CTNF 18/480,963 CTNF 100815 DETAILED ACTION This Office Action is responsive to Request for Continued Examination filed on December 12 th , 2025. Claims 1, 7, 11, 15 and 17-18 are amended, claims 4 and 14 are cancelled, claims 21 and 22 are added. Claims 1-3, 5-13 and 14-22 are pending and have been examined. Any previous objections/rejections not addressed in this action have been withdrawn by the Examiner. Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia 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 Amendments and Arguments Rejections under 35 U.S.C. 103: On page 12 of Remarks, Applicant argues, "Lemaitre discloses that the bot search interface presents lists of available bots to the user following a search request (see Lemaitre, paragraphs [0120], [0121], and [0129] to [0133]) however the available bots are merely displayed and organised by keyword or category. The selection of the bot is entirely manual and the user must interpret the search results and explicitly select a bot by pressing a ‘start’ button or similar UI element (see Lemaitre, paragraph [0133]). There is no suggestion or recommendation generated or provided to the user . This is in contrast to Applicant's claimed subject matter in which an interactive suggestion or recommendation is automatically generated , and is context-aware , reflecting the content of the interaction ." Examiner respectfully disagrees. Lemaitre teaches at paragraph [0132] that the user interface displays category-based chatbots, including a “recommendation area 123”. This list of options presented to the user is created by a server, thereby teaching the broadest reasonable interpretation of an automatically generated, context-aware suggestion provided to a user. On page 13 of Remarks, Applicant argues, "While Lewis discloses storing and presenting past dialog contexts, such storage is explicitly intended to enable smooth resumption of dialogs within the same automated assistant and is organized according to conversation topics or other semantic categories. Lewis is silent regarding transfer of information between distinct automated assistants or chatbots, and the 'selectable' nature of prior contexts is limited to user-initiated resumption within the same assistant. That is, while the user may view or select a prior dialog context for resumption, such selection does not equate to transferring the information to a different automated assistant , nor does the system disclose making the information externally selectable for use by other chat bots ." Applicant’s argument is persuasive; accordingly, the rejections relying on the teachings of Lewis are withdrawn. Starting on page 13 of Remarks, Applicant argues, "The Examiner has stated that D'Agostino, Liang, Lemaitre, and Lewis are considered analogous because they each are concerned with managing human-computer conversation. The fundamental operations and purposes of these references, however, differ significantly. Lemaitre is limited to manual selection of static bots based on keywords or categories, Liang does not disclose selective transfer of interaction content, and Lewis is directed to resuming dialog contexts within the same automated assistant. None of these references teach or suggest automatically generating context-aware recommendations for transferring a natural language interaction from one conversational interface to a distinct, domain-specific interface, nor do they disclose presenting selectable elements associated with relevant portions of contextual information for such transfer ." Examiner respectfully disagrees. D’Agostino and Lemaitre are each classified with interface arrangements, each of Lemaitre and Liang are classified with handling of natural language data, and each of the cited references broadly describes technology and applications that fall within the art of human-machine dialogue. Since each reference is known in the art, in combination, they teach a system for human-machine dialogue that behaves in a context-aware manner to direct a user to a domain-specific interface. Each element is used as taught to achieve an outcome that would be predictable to a person having skill in the art. With regard to rejections relying on Lewis, Applicant’s argument is moot, as those rejections are withdrawn. In accordance with the above arguments, the rejections based on 35 U.S.C. 103 under D’Agostino, Lemaitre and Liang are maintained. Further details are provided below. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. Claims 1-2, 10-12 and 18-19 are rejected under 35 U.S.C. 103 as being obvious over U.S. Patent Application Publication 2020/0099633 to D'Agostino et al. (hereinafter, "D'Agostino") in view of U.S. Patent Application Publication 2021/0144107 to Liang et al. (hereinafter, "Liang"), and further in view of U.S. Patent Application Publication 2024/0012543 to Lemaitre (hereinafter, "Lemaitre"). The applied reference D’Agostino has a common applicant with the instant application. Based upon the earlier publication date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(1). Regarding claims 1, 11 and 18, D’Agostino teaches a system, method and computer-readable medium comprising: at least one memory storing instructions; a network interface; and at least one hardware processor interoperably coupled with the network interface and the at least one memory, wherein execution of the instructions