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 .
Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statement filed 05/24/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claims 5, 9, 14, 18 and 20 are objected to because of the following informalities:
Claim 5:
Line 3 recites “machine leaning model”, which should be rewritten as “machine learning model”.
Line 6 recites “machine leaning model”, which should be rewritten as “machine learning model”.
Claim 9:
Line 4 recites “an training example optimization problem”, which should be rewritten as “a training example optimization problem” OR “training an example optimization problem”.
Claims 14 and 18 are system claims that contain similar issues of claims 5 and 9, respectively. Therefore, claims 14 and 18 are objected under the same rationale.
Claim 20:
Line 1 recites “A computer readable medium storing non-transitory instructions”, which should be rewritten as “A non-transitory computer readable medium storing instructions” for consistency with paragraph [0027] of the Specification.
Line 4 recites “based on the natural language text description”, which lacks of antecedent basis. Appropriate correction is required.
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 filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual 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/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-9, 11-18 and 20 of U.S. Patent No. 12,001,779 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1-9, 11-18 and 20 of U.S. Patent No. 12,001,779 B2 teach every limitation of claims 1-20 of the instant application.
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 (i.e., changing from AIA to pre-AIA ) 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (Chen), CA 3079066A1, published on 12/20/2020, and further in view of Pregasen et al., (Pregasen), US Patent Application Publication No. US 2018/0293211A1 (Both Chen and Pregasen are from IDS filed on 05/24/2024).
As to independent claim 1, Chen discloses a computer implemented method comprising:
receiving a natural language text description of an optimization problem (Figure 3 and paragraph [0069]: receiving input data for the plurality of parameters of the specific optimization problem via a template; Also see Figures 4A and 4B for examples of receiving input data);
generating, based on the natural language text description, a text markup language intermediate representation (IR) of the optimization problem, the text markup language IR including an IR objective declaration that defines an objective for the optimization problem and a first IR constraint declaration that indicates a first constraint for the optimization problem (Figures 4A and 4B show representation of the input data of the specific optimization problem via a template, wherein the representation of the input data includes parameters (objective declaration) and constraints/parameter values); and
generating, based on the text markup language IR, an algebraic modelling language (AML) formulation of the optimization problem, the AML formulation including an AML objective declaration that defines the objective for the optimization problem and a first AML constraint declaration that 15 indicates the first constraint for the optimization problem (paragraphs [0119], [0123] and Figure 7: constructing at least one NP formulation for a specific optimization problem; paragraph [0129] and Figure 8: formulating first objective function and second objective function from at least one NP formation for specific optimization problem; paragraph [00143]: wherein the formulated objective function may be submitted in an Algebraic Modelling language (AML) format).
Chen, however, does not disclose intermediate representation (IR) of the optimization problem is a text markup language.
In the same field of endeavor, Pregasen discloses a formula system for transforming a formula natural language representation (NLR) into a representation which shows the formula in traditional mathematical notation (Abstract). Pregasen further discloses receiving a natural language representation of a formula (NLR) and then performing pre-transformation procedures on the NLR by matching parts of NLR to transition mapping, and initiating a new state indicated by the mapping destination of the transition mapping matched, wherein initiating a new state can include a series of state start actions that can produce context for performing other action of the state or of other states and/or can produce state results, such as a portion of output representing the formula, e.g., a block of HTML (Figure 4 and paragraphs [0036]-[0041]). Pregasen further discloses the constructor can a function for generating HTML from the NLR that will transform the received text into corresponding HTML, e.g., by extracting portions from the NLR and inserting them into one or more HTML templates (paragraph [0041]).
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 system of Chen to include intermediate representation (IR) of the optimization problem is a text markup language, as taught by Pregasen for the purpose of displaying/rendering the formula representation in markup-language version.
As to dependent claim 2, Chen discloses wherein the text markup language IR also includes one or more further constraint declarations each indicating a respective further constraint for the optimization problem, and the AML formulation includes one or more further AML constraint declarations indicating the respective further constraints (paragraph [0034]).
As to dependent claim 3, Chen discloses mapping the AML formulation to a solver language representation of the optimization problem (paragraphs [0119], [0123], [0129], [0143]); and
providing the solver language representation to an optimization solver to output a solution for the optimization problem (paragraph [0026]).
