DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1, 4, 8, 11, 15 and 18 have been amended, claims 2, 3, 8, 10, 16, 17 have been canceled. Claims 1, 4-7, 9, 11-15, 18-20 are pending.
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, 4-7, 9, 11-15, 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims at a high level recite training neural network for name generation.
Step 1: Does the Claim Fall within a Statutory Category?
Yes. Claims 1, 4-7, 9, 11-15, 18-20 recite a method and a system and therefore, are directed to the statutory class of machine and a product.
The USPTO Guidance recites:
(1) any judicial exceptions, including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human activity such as a fundamental economic practice, or mental processes) (Step 2A, Prong 1); and
(2) additional elements that integrate the judicial exception into a practical application (Step 2A, Prong 2). MPEP §§ 2106.04(a), (d).
Only if the claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, do we then look in Step 2B to whether the claim:
(3) adds a specific limitation beyond the judicial exception that is not “well-understood, routine, conventional” in the field; or
(4) simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. MPEP § 2106.05(d).
Step 2A, Prong One: Is a Judicial Exception Recited?
First, determine whether the claims recite any judicial exceptions, including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human activity, or mental processes). MPEP § 2106.04(a).
Claim 1 recites –
▪ receiving a target set comprising words associated with an object type (Abstract Idea of a mental process, see MPEP § 2106.04(a)(2)(III). Under the broadest reasonable interpretation, this limitation is an abstract idea of “a mental process” because it recites a process that can be performed in the human mind (i.e., observation, determination, evaluation, judgment, and opinion) — a user can receive data comprising words);
▪ training a discriminator network and a generator network, wherein the discriminator network is trained with a training data set that is based on the target set and the generator network is trained with random inputs and the discriminator network (Abstract Idea of a mental process, see MPEP § 2106.04(a)(2)(III). Under the broadest reasonable interpretation, this limitation is an abstract idea of “a mental process” because it recites a process that can be performed in the human mind (i.e., observation, determination, evaluation, judgment, and opinion) — a user can have a mental training on historical data to generate new data), and
▪ wherein the discriminator network is trained for two epochs for each epoch for which the generator network is trained (Abstract Idea of a mental process, see MPEP § 2106.04(a)(2)(III). Under the broadest reasonable interpretation, this limitation is an abstract idea of “a mental process” because it recites a process that can be performed in the human mind (i.e., observation, determination, evaluation, judgment, and opinion) — a user can mentally train on epochs); and
▪ generating, with the generator network, words (Amount to “Apply it”. Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, see MPEP § 2106.05(f). Examiner’s note: high level application of using machine learning model to generate words amount to merely invoking a computer component to apply the exception)
▪ receiving guiding metadata (Abstract Idea of a mental process, see MPEP § 2106.04(a)(2)(III). Under the broadest reasonable interpretation, this limitation is an abstract idea of “a mental process” because it recites a process that can be performed in the human mind (i.e., observation, determination, evaluation, judgment, and opinion) — a user can receive metadata);
▪ during training of the discriminator network and the generator network, using the guiding metadata in the training of the generator network (Abstract Idea of a mental process. Under the broadest reasonable interpretation, the obtaining/determining probability distribution and divergence, as drafted, is an abstract idea of “a mental process” because it recites a process that can be performed in the human mind (i.e., observation, determination, evaluation, judgment, and opinion) — a user can obtain metadata and facilitate training based on such metadata.);
▪ wherein using the guiding metadata in the training of the generator network further comprises determining with an NLP transformer network whether words output by the generator network during the training of the generator network match the guiding metadata (Amount to mere instruction to apply the abstract idea using a generic computer component. A mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).).
These limitations, based on their broadest reasonable interpretation, recite a mental process, i.e. a judicial exception. For these reasons, the independent claim 1, as well as independents claims 8 and 15, which include limitations commensurate in scope with claim 1, recite a judicial exception.