by the at least one hardware processor causes performance of operations (paragraph [0004], “The present disclosure involves systems, software, and computer implemented methods for managing a conversation with a plurality of chat bots. One example system includes a communications module, at least one memory storing instructions and a plurality of chat bots, and a repository of contextual content, the contextual content for use in formulating at least one response generated in response to a conversational contextual input, and at least one hardware processor interoperably coupled with the at least one memory and the communications module .”). D'Agostino further teaches interacting, via the first conversational interface, with a first user through a natural language search interaction (paragraph [0051], "A user 201 uses a client device 202 to provide the request. In particular, a user 201 interacts with a conversational interface (or client device at which a user 201 is interacting with the conversational interface) , an NLP engine 208 (including an intent deciphering module 210 and a chat bot decision engine 212) a chat bot library 220, a contextual repository 224, a user profile 222, and an NLG engine 226."). D’Agostino further teaches identifying, by the first conversational interface, at least one response associated with one of the at least one endpoints associated with the first entity (paragraph [0026], "System 100 includes functionality and structure associated with receiving inputs from a client device 164 (associated with a user), analyzing the received input at the conversational analysis system 102 to identify a context of the input and based on the context of the input, determine a chat bot from the plurality of chat bots to route the received input. The determined chat bot can then provide a response on the request to the client device 164 in response to providing the input to the conversational analysis system 102 ."). D'Agostino further teaches receiving [information] at a first conversational interface, the [information] identifying at least one endpoint associated with a first entity, wherein the first entity is separate from the first conversational interface, wherein the first entity is associated with a domain-specific conversational interface, and wherein the at least one endpoint associated with the first entity represents a connection to the domain-specific conversational interface (paragraph [0036], "In some instances, the chat bot decisions engine 118 can determine a particular chat bot from the chat bot library 142, which includes a plurality of chat bots, to route the received input to a particular chat bot for receiving a response. Each chat bot in the chat bot library 142 is stored in or associated with a chat bot instance 144 . For example, the chat bot library 142 can have chat bot instance 144-1 through chat bot instance 144-N. Each chat bot may be used by the conversational analysis system 102 for a particular subject, product, or type of request . For example, chat bot instance 144-1 is used for answering requests regarding the user profile, chat bot instance 144-2 is used for answering requests regarding financial information, chat bot instance 144-3 is used for answering requests regarding authentication data of the user, and chat bot instance 144-4 is used or answering requests regarding stock information. Other particular subjects are available for a chat bot instance that include, but are not limited to, social media management, emailing, and mortgage requests. In some instances, different chat bot instances 144 may be associated with different departments of a retailer, while in other instances, different chat bot instances 144 may be associated with different product lines, such as personal banking, investments, account management, and others ."). Although D’Agostino teaches receiving some information, it does not explicitly teach receiving “a registration”; however, Liang teaches receiving a registration at a first conversational interface, the registration identifying at least one endpoint associated with a first entity (paragraph [0018], “ Chatbot owners may register one or more chatbots with an orchestrated chat service . During the registration process, the chatbot owners can provide descriptions of the chatbot being registered, along with one or more intents and entities associated with the chatbot to the chat service's natural language classifier. An ‘intent’ may refer to a representation of the purpose of a user's input. Chatbot owners may define an intent for each type of user request the registered chatbot intends to support. An ‘entity’ may refer to a term or object that is relevant to an intent and provides a specific context for an intent.”). D'Agostino and Liang are considered analogous because they are each concerned with managing human-computer conversation. 