DETAILED ACTION
This office action is responsive to claims 1 – 17 filed in this application Sohn et al., U.S. Patent Application No. 18/970,861 (Filed December 5, 2024) claiming priority to KR10-2024-0175240 (11/29/2024) and KR10-2023-0174949 (12/5/2023) (“Sohn”).
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement(s) (IDS) filed on 12/5/2024, 2/10/2026, 6/5/2026, 9/10/2026 are in compliance with the provisions of 37 CFR 1.97, 1.98 and MPEP § 609. The references listed therein have been considered, and placed in the application file.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 - 17 are rejected under 35 U.S.C. 101 because the claimed inventions are directed to non-statutory subject matter. The claimed inventions do not fall within a statutory category of invention because the claimed invention is directed to a “Mental Processes” abstract idea without significantly more.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a “Mental Processes” abstract idea without significantly more. The claim recites determining a response dialogue act responding to the user dialogue input based on a dialogue graph and providing the response dialogue act; determining a context of task-oriented dialogues by analyzing the task-oriented dialogues including the user dialogue input and the response dialogue act; determining a type of a task requested by a user based on the context of the task-oriented dialogues; and performing the task of which type is determined, which covers performance of the limitations that can be performed in the mind or by pen and paper, but for the recitation of generic computer components.
The claims recite additional limitations of generic data transmission and generic computing components. MPEP 2106.05(g) & 2106.05(d). That is, other than reciting the generic transmission and generic computing components nothing in the claim elements precludes the determining and performing steps from being performed in the mind of a developer. MPEP 2106.05(d). As drafted, the claimed process, under its broadest reasonable interpretation, covers the performance of the limitation in the mind but for the recitation of generic computer components, which falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application because the claims only recite generic computing components and routine data transmission. See MPEP 2106.05(d). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the courts have identified mere data gathering, displaying/outputting, transmitting, and storing, are well-understood, routine and conventional activity See MPEP 2106.05(d)(II) & (f).
Claims 2, and 4 – 17 contain the same abstract idea as claim 1 and do not contain any additional limitations that would integrate the judicial exception into a practical application or additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 3 includes the abstract idea of the parent claims and also contains the additional element of utilizing a model to perform the task which is directed to implementing an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea, and which fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception, see MPEP 2106.05(f)(2).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1, 15, and 16 are rejected on the ground of obviousness-type double patenting as being unpatentable over claim 13 of U.S. Patent Application No. 18/970,787 and claim 6 of 18/970,842. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the Applications anticipate the claims of the instant application.
Dependent claims 2 – 14 and 17 are rejected on the ground of obviousness double patenting as being unpatentable over claim 13 of, respectively, U.S. Patent Application No. 18/970,787 and claim 6 of 18/970,842. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims are obvious in view of the Applications and the art used infra to teach the dependent claims and associated motivation.
35 USC § 112(f)
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “electronic device configured to”, in claims 16 and 17.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections 35 U.S.C. § 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 of this title, 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.
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 – 4 and 7 – 17 are rejected under 35 U.S.C. 103 as being unpatentable over Wen et al., United States Patent No. 11,430,446 (Patented August 30, 2022, filed August 12, 2021) (“Wen”) in view of Shen et al., HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face, Arxiv.org (December 3, 2023) retrieved from https://arxiv.org/pdf/2303.17580 on 9/28/2026 (“Shen”).
Claims 1, 15, and 16
With respect to claims 1, 15, and 16, Wen teaches the invention as claimed a computerized method comprising: receiving a user dialogue input; determining a response dialogue act responding to the user dialogue input based on a dialogue graph and providing the response dialogue act; determining a context of task-oriented dialogues by analyzing the task-oriented dialogues including the user dialogue input and the response dialogue act; … and performing the task of which type is determined. {A user request is received and analyzed to identify keywords, determine a task, place the keywords in slots of the task and dialogue graph is used to receive the task request information, determiner user intent, use the graph to determine a dialogue act response to the user request and intent, and to perform a task in response to the selected dialogue act . Wen at Abstract; id. at col. 44 ll. 30 – 50 (receive user request); id. at col. 5 ll. 1 – 23, col. 7 ll. 37 – 51, col. 7 ll. 61 – 66, col. 8 ll. 51-56, col. 46 ln. 66 - col. 47 ln. 36 (dialogue graph takes user input, determines a task, intent, and context, and returns a dialogue act response); id. at col. 24 ll. 49 – 50, col. 35 ll. 16 – 21, & col. 45 ll. 22 – 34 (task performance in response to dialogue act).}
However, Wen doesn’t explicitly teach the limitation:
determining a type of a task requested by a user based on the context of the task-oriented dialogues; {Shen does teach this limitation. Shen teaches that determining user task request, intent, and context, as taught in Wen, may include where the system may determine, based on the dialogue act, the context, the intent, and the keywords of the request, the type of task that needs to be performed such as determining which AI model would be most suited to performing the requested task and the system may dispatch the task to the model and report the results of the model accomplishing the task. Shen at Abstract; id. at pg. 2 & fig. 1; id. at pg. 6 (3.2 The best Model to perform task is selected).
