2Notice 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 .
DETAILED ACTION
Response to Amendment
1. Applicant's amendments, filed December 31, 2025 are respectfully acknowledged and have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed December 31, 2025 and therefore rejections newly made in the instant office action have been necessitated by amendment.
Claims 1, 8, and 15 are amended.
Claims 1-20 are pending.
Claim Objections
Claim 1 is objected to because of the following informalities: typographical error. “a system architecture comprising, a server, an…” in line 2 should be “a system architecture comprising a server, an…” Appropriate correction is required.
Further depending claims not mentioned inherit the deficiencies of their respective base claims and are rejected [objected to] under similar rationale.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3, 5-10, 12-17, and 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Sekar et al. (U.S. Patent Application Publication 20210201238 A1, hereinafter “Sekar”) in view of Vale et al. (U.S. Patent Application 20220342891 A1, hereinafter “Vale”).
Regarding Claim 1 (Currently Amended), Sekar teaches a system for interacting with a chat bot (par 0068 chat server 240 may operate as an execution engine or environment for the chatbots 260), comprising:
a system architecture comprising, a server (par 0039 Fig 2 the system architecture comprises a number of servers including reporting server 248, routing server 218, etc.), an interface module (par 0067 Fig 3 chat server 240 may include a customer interface module 265 for generating particular UIs at the customer device 205), a natural language processing engine (par 0076 Fig 2 text analytics module 270 is configured to analyze and understand natural language, using at least one model 252 of analytics module 250 for natural language processing), a conversation engine (par 0051 Fig 2 chat server/conversation engine 240 operates to dispatch the actual chat conversation to the client/user interface), a knowledge base (at least par 0050 Fig 2 knowledge system 238 may be a computer system capable of receiving questions or queries and providing answers in response. The knowledge system 238 may include an artificially intelligent computer system capable of answering questions posed in natural language by retrieving…), and a database (at least par 0050 Fig 2 knowledge system 238 retrieves information from information sources such as encyclopedias, dictionaries, newswire articles, literary works, or other documents submitted to the knowledge system 238 into a reference materials database);
the server, comprising a processor and memory (par 0064 Figs 1,2 each server includes one or more processors 105 executing computer program instructions stored in memory 110), and configured to:
interact, by the interface module, with a user using text or voice-based natural language by receiving natural language input from the user (par 0067 Fig 3 chat server 240 may be in electronic communication with a client system 205 operated by the customer over a data communications network 210; chat server 240 may include a customer interface module 265 and an agent interface module 266 for generating a UI at the client system/customer device 205; paras 0068-0069 customer input is captured by the chat server 240 from the client system UI using one or more chatbots par 0071 responding to input from the user [par 0082 Fig 5 chat interface 284 is a text display area 286 dedicated to the display of received and sent text messages, and a text input area 288 facilitates the customer's input of text messages]; par 0089 Fig 7 customer automation system 300 receives input at an initial step or operation 355. Such input may come from several sources. For example, a primary source of input may be the customer/user, where such input is received via the user interface 305 on the customer/user client device (e.g., customer device 205) as text (e.g., unstructured, natural language input));
perform, by the natural language processing engine (par 0090 Fig 7 customer automation system 300 parses the natural language of the input using the natural language processing (NLP) module 310 [par 0088], similarly par 0076 Fig 2 text analytics module 270 is configured to analyze and understand natural language), natural language processing to decode the user input (par 0090 Fig 7 customer automation system 300 NLP module decodes the user input language and determines therefrom the user’s intent using system 300’s intent inference module 315; determining/identifying one or more keywords from the customer input which might have corresponding potential intents) and provide the decoded user input to the knowledge base (par 0090 Fig 7 the intent may be automatically inferred from the user input text using artificial intelligence or machine learning techniques comprising searching a data/knowledge base of potential intents corresponding to keywords, the data/knowledge base having been generated from a collection of historical interaction recordings; par 0091 Fig 7 a script storage module 320 [a knowledge base par 0091 produced from mining data, actions, and dialogue from previous customer interactions] is searched to provide the “definition”/ script of the determined intent, to include commands, operations [tasks, actions], text, and data fields [functions of the user interface] that will be required to complete an interaction in order to resolve the issue specified by the user's intent),
receive, by the natural language processing engine, responses from the knowledge base (par 0091 Fig 7 the customer's intent is determined/received from the knowledge base; par 0091 Fig 7 step 365 customer automation system 300 provides/ loads a script [natural language response to the chat server/ conversation engine 240] associated with the given intent);
transform, by the natural language processing engine, the responses from the knowledge base to natural language responses (par 0091 Fig 7 step 365 customer automation system 300 provides/loads a script [natural language response to the chat server/ conversation engine 240] associated with the given intent); and
display, by the conversation engine, the natural language responses (par 0051 Fig 2 chat server/conversation engine 240 operates to dispatch the actual chat conversation to the client/user interface).
However, Sekar appears not to expressly teach
wherein the natural language processing engine interprets the user input according to one or more meta-classes.
Vale teaches
wherein the natural language processing engine interprets the user input (par 0056 Fig 5 user-generated request, par 0062 in an application user interface) according to one or more meta-classes (par 0069 Fig 6C the user query is analyzed as to intent and context with reference to e.g. the domain ontology at multiple levels—class “Beam”, meta-classes “Material” and “Application”, etc.).
Sekar and Vale are analogous art as they each pertain to systems for responding to user information requests. It would have been obvious to a person of ordinary skill in the art to modify the system of Sekar with the inclusion of the user input interpretation according to one or more meta-classes of Vale. The motivation would have been in order to provide matching of the problem context with the generative context of knowledge to assess the degree of similarity between the two, which then provides the basis for ranking the suitability of different resulting outputs for the problem context (Vale par 0082).