A method, like the claimed method, “a process that employs mathematical algorithms to manipulate existing information to generate additional information is not patent eligible.” See Digitech Image Techs, LLC v. Elecs. for Imaging, Inc., 758 F.3d 1344, 1351 (Fed. Cir. 2014). See Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016) where collecting information, analyzing it, and displaying results from certain results of the collection and analysis was held to be an abstract idea. See In re Meyer, 688 F.2d 789, 795—96 (CCPA 1982), which held that “a mental process that a neurologist should follow” when testing a patient for nervous system malfunctions was not patentable.
Accordingly, the claims recite an abstract idea.
Step 2A, Prong Two: Is the Abstract Idea Integrated into a Practical Application?
Next determine whether the claims recite additional elements that integrate the judicial exception into a practical application (see MPEP §§ 2106.05(a)-(c), (e)-(h)). To integrate the exception into a practical application, the additional claim elements must, for example, improve the functioning of a computer or any other technology or technical field (see MPEP § 2106.05(a)), apply the judicial exception with a particular machine (see MPEP § 2106.05(b)), or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment (see MPEP § 2106.05(e)).
Additional elements:
▪ a discriminator network and a generator network (Amount to “Apply it”. Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, see MPEP § 2106.05(f). Examiner’s note: high level application of using machine learning model to generate words amount to merely invoking a computer component to apply the exception);
▪ network is trained with a training data set (Adding insignificant extra-solution activity to the judicial exception - see MPEP § 2106.05(g));
The term “additional elements” for claim features, limitations, or steps that the claim recites beyond the identified judicial exception. Claim 1 recites the additional elements of “discriminator network and a generator network”, claim 8 additionally recite “one or more storage devices; and a processor” and claim 15 recites “one or more computers and one or more storage devices.” However, claims do not recite any improvements to these additional elements, nor does the claims recite any particularly programmed or configured computer system, device, or machine learning. Rather, the additional elements in claims 1, 8 and 15 serve merely to automate the abstract idea. See Int’l Bus. Machs. Corp. v. Zillow Group, Inc., 50 F. 4" 1371, 1382 (Fed. Cir. 2022) (“[A] patent that ‘automate[s] “pen and paper methodologies” to conserve human resources and minimize errors’ is a ‘quintessential “do it on a computer” patent’ directed to an abstract idea.”) (quoting Univ. of Fla. Rsch. Found., Inc. v. Gen. Elec. Co., 916 F.3d 1363, 1367 (Fed. Cir. 2019)). Therefore, none of these recited additional elements, whether considered individually or in combination, integrates the judicial exception into a practical application.
The additional elements listed above that relate to computing components are recited at a high level of generality (i.e., as generic components performing generic computer functions such as communicating and processing known data) such that they amount to no more than mere instructions to apply the exception using generic computing components. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. Additionally, the claims do not purport to improve the functioning of the computer itself. There is no technological problem that the claimed invention solves. Rather, the computer system is invoked merely as a tool. Accordingly, the 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. Therefore, these claims are directed to an abstract idea.
Step 2B: Does the Claim Provide an Inventive Concept?
Next, determine whether the claims recite an “inventive concept” that “must be significantly more than the abstract idea itself, and cannot simply be an instruction to implement or apply the abstract idea on a computer.” BASCOM Glob. Internet Servs., Inc. v. AT&T Mobility LLC, 827 F.3d 1341, 1349 (Fed. Cir. 2016); see MPEP § 2106.05(d). There must be more than “computer functions [that] are “well-understood, routine, conventional activit[ies]’ previously known to the industry.” Alice Corp. v. CLS Bank Int'l, 573 U.S. 208, 225 (2014) (second alteration in original) (quoting Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 73 (2012)); see MPEP § 2106.05(d).
Step 2B: The additional elements are not sufficient to amount to significantly more than the judicial exception.
Additional elements: (see MPEP 2106.05(d)(Il). Taking the claim elements separately, the function performed by the computer at each step of the process is purely conventional. Using a computer and associated computer network to obtain data, use data to identify other data, and comparing data, are some of the most basic functions of a computer. All of these computer functions are well-understood, routine, conventional activities previously known to the industry. The method claims do not, for example, purport to improve the functioning of the computer itself. Nor do they effect an improvement in any other technology or technical field. Instead, the claims at issue amount to nothing significantly more than an instruction to apply the abstract idea of displaying, processing and storing data using some unspecified, generic computer).