Wen and Shen are analogous art because they are from the “same field of endeavor” and are both from the same “problem-solving area.” Specifically, they are both from the field of software development, and both are trying to solve the problem of how to create customized program code.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine determining user task request, intent, and context, as taught in Wen, with selecting models based on task type, as taught in Shen. Shen teaches that model descriptions can be used to select the best suited model for a particular task. Shen at Abstract; id. at pg. 2. Therefore, one having ordinary skill in the art would have been motivated to combine determining user task request, intent, and context, as taught in Wen, with selecting models based on task type, as taught in Shen, for the purpose of using a method to select optimum models to perform a task with a system that requires performing a task.}
Claim 2
With respect to claim 2, Wen and Shen teach the invention as claimed including:
wherein the determining of the context of the task-oriented dialogues comprises extracting a plurality of keywords from the task-oriented dialogues, and analyzing one or more of a correlation between a plurality of dialogue acts included in the task-oriented dialogues, an intent of the task-oriented dialogues, or a purpose of the task-oriented dialogues based on the plurality of keywords. {A user request is received and analyzed to identify keywords, determine a task, place the keywords in slots of the task and dialogue graph is used to receive the task request information, determiner user intent, use the graph to determine a dialogue act response to the user request and intent, and to perform a task in response to the selected dialogue act . Wen at Abstract; id. at col. 44 ll. 30 – 50 (receive user request); id. at col. 5 ll. 1 – 23, col. 7 ll. 37 – 51, col. 7 ll. 61 – 66, col. 8 ll. 51-56, col. 46 ln. 66 - col. 47 ln. 36 (dialogue graph takes user input, determines a task, intent, and context, and returns a dialogue act response); id. at col. 24 ll. 49 – 50, col. 35 ll. 16 – 21, & col. 45 ll. 22 – 34 (task performance in response to dialogue act).}
Claim 3
With respect to claim 3, Wen and Shen teach the invention as claimed including:
further comprising: determining at least one task performing model optimized to the task of which type is determined among a plurality of task performing models based on the context of the task-oriented dialogues, wherein the performing of the task of which type is determined comprises performing the task by using the determined at least one task performing model. {The system may determine, based on the dialogue act, the context, the intent, and the keywords of the request, the type of task that needs to be performed such as determining which AI model would be most suited to performing the requested task and the system may dispatch the task to the model and report the results of the model accomplishing the task. Shen at Abstract; id. at pg. 2 & fig. 1; id. at pg. 6 (3.2 The best Model to perform task is selected).}
Claim 4
With respect to claim 4 wherein a computing system comprising memory and a processor supports {Wen at fig. 1 and col. 5 ll. 50 – 60.}
at least a part of calculation for the determining of the type of the task and the performing of the task. {The system may determine, based on the dialogue act, the context, the intent, and the keywords of the request, the type of task that needs to be performed such as determining which AI model would be most suited to performing the requested task and the system may dispatch the task to the model and report the results of the model accomplishing the task. Shen at Abstract; id. at pg. 2 & fig. 1; id. at pg. 6 (3.2 The best Model to perform task is selected).}
Claim 7
With respect to claim 7, Wen and Shen teach the invention as claimed including:
wherein the determining of the response dialogue act includes: generating the dialogue graph which models at least one conditional relationship for a dialogue dataset; sampling a plurality of dialogue act groups for responding to the user dialogue input by using a pre-trained dialogue model; adjusting the plurality of dialogue act groups based on the dialogue graph; and selecting one dialogue act group satisfying a predetermined condition among the plurality of dialogue act groups. {A user request is received and analyzed to identify keywords, determine a task, place the keywords in slots of the task and dialogue graph is used to receive the task request information, determiner user intent, use the graph to determine a dialogue act or group of acts in response to the user request and intent, including by adjusting groups of dialogue acts prior to selection based on global rule actions), and to perform a task in response to the selected dialogue act . Wen at Abstract; id. at col. 44 ll. 30 – 50 (receive user request); id. at col. 5 ll. 1 – 23, col. 7 ll. 37 – 51, col. 7 ll. 61 – 66, col. 8 ll. 51-56, col 15, ll. 45 – col. 16, ll. 55, col. 46 ln. 66 - col. 47 ln. 36 (dialogue graph takes user input, determines a task, intent, and context, and returns a dialogue act response and may be updated); id. at col. 24 ll. 49 – 50, col. 35 ll. 16 – 21, & col. 45 ll. 22 – 34 (task performance in response to dialogue act).}