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 replaced the chatbot library of D’Agostino with the registration process of Liang for the purpose of aggregating chatbots and improving user experience, given that the substitution of one known element for another yields predictable results. Neither D’Agostino nor Liang teach “providing for presentation, by the first conversational interface, the at least one identified response and an interactive suggestion or recommendation to initiate a transfer of the natural language search interaction from the first conversational interface to a domain-specific conversational interface of the first entity,” or “in response to identifying a user interaction from the first user indicating an intent to transfer, transferring the natural language search interaction from the first conversational interface to domain-specific conversational interface associated with the first entity,” and thus, Lemaitre is introduced. Lemaitre teaches providing for providing for presentation, by the first conversational interface, the at least one identified response and an automatically generated interactive suggestion or recommendation to initiate a transfer of the natural language search interaction from the first conversational interface to the domain-specific conversational interface of the first entity, the interactive suggestion or recommendation being presented as one or more selectable user interface elements associated with at least a portion of a set of contextual information from the natural language search interaction to be shared with the domain-specific conversational interface (paragraph [0132], "An embodiment of a search by category(ies) is now presented in relation to FIGS. 12 and 13. From its messaging client run on its mobile terminal 1, the search interface opens a page (user interface window referenced 121 in FIG. 12) that provides an example of a category-based organisation for performing the bot search. A recommendation area 123 (‘Recommended’) allows sponsored bots to be reached directly . The user can refine their search by selecting a category among those (125a, 125b, etc.) listed in the area referenced 124, or by entering a keyword in the search area referenced 122 and comprising an invitation to enter a keyword (‘Find chatbot’) .") and in response to identifying a user interaction from the first user indicating an intent to transfer, initiating a context-aware transfer of the natural language search interaction from the first conversational interface to the domain-specific conversational interface associated with the first entity (paragraph [0130], "Another explanation is that the display of the communication channels associated with the listed chatbots requires an action by the user via the user interface (for example, pressing a ‘+’ button displayed near an identifier and/or a logo of a given chatbot enables the associated communication channel to be displayed, or even a plurality of associated channels if the chatbot can be accessed via the mediation server 7). In the case where several communication channels are displayed, if the user chooses a channel that is not the one associated with the currently used messaging client, then the mobile terminal 1 switches to another messaging client associated with the chosen communication channel, thus allowing the opening of a conversation with the given chatbot ."). The combination of D’Agostino and Lemaitre does not explicitly teach “the initiating comprising generating a transfer payload comprising a selected set of contextual information associated with the natural language search interaction,” however, Liang teaches the initiating comprising generating a transfer payload comprising a selected set of contextual information associated with the natural language search interaction (paragraph [0112], "In step 819, the format exchanger 221 of the orchestrator services 217 transforms the user input, intent, entities and session history 229 from a native format maintained by the chat services 225 and/or data repository 227 into an API format acceptable for transmission to the selected chatbot 241 ."). D’Agostino, Liang and Lemaitre are considered analogous because they are each concerned with managing human-computer conversation. 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 D’Agostino and Liang with the teachings of Lemaitre for the purpose of improving user experience. Given that all the claimed elements were known in the prior art, one skilled in the art could have combined the elements by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Regarding claims 2, 12 and 19, D’Agostino further teaches generating a search configuration profile associated with the first entity, the search configuration profile associated with at least one search result or response and the at least one endpoint associated with the first entity (paragraph [0058], "In other implementations, each time data passes from the conversational manager 206 to the domain intelligence 218 and from the domain intelligence 218 to the conversational manager 206, the conversational manager 206 stores data in the domain intelligence 218 indication for tracking the conversation. The data stored in the domain intelligence is a generated historical context for the conversational manager 206 to track an ongoing conversation between the client device and the conversational manager ," and paragraph [0069], "The conversation manager 310 routes the request to one or more places in the domain intelligence 314. For example, the domain intelligence 314 includes a team of individuals, a banking inquiry, a Domain 2 BOT, or a Domain 3 BOT . The conversation manager 310 also stores an indication of the received request as well as the routed chat agent in conversation data 312. The conversation data 312 includes context (interactions), interaction details, and conversation session