Note, that in similar case, such as Collecting information, analyzing it, and displaying certain results of the collection and analysis (Electric Power Group), the Courts have identified that the additional elements of displaying and analyzing data, as shown in the independent claims 1, 7 , 15 do not amount to significantly more than the judicial exception. Consequently, that is not enough to transform an abstract idea into a patent-eligible invention.
No “inventive concept” sufficient to transform the abstract method of organizing human activity into a patent-eligible application. See MPEP § 2106.05. Rather, the additional elements identified above are merely well-understood, conventional computer components, as confirmed by the Specification. See MPEP § 2106.05(d)(1). For example, the Specification refers to the additional elements in generic terms.
As discussed above with respect to integration of the abstract idea into a practical application, the additional elements relating to computing components amount to no more than applying the exception using a generic computing components. Mere instructions to apply an exception using a generic computing component cannot provide an inventive concept. Furthermore, the broadest reasonable interpretation of the claimed computer components (i.e., additional elements) includes any generic computing components that are capable of being programmed to communicate and process known data.
Additionally, the computer components are used for performing insignificant extra-solution activity and well understood, routine, and conventional functions. For example, the claimed processor and machine learning merely communicates and processes known data. Activities such as these are insignificant extra-solution activity and, therefore, well understood, routine, and conventional. See MPEP 2106.05(d); see also, e.g., OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d at 1363, 115 USPQ2d at 1092-93 (Presenting offers to potential customers and gathering statistics generated based on the testing about how potential customers responded to the offers; the statistics are then used to calculate an optimized price); CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (Obtaining information about transactions using the Internet to verify credit card transactions); Ultramercial, Inc. v. Hulu, LLC, 772 F.3d at 715, 112 USPQ2d at 1754 (Consulting and updating an activity log); Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016) (Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display); Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1244, 120 USPQ2d 1844, 1856 (Fed. Cir. 2016) (Recording a customer’s order); Return Mail, Inc. v. U.S. Postal Service, -- F.3d --, -- USPQ2d --, slip op. at 32 (Fed. Cir. August 28, 2017) (Identifying undeliverable mail items, decoding data on those mail items, and creating output data); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015) (Arranging a hierarchy of groups, sorting information, eliminating less restrictive pricing information and determining the price). Furthermore, limitations such as integrating account details are well-understood, routine, and conventional activity. See Alice Corp., 134 S. Ct. at 2359, 110 USPQ2d at 1984 (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log).
Independent system claim 1, 8 and 15 contain the identified abstract ideas, with the additional elements of a processor, hardware and the media, which is a generic computer component, and thus not significantly more for the same reasons and rationale above. Accordingly, independent claims 1, 8 and 15 are patent ineligible because they are directed to an abstract idea that does not recite an inventive concept that amounts to significantly more than the abstract idea.
Dependent claims 2-7, 9-14, 16-20 do not recite additional limitations that demonstrate integration of the abstract idea into a practical application or an inventive concept that amounts to significantly more than the abstract idea.
With respect to claims 4, 11 and 18:
Step 2A Prong 1: the claims recite a judicial exception (an abstract idea)
▪ wherein the guiding metadata comprises options selected for properties of words (Abstract Idea of a mental process. Under the broadest reasonable interpretation, the obtaining/determining probability distribution and divergence, as drafted, is an abstract idea of “a mental process” because it recites a process that can be performed in the human mind (i.e., observation, determination, evaluation, judgment, and opinion) — a user can analyze words and select options.)
Step 2A Prong 2: the additional elements that are not sufficient to integrate the judicial exception into a practical application. Additional elements: training of the generator network and NLP transformer amount to mere instruction to apply the abstract idea using a generic computer component. The additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. A mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).) Step 2B: the additional element is not sufficient to amount to significantly more than the judicial exception. Therefore, claims 2-3, 9-10 and 16-17 is ineligible.