Claim 8
With respect to claim 8, Wen and Shen teach the invention as claimed including:
wherein the at least one conditional relationship includes one or more of a first conditional relationship (a should relationship) indicating what utterance should occur for one utterance in a dialogue flow, a second conditional relationship (a can relationship) indicating what utterance can occur for one utterance in the dialogue flow, or a third conditional relationship (a should-not relationship) indicating what utterance should not occur for one utterance in the dialogue flow. {Conditionals for the dialogues include expected, available global rules, and prohibited “skip_nodes.” Wen at id. at col. 9 ll. 1 – 36, col. 10 ll. 26 – 53, and col. 10 ln. 59 – col. 11 ln 4. col 15, ll. 45 – col. 16, ll. 55}
Claim 9
With respect to claim 9, Wen and Shen teach the invention as claimed including:
wherein the selecting of the one dialogue act group comprises selecting the one dialogue act group which best satisfies the predetermined condition among the plurality of dialogue act groups. {A user request is received and analyzed to identify keywords, determine a task, place the keywords in slots of the task and dialogue graph is used to receive the task request information, determiner user intent, use the graph to determine a dialogue act or group of acts in response to the user request and intent, including by adjusting groups of dialogue acts prior to selection based on global rule actions), and to perform a task in response to the selected dialogue act . Wen at Abstract; id. at col. 44 ll. 30 – 50 (receive user request); id. at col. 5 ll. 1 – 23, col. 7 ll. 37 – 51, col. 7 ll. 61 – 66, col. 8 ll. 51-56, col. 46 ln. 66 - col. 47 ln. 36 (dialogue graph takes user input, determines a task, intent, and context, and returns a dialogue act response and may be updated); id. at col. 24 ll. 49 – 50, col. 35 ll. 16 – 21, & col. 45 ll. 22 – 34 (task performance in response to dialogue act).}
Claim 10
With respect to claim 10, Wen and Shen teach the invention as claimed including:
wherein each of the plurality of dialogue act groups includes one or more dialogue acts for a dialogue input. {A user request is received and analyzed to identify keywords, determine a task, place the keywords in slots of the task and dialogue graph is used to receive the task request information, determiner user intent, use the graph to determine a dialogue act or group of acts in response to the user request and intent, including by adjusting groups of dialogue acts prior to selection based on global rule actions), and to perform a task in response to the selected dialogue act . Wen at Abstract; id. at col. 44 ll. 30 – 50 (receive user request); id. at col. 5 ll. 1 – 23, col. 7 ll. 37 – 51, col. 7 ll. 61 – 66, col. 8 ll. 51-56, col. 46 ln. 66 - col. 47 ln. 36 (dialogue graph takes user input, determines a task, intent, and context, and returns a dialogue act response and may be updated); id. at col. 24 ll. 49 – 50, col. 35 ll. 16 – 21, & col. 45 ll. 22 – 34 (task performance in response to dialogue act).}
Claim 11
With respect to claim 11, Wen and Shen teach the invention as claimed including:
wherein the adjusting of the plurality of dialogue act groups comprises, adding a dialogue act satisfying the first conditional relationship (the should relationship) to each of the plurality of dialogue act groups, removing a dialogue act not satisfying the second conditional relationship (the can relationship) from each of the plurality of dialogue act groups, and removing a dialogue act not satisfying the third conditional relationship (the should-not relationship) from each of the plurality of dialogue act groups. {A user request is received and analyzed to identify keywords, determine a task, place the keywords in slots of the task and dialogue graph is used to receive the task request information, determiner user intent, use the graph to determine a dialogue act or group of acts in response to the user request and intent, including by adjusting groups of dialogue acts prior to selection based on global rule actions), and to perform a task in response to the selected dialogue act . Wen at Abstract; id. at col. 44 ll. 30 – 50 (receive user request); id. at col. 5 ll. 1 – 23, col. 7 ll. 37 – 51, col. 7 ll. 61 – 66, col. 8 ll. 51-56, col. 46 ln. 66 - col. 47 ln. 36 (dialogue graph takes user input, determines a task, intent, and context, and returns a dialogue act response and may be updated); id. at col. 24 ll. 49 – 50, col. 35 ll. 16 – 21, & col. 45 ll. 22 – 34 (task performance in response to dialogue act). Conditionals for the dialogues include expected, available global rules, and prohibited “skip_nodes.” Wen at id. at col. 9 ll. 1 – 36, col. 10 ll. 26 – 53, and col. 10 ln. 59 – col. 11 ln 4.}
