), the recommendation panel comprising:
a second section including a suggested action narrative, the suggested action narrative determined by:
generating a second prompt including at least a portion of the one or more transaction messages and content extracted from a content item identified in response to submitting the knowledge base query to the knowledge base system. As Ferrucci teaches in paragraph [0061], and corresponding Fig. 6, the portal may present suggestions based upon the identified problem;
providing the second prompt to the generative output engine. As Ferrucci teaches in paragraph [0023], the system configures domain models to provide AI expertise, thus the issue data is submitted to an AI. As all responses are generated via an AI engine, the Examiner interprets this as encompassing Applicant’s multiple prompts; and
generating the suggested action narrative using a second generative response received from the generative output engine in response to the prompt. See Fig. 6, “Causes & Remedies”.
While Ferrucci teaches in paragraph [0138], the user portal may include prompts to explore suggestions and/or linked relevant passages, Ferrucci does not explicitly teach of a first section including said links. In a similar field of endeavor, Piagentini teaches of a user interface for support services (see abstract). Piagentini further teaches the following:
a first section including a set of one or more selectable link objects received as part of a response to the knowledge base query. Piagentini shows in Fig. 5, and corresponding paragraph [0038], related articles to an issue are displayed within a pop out window (first section).
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the interface of Ferrucci with the related article panel of Piagentini. One of ordinary skill would have been motivated to have made such modification because as Piagentini teaches in paragraph [0018], such initial search and presentation of articles benefits users in possible finding a solution before a ticket for support is submitted.
Regarding claim 9, modified Ferrucci teaches the method of claim 8 as described above. Ferrucci further teaches the following:
wherein identifying the set of issues using the issue data from the particular issue comprises: performing a semantic analysis of at least one of an issue description associated with the particular issue and the one or more transaction messages; and performing a search of issues managed by the issue tracking system using a result of the semantic analysis. As Ferrucci teaches in paragraph [0030], the engine includes a semantic parser and a multimodal dialog engine to parse received natural language input.
Regarding claim 11, modified Ferrucci teaches the method of claim 8 as described above. Ferrucci further teaches the following:
wherein the recommendation panel comprises a third section including a link to a user profile of a subject matter expert user, the subject matter expert user selected using the issue data. As Ferrucci teaches in paragraph [0043], and corresponding Fig. 8, the portal includes an “Invite Agent” control. Further see paragraph [0073] where the agent is a “knowledge expert”.
Regarding claim 13, modified Ferrucci teaches the method of claim 8 as described above. Ferrucci further teaches the following:
wherein the second issue data comprises one or more actions, each action of the one or more actions associated with a resolution for a respective issue of the set of issues. As Ferrucci teaches in paragraph [0135], and corresponding Fig. 7, a user may enter additional information to update recommendations. As Ferrucci teaches in paragraph [0090], “in response to answering questions or advice, and/or changing a visual component, the multimodal dialog engine 216 may update the session”, which is interpreted as at least suggesting actions taken to reach a resolution.
Regarding claim 14, modified Ferrucci teaches the method of claim 8 as described above. Ferrucci further teaches the following:
in response to a user modification of the issue data: generating an updated prompt comprising the user modification to the issue data; providing the updated prompt to the generative output engine; and causing the suggested action narrative to be updated using an updated generated response received from the generative output engine in response to the updated prompt. As Ferrucci teaches in paragraph [0135], and corresponding Fig. 7, updated information may be entered to further define an issue. Ferrucci then teaches in paragraph [0138], and corresponding Fig. 8, the session model is updated in response to the user input and the reasoning engine identifies new suggestions.
Regarding claim 15, modified Ferrucci teaches the method of claim 8 as described above. Ferrucci further teaches the following:
wherein the one or more transaction messages comprise a user description of the issue and one or more actions that have been taken to resolve the issue. See Fig. 5, 504 for user description of issue and as Ferrucci teaches in paragraph [0135], and corresponding Fig. 7, updated information may be entered to further define an issue (one or more action taken to resolve an issue). Ferrucci then teaches in paragraph [0138], and corresponding Fig. 8, the session model is updated in response to the user input and the reasoning engine identifies new suggestions.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ferrucci in view of Piagentini as applied to claim 8, and further in view of Kim (US 2015/0271316).
Regarding claim 10, modified Piagentini teaches the method of claim 8 as described above. However, Piagentini in view of Ferrucci does not explicitly teach of a transaction message comprising agent generated content. In a similar field of endeavor, Kim teaches of recommending/generating content based upon user input (see abstract). Kim further teaches the following:
wherein the issue data comprises one or more transaction messages input by an agent to the issue-view graphical user interface. As Kim teaches in paragraphs [0023] and [0024], the system may generate content based upon a first message received from a first terminal and a second message received from a second terminal.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the recommendations based on input of Piagentini with the recommendations based on input from different users of Kim. One of ordinary skill would have been motivated to have such modification because utilizing the input of both the issue user and the expert would benefit users in providing further context to the AI system of Piagentini, thus improving output quality.
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ferrucci in view of Piagentini as applied to claims 8 and 11, and further in view of Anderson et al. (US 2015/0278748), hereinafter Anderson.
Regarding claim 12, modified Ferrucci teaches the method of claim 11 as described above. While Ferrucci teaches in paragraph [0043], an agent may be invited to join a session, Ferrucci does not explicitly teach of an expert selected based on information received. In a similar field of endeavor, Anderson teaches of a support method of handling trouble tickets. Anderson further teaches the following:
wherein the subject matter expert user is selected based on user information received as part of the response received from the knowledge base system. As Anderson teaches in paragraph [0032], the system matches the subject matter of an issue to an expertise of an agent.
It would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s claimed invention to have modified the invite agent of Ferrucci with the expert matching of Anderson. One of ordinary skill would have been motivated to have made such modification because as Anderson teaches in paragraph [0020], routing issues to agents with appropriate expertise/knowledge/ability needed was a well known technique in the art as being beneficial to users.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
-Cogger et al. (US 6,032,184), see abstract.
-Heere et al. (US 2021/0089860), see Fig. 5.
-Hill et al. (US 2006/0080107), management of conversations between user, human agent, and system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GREGORY A DISTEFANO whose telephone number is (571)270-1644. The examiner can normally be reached Monday - Friday: 9 am - 5 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William Bashore can be reached at 5712424088. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/GREGORY A. DISTEFANO/
Examiner
Art Unit 2174
/WILLIAM L BASHORE/ Supervisory Patent Examiner, Art Unit 2174
Prosecution Insights