With respect to claims 5, 12 and 19:
▪ receiving an indication of the object type; gathering the words associated with the object type from one or more websites associated with objects of the object type; and generating the target set from the gathered words associated with the object type (Abstract Idea of a mental process. Under the broadest reasonable interpretation, the obtaining/determining probability distribution and divergence, as drafted, is an abstract idea of “a mental process” because it recites a process that can be performed in the human mind (i.e., observation, determination, evaluation, judgment, and opinion) — a user can mentally determine words / target set based on a type).
Additional elements: the additional element listed above in step 2A Prong 2 is merely instructions to be implemented on a generic computer component. Therefore, the additional element does not amount to an inventive concept, particularly when the activity is well understood or conventional (MPEP 2106.05(d)). Step 2A Prong 1: The claim does not recite any of the judicial exceptions enumerated in the 2019 PEG. Step 2A Prong 2: The judicial exception is not integrated into a practical application.
With respect to claims 6-7, 13-14 and 20:
▪ initiating a hyperparameter search that uses sets of dimensions for the generator network and the discriminator network (Abstract idea of “a mathematical concept” — see MPEP § 2106.04(a)(2)(l). Note: under the broadest reasonable interpretation of the claim, the claimed invention encompasses mathematical concept (e.g., Mathematical Formula or Equations)).
▪ initializing the discriminator network with weights that preserve variance; and initializing the generator network with weights that are orthogonal matrices (i.e. additional generic mathematical evaluation, which performs the determination, thereby further defining the abstract idea. A human being may use this mathematical calculation to facilitate the mental evaluation in order to arrive at the necessary determination. This claim limitation appears to recite both a mathematical formula and mental process. See at least MPEP § 2106.05(a) ("Improvements to the Functioning of a Computer or to Any Other Technology or Technical Field"));
Step 2A Prong 1: The claim does not recite any of the judicial exceptions enumerated in the 2019 PEG. Step 2A Prong 2: The judicial exception is not integrated into a practical application.
Therefore, dependent claims 4-7, 11-14 and 18-20 further describe the abstract idea. The additional elements of the dependent claims fail to integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea. Thus, as the dependent claims remain directed to a judicial exception, and as the additional elements of the claims do not amount to significantly more, the dependent claims are not patent eligible. As such, the claims are not patent eligible.
Claim Objections /Construction
Claims 1, 8 and 15 are objected to because of the following informalities:
Claim 1 recites – “A computer-implemented comprising,” which should be corrected to “A computer-implemented method comprising.”
Claims 1, 8 and 15 further recite the acronym "NLP" without first defining the acronym in the claim. Acronyms should be defined in the claims. For the purpose of examining it will be assumed that it was meant -- Natural Language Processing --.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 8 and 15 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Pinheiro e Mota et al. (US 20210352032).
Regarding claims 1, 8 and 15, Pinheiro e Mota a teaches a computer-implemented method, computer-implemented system and a system comprising: one or more computers and one or more storage devices comprising:
receiving a target set comprising words ([0026] “matrix data set from text message inputs”, “message data are collected from a target”, [0033], [0036]) associated with an object type ([0041], [0046]);
training a discriminator network and a generator network, wherein the discriminator network is trained with a training data set that is based on the target set and the generator network is trained with random inputs and the discriminator network ([0027]-[0028], [0040]), and
wherein the discriminator network is trained for two epochs for each epoch for which the generator network is trained ([0028]-[0029]); and
generating, with the generator network, words ([0033]-[0034])
receiving guiding metadata ([0020], [0026], wherein “touch activation matrix” associated with the message is the guiding metadata); and
during training of the discriminator network and the generator network, using the guiding metadata in the training of the generator network ([0026]-[0029]), wherein using the guiding metadata in the training of the generator network further comprises determining with an NLP transformer network ([0043] see analyzing received message in natural language, [0046]) whether words output by the generator network during the training of the generator network match the guiding metadata ([0034], [0040]-[0041]).
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.
Claims 1,4-5, 8, 11-12, 15, 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Voinea et al. (US 11797705) in view of Tran (US 20230351102).