As to dependent claim 4, Chen and Pregasen disclose wherein generating the text markup language IR comprises:
generating, based on the text markup language IR, an objective declaration prompt that includes information about the objective for the optimization problem and a first constraint declaration prompt that includes information about the first constraint for the optimization problem (Chen, Figures 4A-4B; Pregasen, paragraph [0041]);
providing the objective declaration prompt and the natural language text description to a transformer to generate the IR objective declaration (Chen, Figures 4A-4B); and
providing the first constraint declaration prompt and the natural language text description to the transformer to generate the first IR constraint declaration (Chen, Figures 4A-4B).
As to dependent claim 5, Chen discloses wherein generating the objective declaration prompt and the first constraint declaration prompt comprises:
recognizing, using a first trained machine leaning model, declaration entities included in the natural language text description that correspond to a set of pre-defined type categories (paragraph [0105]);
identifying, using a second trained machine learning model, recognized declaration entities that are co-references (paragraph [0105]); and
assembling the objective declaration prompt and the first constraint declaration prompt based on the recognized declaration entities and the identified co-references (paragraph [0105]).
As to dependent claim 6, Chen discloses prior to providing the objective declaration prompt to the transformer, communicating the objective declaration prompt to a user input/output module to enable a user to approve or modify the objective declaration prompt (paragraph [0069]); and
prior to providing the first constrain declaration prompt to the transformer, communicating the first constrain declaration prompt to the user input/output module to enable the user to approve or modify the first constrain declaration prompt (paragraph [0069]).
As to dependent claim 7, Chen and Pregasen disclose wherein the IR objective declaration and IR constraint declaration are each generated using a machine learning based transformer that receives the natural language text description as an input, the method comprising training the transformer to extract and copy selected entities from the natural language text description into one or both of the IR objective declaration and the first IR constraint declaration (Pregasen, paragraph [0041].
As to dependent claim 8, Chen discloses performing an objective declaration validation check of the IR objective declaration by inputting the natural language text description and the IR objective declaration to a machine learning model that is trained to predict if an input IR declaration includes an error (paragraphs [0160]-[0164]);
performing a constraint declaration validation check of the first IR constraint declaration by inputting the natural language text description and the first IR constraint declaration to the machine learning model (paragraphs [0160]-[0164]); and
communicating results of the objective declaration validation check and the constraint declaration validation check to a user input/output module for presentation to a user (paragraphs [0160]-[0164]).
As to dependent claim 9, Chen discloses augmenting a training dataset for training the machine learning model by generating a set of erroneous IR declarations for a respective training example of a natural language text description of an training example optimization problem by perturbing entities included in a ground truth IR declaration respective training example of the natural language text description (paragraph [0105]).
As to dependent claim 10, Chen discloses performing an objective declaration validation check of the AML objective declaration by inputting the IR objective declaration and the AML objective declaration to a machine learning model that is trained to predict if an input AML declaration includes an error (paragraphs [0119], [0123], [0129], [0143]);
performing a constraint declaration validation check of the fist AML constraint declaration by inputting the first IR constraint declaration and the first AML constraint declaration to the machine learning model (paragraphs [0119], [0123], [0129], [0143]); and
communicating results of the objective declaration validation check and the constraint declaration validation check to a user input/output module for presentation to a user (paragraphs [0119], [0123], [0129], [0143]).
Claims 11-19 are system claims that contain similar limitations of claims 1, 3-10, respectively. Therefore, claims 11-19 are rejected under the same rationale.
Claim 20 is medium claim that contains similar limitations of claim 1. Therefore, claim 20 is rejected under the same rationale.
Conclusion
Any inquiry concerning this communication should be directed to CHAU T NGUYEN at telephone number (571)272-4092. The examiner can normally be reached on M-F from 8am to 5pm (PT).
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) Form at https://www.uspto.gov/patents/uspto-automated-interview-request-air-form.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Cesar Paula, can be reached at telephone number 5712724128. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from Patent Center and the Private Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from Patent Center or Private PAIR. Status information for unpublished applications is available through Patent Center and Private PAIR for authorized users only. Should you have questions about access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
/CHAU T NGUYEN/Primary Examiner, Art Unit 2145
Prosecution Insights