info ."). Neither D’Agostino nor Liang teach “associating at least one of a disclosure, a set of terms and conditions, or a privacy statement with the first entity,” however, Lemaitre teaches associating at least one of a disclosure, a set of terms and conditions, or a privacy statement with the first entity (paragraph [0042], "According to a particular feature, prior to receiving the request to launch the lookup operation or receiving the new request to launch the lookup operation, the bot search interface performs a step of displaying, via the user interface, a link to terms and conditions applying to the plurality of bots , said link being able to be activated via the user interface."). D’Agostino, Liang and Lemaitre are considered analogous because they are each concerned with managing human-computer conversation. 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 D’Agostino and Liang with the teachings of Lemaitre for the purpose of improving user experience. Given that all the claimed elements were known in the prior art, one skilled in the art could have combined the elements by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Regarding claim 10, D’Agostino further teaches receiving the registration at the first conversational interface comprises receiving registrations for a plurality of endpoints, the plurality of endpoints associated with the first entity and at least one other entity, wherein each of the plurality of endpoints are associated with entities separate from the first conversational interface, and wherein each of the entities is associated with at least one corresponding domain-specific conversational interface, and wherein each of the plurality of endpoints are operable to connect with a corresponding domain-specific conversational interface (paragraph [0036], "In some instances, the chat bot decisions engine 118 can determine a particular chat bot from the chat bot library 142, which includes a plurality of chat bots, to route the received input to a particular chat bot for receiving a response. Each chat bot in the chat bot library 142 is stored in or associated with a chat bot instance 144 . For example, the chat bot library 142 can have chat bot instance 144-1 through chat bot instance 144-N. Each chat bot may be used by the conversational analysis system 102 for a particular subject, product, or type of request . For example, chat bot instance 144-1 is used for answering requests regarding the user profile, chat bot instance 144-2 is used for answering requests regarding financial information, chat bot instance 144-3 is used for answering requests regarding authentication data of the user, and chat bot instance 144-4 is used or answering requests regarding stock information. Other particular subjects are available for a chat bot instance that include, but are not limited to, social media management, emailing, and mortgage requests. In some instances, different chat bot instances 144 may be associated with different departments of a retailer, while in other instances, different chat bot instances 144 may be associated with different product lines, such as personal banking, investments, account management, and others ."). Allowable Subject Matter 12-151-08 AIA 07-43 12-51-08 Claim s 3, 5-9, 13, 15-17 and 20-22 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. While the combination of D’Agostino, Lemaitre and Liang combine to describe a system for context-aware transfer of chatbot dialogue, none of the references, alone or in combination, describe a system wherein the user is prompted to select a variable portion of contextual information. Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. U.S. Patent Application Publication 2023/0353512 to Gollareddy et al. U.S. Patent Application Publication 2021/0165967 to Shek et al. U.S. Patent Application Publication 2022/0407961 to Willshire et al. U.S. Patent Application Publication 2022/0150190 to Liao et al. U.S. Patent Application Publication 2024/0203413 to Sharifi et al. U.S. Patent 11,223,580 to Parr et al. U.S. Patent 11,922,938 to Khan et al. U.S. Patent 12,348,915 to van Scheltinga et al. U.S. Patent 11,803,395 to Kushner et al. WIPO Publication WO 2019/209511 to Srivastava et al. Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAN T SMITH whose telephone number is (571)272-6643. The examiner can normally be reached Monday - Friday 8:00am - 5:00pm. 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, PIERRE-LOUIS DESIR can be reached at (571) 272-7799. 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. /SEAN THOMAS SMITH/Examiner, Art Unit 2659 /PIERRE LOUIS DESIR/Supervisory Patent Examiner, Art Unit 2659 Application/Control Number: 18/480,963 Page 2 Art Unit: 2659 Application/Control Number: 18/480,963 Page 3 Art Unit: 2659 Application/Control Number: 18/480,963 Page 4 Art Unit: 2659 Application/Control Number: 18/480,963 Page 5 Art Unit: 2659 Application/Control Number: 18/480,963 Page 6 Art Unit: 2659 Application/Control Number: 18/480,963 Page 7 Art Unit: 2659 Application/Control Number: 18/480,963 Page 8 Art Unit: 2659 Application/Control Number: 18/480,963 Page 9 Art Unit: 2659 Application/Control Number: 18/480,963 Page 10 Art Unit: 2659 Application/Control Number: 18/480,963 Page 11 Art Unit: 2659 Application/Control Number: 18/480,963 Page 12 Art Unit: 2659
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