Regarding claim 1, Voinea teaches a computer-implemented comprising:
receiving a target set (C17L35-50) comprising words associated with an object type (C3L25, 29-30, 33-33540-44, 53-56, C4L12-14, C5L30-37);
training a discriminator network and a generator network, wherein the discriminator network is trained with a training data set that is based on the target set and the generator network is trained with random inputs and the discriminator network (C10L1-29), and
wherein the discriminator network is trained for two epochs for each epoch for which the generator network is trained (C10L30-50, C11L8-30); and
generating, with the generator network, words (C13L23-25)
receiving guiding metadata (C4L34-55, C5L42-58, C6L1-9, 19-65); and
during training of the discriminator network and the generator network, using the guiding metadata in the training of the generator network (C5L60-63, C10L8-30, 50-55, C11L7-30, C16L14-25 “trained, ANN … based on extracted features”, wherein extracted features comprise guiding metadata C7L44-47 “based on identification of named entity types and metadata to create extracted features representing both named entities and associated context,” F5A),
wherein using the guiding metadata in the training of the generator network further comprises determining with an NLP transformer network whether words output by the generator network during the training of the generator network match the guiding metadata (C3L41-44, C5L31-63, C16L17-22, note the named entity recognition (NER) is a part or subtask of NLP).
Voinea teaches identifying sensitive data in a target dataset by entity recognition, which “LSTM network … generate synthetic sensitive data based on training set” and “produce output … which correspond to words "Michael", "Apple", and "Blue"”(C13L23-25, wherein LSTM network is generator C11L31-33), and “publish a sensitive data summary” (C17L49-50), which reasonably and obviously generates words. However, such words are intended for different purposes (not naming). Thus, to further obviates the teachings of Voinea, Tran discloses –
generating, with the generator network, words ([0064], [0072], [0094]).
NOTE Tran further discloses receiving guiding metadata; during training of the discriminator network and the generator network, using the guiding metadata in the training of the generator network ([0042], [0074], [0094], [0109]-[0130], [0185], [0209]),
wherein using the guiding metadata in the training of the generator network further comprises determining with an NLP transformer network ([0069]) whether words output by the generator network during the training of the generator network match the guiding metadata ([0108], [0143], [0148]-[0152], [0160]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Voinea to include generating, with the generator network, words as disclosed by Tran. Doing so provides a visual and intuitive user interface with built-in semantic and technical understanding and automatic relevant suggestions that serves as a writing assistant (Tran [0010]).
Claims 8 and 15 recite substantially the same limitations as claim 1, and is rejected for substantially the same reasons.
Regarding claims 4, 11 and 18, Voinea as modified teaches the method and the system, wherein the guiding metadata comprises options selected for properties of words (Tran [0069]-[0070]).
Regarding claims 5, 12 and 19, Voinea as modified teaches the method and the system, further comprising:
receiving an indication of the object type (Voinea C340-44, 53-56, 63-65, C5L30-63, Tran [0137]-[0138], [0214], [0224]);
gathering the words associated with the object type from one or more websites associated with objects of the object type (Tran [0181]-[0184], [0192], [0220]-[0223], [0257]); and
generating the target set from the gathered words associated with the object type (Tran [0139]-[0140], [0185], [0187], [0300]).
Claims 6, 13 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Voinea as modified and in further view of SINN et al. (US 20230185912).
Regarding claims 6, 13 and 20, Voinea as modified does not explicitly teach, however SINN discloses the method and the system, wherein training the discriminator network and the generator network further comprises initiating a hyperparameter search that uses sets of dimensions for the generator network and the discriminator network (SINN [0087], [0091]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Voinea to include hyperparameter search as disclosed by SINN. Doing so provides a automated evaluation of robustness of machine learning models (SINN [0016]).
Claims 7 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Voinea as modified and in further view of Bai et al. (US 20210342643) or Martens et al. (US 20230107247).
Regarding claims 7 and 14, Voinea as modified teaches the method and the system, further comprising, before training the discriminator network and the generator network:
initializing the discriminator network with weights
Voinea as modified does not explicitly teach, however Bai discloses initializing the discriminator network with weights that preserve variance ([0146]); and initializing the generator network with weights that are orthogonal matrices ([0169]- [0170]). Martens discloses the same in [0106], [0110].