Regarding Claim 2 (Original), Sekar as modified teaches the system of Claim 1, wherein
the database stores interaction history and analytics Sekar (par 0091 Fig 7 a script storage module 320 [a knowledge base par 0091 produced from a database of mining, actions, and dialogue from previous customer interactions] is searched to provide the “definition”/script of the determined intent, to include commands, operations [tasks, actions], text, and data fields [functions of the user interface] that will be required to complete an interaction in order to resolve the issue specified by the user's intent).
Regarding Claim 3 (Original), Sekar as modified teaches the system of Claim 1, wherein
the knowledge base comprises intent-driven markers on layouts which comprises actions and tasks that are possible on the layouts (Sekar par 0093 Fig 7 data for some or most of the data fields [for UI layouts] within the script may be automatically loaded with relevant data [corresponding to the customer's intent] retrieved from stored customer data; for ambiguous data fields or missing information within a [UI layout], the script processing module 325 may include prompts [intent-driven markers which comprise actions and tasks that are possible on the layouts] and allows the customer to manually input the needed information).
Regarding Claim 5 (Original), Sekar as modified teaches the system of Claim 1, wherein
the knowledge base comprises functional workflows comprising a logical sequence of actions (Sekar par 0091 Fig 7 a script storage module 320 [a knowledge base par 0091 produced from mining data, actions, and dialogue from previous customer interactions] is searched to provide the “definition”/script of the determined intent, to include commands, operations [tasks, actions], text, and data fields [functions of the user interface] that will be required to complete an interaction in order to resolve the issue specified by the user's intent).
Regarding Claim 6 (Original), Sekar as modified teaches the system of Claim 5, wherein
the functional workflows comprise operations and tasks that are coupled with a business objective (Sekar par 0037 Fig 2 the system operations [tasks, actions] are coupled to performance of the functions of sales and service relative to the products and services available through the enterprise; e.g. par 0069 Fig 3 a chatbot [workflow] may be specialized to engage in a user opening a new account with the business); while another may be specialized for technical support for a product or service provided by the business)).
Regarding Claim 7 (Original), Sekar as modified teaches the system of Claim 1, wherein
the conversation engine comprises a chatbot (Sekar par 0068 chat server 240 may operate as an execution engine or environment for the chatbot 260).
Claim 8 presents the limitations of Claim 1 in a different claim category, and therefore Claim 8 is rejected with a rationale similar to Claim 1, mutatis mutandis.
Claim 9 presents the limitations of Claim 2 in a different claim category, and therefore Claim 9 is rejected with a rationale similar to Claim 2, mutatis mutandis.
Claim 10 presents the limitations of Claim 3 in a different claim category, and therefore Claim 10 is rejected with a rationale similar to Claim 3, mutatis mutandis.
Claim 12 presents the limitations of Claim 5 in a different claim category, and therefore Claim 12 is rejected with a rationale similar to Claim 5, mutatis mutandis.
Claim 13 presents the limitations of Claim 6 in a different claim category, and therefore Claim 13 is rejected with a rationale similar to Claim 6, mutatis mutandis.
Claim 14 presents the limitations of Claim 7 in a different claim category, and therefore Claim 14 is rejected with a rationale similar to Claim 7, mutatis mutandis.
Claim 15 presents the limitations of Claim 1 in a different claim category, and therefore Claim 15 is rejected with a rationale similar to Claim 1, mutatis mutandis.
Claim 16 presents the limitations of Claim 2 in a different claim category, and therefore Claim 16 is rejected with a rationale similar to Claim 2, mutatis mutandis.
Claim 17 presents the limitations of Claim 3 in a different claim category, and therefore Claim 17 is rejected with a rationale similar to Claim 3, mutatis mutandis.
Claim 19 presents the limitations of Claim 5 in a different claim category, and therefore Claim 19 is rejected with a rationale similar to Claim 5, mutatis mutandis.
Claim 20 presents the limitations of Claim 7 in a different claim category, and therefore Claim 20 is rejected with a rationale similar to Claim 7, mutatis mutandis.
Claims 4, 11, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Sekar et al. (U.S. Patent Application Publication 20210201238 A1, hereinafter “Sekar”) in view of Lv et al. (U.S. Patent Application Publication 20230196239 A1, hereinafter “Lv”).
Regarding Claim 4 (Original), Sekar as modified teaches the system of Claim 3. However, Sekar as modified appears not to expressly teach wherein
the intent-driven markers comprise graphic elements on cards based on an intent of the user.
Lv teaches a workflow planning system wherein
the intent-driven markers comprise graphic elements on cards based on an intent of the user (par 0089 Fig 5 user interface 503 includes a section 506 that includes a number of cards 509; the cards 509 may have intent-driven markers thereon comprising a graphic element of a geometric shape with “get” applied to it; the user can select “get” to install or configure a workflow according to a workflow definition).
Sekar Vale and Lv are analogous art as they each pertain to systems for responding to user information requests. It would have been obvious to a person of ordinary skill in the art to modify the system of Sekar/Vale with the inclusion of card graphic markers of Lv. The motivation would have been in order to provide more intuitive and efficient user sequences of actions in the UI.
Claim 11 presents the limitations of Claim 4 in a different claim category, and therefore Claim 11 is rejected with a rationale similar to Claim 4, mutatis mutandis.
Claim 18 presents the limitations of Claim 4 in a different claim category, and therefore Claim 18 is rejected with a rationale similar to Claim 4, mutatis mutandis.
Response to Arguments
Applicant's arguments filed December 31, 2025 have been fully considered but they are not persuasive. Applicant’s arguments with respect to independent claims 1, 8, and 15 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
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/MARK EDWARDS/Primary Examiner, Art Unit 2624