Claim 12
With respect to claim 12, Wen and Shen teach the invention as claimed including:
wherein the selecting of the one dialogue act group comprises selecting a dialogue act group having a largest number of dialogue acts satisfying the at least one conditional relationship among the plurality of dialogue act groups. {A user request is received and analyzed to identify keywords, determine a task, place the keywords in slots of the task and dialogue graph is used to receive the task request information, determiner user intent, use the graph to determine the best dialogue act or group of acts in response to the user request and intent, including by adjusting groups of dialogue acts prior to selection based on global rule actions), and to perform a task in response to the selected dialogue act . Wen at Abstract; id. at col. 44 ll. 30 – 50 (receive user request); id. at col. 5 ll. 1 – 23, col. 7 ll. 37 – 51, col. 7 ll. 61 – 66, col. 8 ll. 51-56, col. 46 ln. 66 - col. 47 ln. 36 (dialogue graph takes user input, determines a task, intent, and context, and returns a dialogue act response and may be updated); id. at col. 24 ll. 49 – 50, col. 35 ll. 16 – 21, & col. 45 ll. 22 – 34 (task performance in response to dialogue act). Conditionals for the dialogues include expected, available global rules, and prohibited “skip_nodes.” Wen at id. at col. 9 ll. 1 – 36, col. 10 ll. 26 – 53, and col. 10 ln. 59 – col. 11 ln 4.}
Claim 13
With respect to claim 13, Wen and Shen teach the invention as claimed including:
providing one dialogue act included in the selected one dialogue act group as the response dialogue act responding to the user dialogue input. {A user request is received and analyzed to identify keywords, determine a task, place the keywords in slots of the task and dialogue graph is used to receive the task request information, determiner user intent, use the graph to determine a dialogue act or group of acts in response to the user request and intent, including by adjusting groups of dialogue acts prior to selection based on global rule actions), and to perform a task in response to the selected dialogue act . Wen at Abstract; id. at col. 44 ll. 30 – 50 (receive user request); id. at col. 5 ll. 1 – 23, col. 7 ll. 37 – 51, col. 7 ll. 61 – 66, col. 8 ll. 51-56, col. 46 ln. 66 - col. 47 ln. 36 (dialogue graph takes user input, determines a task, intent, and context, and returns a dialogue act response and may be updated); id. at col. 24 ll. 49 – 50, col. 35 ll. 16 – 21, & col. 45 ll. 22 – 34 (task performance in response to dialogue act). Conditionals for the dialogues include expected, available global rules, and prohibited “skip_nodes.” Wen at id. at col. 9 ll. 1 – 36, col. 10 ll. 26 – 53, and col. 10 ln. 59 – col. 11 ln 4.}
Claim 14
With respect to claim 14, Wen and Shen teach the invention as claimed including:
wherein the providing of the response dialogue act comprises providing a dialogue act having a highest relevance to the user dialogue input as the response dialogue act responding to the user dialogue input among one or more dialogue acts included in the selected one dialogue act group. {A user request is received and analyzed to identify keywords, determine a task, place the keywords in slots of the task and dialogue graph is used to receive the task request information, determiner user intent, use the graph to determine the best dialogue act or group of acts in response to the user request and intent, including by adjusting groups of dialogue acts prior to selection based on global rule actions), and to perform a task in response to the selected dialogue act . Wen at Abstract; id. at col. 44 ll. 30 – 50 (receive user request); id. at col. 5 ll. 1 – 23, col. 7 ll. 37 – 51, col. 7 ll. 61 – 66, col. 8 ll. 51-56, col. 46 ln. 66 - col. 47 ln. 36 (dialogue graph takes user input, determines a task, intent, and context, and returns a dialogue act response and may be updated); id. at col. 24 ll. 49 – 50, col. 35 ll. 16 – 21, & col. 45 ll. 22 – 34 (task performance in response to dialogue act). Conditionals for the dialogues include expected, available global rules, and prohibited “skip_nodes.” Wen at id. at col. 9 ll. 1 – 36, col. 10 ll. 26 – 53, and col. 10 ln. 59 – col. 11 ln 4.}
Claim 17
With respect to claim 17, Wen and Shen teach the invention as claimed including:
wherein the electronic device is configured to receive the user dialogue input in form of one or more of text, voice, gesture, or touch. {Text or speech may be used as input. Wen at Abstract.}
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Wen in view of Shen and Prasad et al., United States Patent Application Publication No. 2022/0244937 (Published August 4, 2022, filed February 1, 2021) (“Prasad”). Claim 5
With respect to claim 5, Wen and Shen teach the invention as claimed including:
wherein the performing of the task comprises …and performing the task by executing the generated programming code for performing the task. {Software updates for a plurality of different platform ECUs, each update consisting of a plurality of subsections/partitions, may be transmitted from a manufacturer repository to vehicle telematics control units of target vehicles, where the telematics control units then distributes the updates to target ECUs for validation and subsequent installation. Wen at Abstract; id. at ¶¶ 0005, 0016, 0020, 0025 – 0027, 0030, 0033; id. at fig. 1.}
However, Wen and Shen doesn’t explicitly teach the limitation:
generating a programming code for performing the task by analyzing a programming code related to the task of which type is determined, {Prasad does teach this limitation. Prasad teaches that selecting a model to perform a task in response to a user request, intent, and context, as taught in Wen and Shen, may include where the selected model uses the request, intent, and context to select software code and modify it in accordance with the request. Prasad at Abstract; id. at ¶¶ 0013, 0033, 0043
Wen, Shen, and Prasad are analogous art because they are from the “same field of endeavor” and are both from the same “problem-solving area.” Specifically, they are both from the field of software development, and both are trying to solve the problem of how to create customized program code.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine selecting a model to perform a task in response to a user request, intent, and context, as taught in Wen and Shen, with selecting software code and modifying it to perform the task, as taught in Prasad. Shen teaches that model descriptions can be used to select the best suited model for a particular task. Shen at Abstract; id. at pg. 2. Therefore, one having ordinary skill in the art would have been motivated to combine selecting a model to perform a task in response to a user request, intent, and context, as taught in Wen and Shen, with selecting software code and modifying it to perform the task, as taught in Prasad, for the purpose of using a known model that can generate code which performs tasks with a method that requires selecting the best model to perform a task.}
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Wen in view of Shen and Marks et al., United States Patent Application Publication No. 2024/0046142 (Published February 8, 2024, filed July 26, 2022) (“Marks”).
Claim 6
With respect to claim 6, Wen and Shen teach the invention as claimed including:
the context of the task-oriented dialogues {Software updates for a plurality of different platform ECUs, each update consisting of a plurality of subsections/partitions, may be transmitted from a manufacturer repository to vehicle telematics control units of target vehicles, where the telematics control units then distributes the updates to target ECUs for validation and subsequent installation. Wen at Abstract; id. at ¶¶ 0005, 0016, 0020, 0025 – 0027, 0030, 0033; id. at fig. 1.}
However, Wen and Shen doesn’t explicitly teach the limitation:
acquiring a user screen shot by capturing a screen of an electronic device from which the user dialogue input is received, wherein the determining of the type of the task requested by the user comprises determining the type of the task based on… and the user screen shot. {Marks does teach this limitation. Marks teaches that selecting a model to perform a task in response to a user request, intent, and context, as taught in Wen and Shen, may include where a portion of the input is a screenshot from which tasks can be identified. Marks at Abstract; id. at ¶ 0141; id. at fig. 10.
Wen, Shen, and Marks are analogous art because they are from the “same field of endeavor” and are both from the same “problem-solving area.” Specifically, they are both from the field of software development, and both are trying to solve the problem of how to create customized program code.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine selecting a model to perform a task in response to a user request, intent, and context, as taught in Wen and Shen, with using screenshots to identify the task, as taught in Marks. Shen teaches that model descriptions can be used to select the best suited model for a particular task. Shen at Abstract; id. at pg. 2. Therefore, one having ordinary skill in the art would have been motivated to combine selecting a model to perform a task in response to a user request, intent, and context, as taught in Wen and Shen, with using screenshots to identify the task, as taught in Marks, for the purpose of using a known model that requires identifying tasks to perform with a method that provides model to recognize tasks from screenshots.}
Conclusion
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//T.H./ September 28, 2026
Examiner, Art Unit 2199
/LEWIS A BULLOCK JR/Supervisory Patent Examiner, Art Unit 2199
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