It would have been obvious to one of ordinary skill in the art at the time of invention to modify the teachings of Voinea as modified to include representation vectors in an orthogonal feature space as disclosed by Bai or Martens. Doing so would achieve efficiency requirements for pattern recognition (Bai [0068]).
Claims 3, 10 and 17 is/are additionally or alternatively rejected under 35 U.S.C. 103 as being unpatentable over Voinea as modified and in further view of SINN et al. (US 20230185912).
Regarding claims 3, 10 and 17, Voinea as modified teaches the method and the system as stated above, Arai additionally discloses wherein using the guiding metadata in the training of the generator network further comprises determining with an NLP transformer network whether words output by the generator network during the training of the generator network match the guiding metadata (C6L51-67, C9L1-10, C7L28-40, C10L15-19).
Regarding claims 4, 11 and 18, Voinea as modified teaches the method and the system as stated above, Arai additionally discloses the method and the system, wherein the guiding metadata comprises options selected for properties of words (C7L1-67).
Regarding claims 5, 12 and 19, Voinea as modified teaches the method and the system as stated above, Arai additionally discloses the method and the system, further comprising: receiving an indication of the object type (C7L35-40); gathering the words associated with the object type from one or more websites associated with objects of the object type (C11L46-63, C12L65-67); and generating the target set from the gathered words associated with the object type (C7L30-34, C8L3-10, 40-44).
It would have been obvious to one of ordinary skill in the art at the time of invention to modify the teachings of Voinea as modified to include NLP processing as disclosed by Arai. Doing so would achieve desired information to be efficiently acquired (Arai C12L30).
Response to Arguments
Applicant's arguments filed 10/30/2025 have been fully considered but they are not persuasive.
With respect to the rejection under 35 USC 101, the applicant argues that the features of the independent claims “constitute a technical improvement in the field of training generator networks. The end result of the “using the guiding metadata in the training of the generator network” in the present claims is overall improvement in the generation of words by the . The claim further uses an NLP transformer with the guiding metadata in the training of the generator network. Automatic generation of words can itself be considered a technical field under MPEP 2106.04(d)(1), and the claims are thus directed to an improvement in a technical field without monopolizing any judicial exception.”
The arguments are not persuasive. The user is interacting with the computer in a conventional manner. Relatedly, the computer, that is to say the hardware upon which the program is operating, is operating in an entirely conventional manner. The proposed technical effect is not causing the computer in of itself to operate different as the method is operating at the level of application and thus is not interacting with the hardware at a level beyond that which any computer program would do so. Similarly, the computer upon which the program is operating is not operating more efficiently or effectively. The computer itself is operating entirely conventionally and the contribution is not having an effect on the efficiency of the computer itself.
The additional elements do not: (1) improve the functioning of a computer or other technology; (2) are not applied with any particular machines (except for a generic computer); (3) do not effect a transformation of a particular article to a different state; and (4) are not applied on any meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP §§ 2 106.05(a) (c), (e) (b). In other words, the aforementioned additional element (or combination of elements) recited in the claims do not integrate the judicial exception into a practical application. See Revised Guidance, 84 Fed. Reg. at 54- 55 ("Prong 2"). Second, the use of computer hardware and/or software components to optimize the processing of data may improve the abstract idea, but, in this context, is not a technological improvement. Appeal Br.5; see Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363. 1367 (Fed. Cir. 2015).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, under Step 2A, Prong Two (MPEP §§ 2106.05(a)-(c) and (e) (h)), the claims do not integrate the judicial exception into a practical application. The rejection is maintained.
Applicant's remaining arguments, in regard to the presently amended claims, are addressed in the updated rejections to the claims above.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to POLINA G PEACH whose telephone number is (571)270-7646. The examiner can normally be reached Monday-Friday, 9:30 - 5:30.
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/POLINA G PEACH/Primary Examiner, Art Unit 2165 November 13, 2025